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Primary students’ group metacognitive processes in a computer supported collaborative learning environment
Dissertation submitted in fulfillment of the requirements for the degree of Doctor of Philosophy
Centre for Learning Innovation, Faculty of Education
By Christina Chalmers (B.Ed)
Queensland University of Technology 2009
ABSTRACT
The current understanding of students’ group metacognition is limited. The
research on metacognition has focused mainly on the individual student. The aim of
this study was to address the void by developing a conceptual model to inform the use
ii
of scaffolds to facilitate group metacognition during mathematical problem solving in
computer supported collaborative learning (CSCL) environments. An initial
conceptual framework based on the literature from metacognition, cooperative
learning, cooperative group metacognition, and computer supported collaborative
learning was used to inform the study. In order to achieve the study aim, a design
research methodology incorporating two cycles was used. The first cycle focused on
the within-group metacognition for sixteen groups of primary school students working
together around the computer; the second cycle included between-group
metacognition for six groups of primary school students working together on the
Knowledge Forum® CSCL environment. The study found that providing groups with
group metacognitive scaffolds resulted in groups planning, monitoring, and evaluating
the task and team aspects of their group work. The metacognitive scaffolds allowed
students to focus on how their group was completing the problem-solving task and
working together as a team. From these findings, a revised conceptual model to
inform the use of scaffolds to facilitate group metacognition during mathematical
problem solving in computer supported collaborative learning (CSCL) environments
was generated.
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KEYWORDS
Computer supported collaborative learning (CSCL), group learning, group
metacognition, group problem solving, groups, Knowledge Forum®, online teams,
shared understanding, task, team.
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TABLE OF CONTENTS
ABSTRACT ......................................................................................................................... i
KEYWORDS ..................................................................................................................... iii
TABLE OF CONTENTS ................................................................................................... iv
LIST OF TABLES ........................................................................................................... viii
LIST OF FIGURES .............................................................................................................x
STATEMENT OF ORIGINAL AUTHORSHIP .............................................................. xii
ACKNOWLEDGEMENTS ............................................................................................. xiii
DEDICATION ................................................................................................................. xiii
CHAPTER 1 INTRODUCTION .........................................................................................1 1.1 Overview of the study ..............................................................................................4 1.2 Discussion of terms ..................................................................................................5
1.2.1 Groups and teams ........................................................................................... 5 1.2.2 Group problem solving and learning ............................................................. 6 1.2.3 Group problem solving with computers ........................................................ 7 1.2.4 Metacognition ................................................................................................ 8 1.2.5 Group metacognition ..................................................................................... 8
1.3 Significance of study................................................................................................9 1.4 Chapter Overviews .................................................................................................10 1.5 Conclusion .............................................................................................................11
CHAPTER 2: LITERATURE REVIEW ...........................................................................13 2.1 Group problem solving and learning .....................................................................14
2.1.1 Organisational factors .................................................................................. 16 2.1.1.1 Strategies to address organisational factors ........................................ 23
2.1.2 Cognitive factors .......................................................................................... 33 2.1.2.1 Strategies to address cognitive factors ................................................ 36
2.1.3 Summary ...................................................................................................... 41 2.2 Group metacognitive factors ..................................................................................43
2.2.1 Group metacognitive strategies .................................................................... 47 2.2.2 Group metacognitive scaffolds .................................................................... 49 2.2.3 Summary ...................................................................................................... 54
2.3 Conclusion .............................................................................................................55
CHAPTER 3: RESEARCH DESIGN AND METHOD ....................................................57 3.1 Research design .....................................................................................................57 3.2 Data Collection and Analysis .................................................................................59
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3.2.1 Observations ................................................................................................ 60 3.2.1.1 Participant observation........................................................................ 61 3.2.1.2 Video recordings ................................................................................. 62 3.2.1.3 Audio (MP3) recordings ..................................................................... 62
3.2.2 Focus group interview.................................................................................. 63 3.2.3 Classroom artefacts ...................................................................................... 64
3.2.3.1 Diaries ................................................................................................. 64 3.2.3.2 Checklists ............................................................................................ 65 3.2.3.3 Questionnaires..................................................................................... 68 3.2.3.4 Knowledge Forum notes ..................................................................... 70 3.2.3.5 Mathematical ranking models ............................................................. 70
3.3 Procedure ...............................................................................................................71 3.3.1 Stage 1: Cycles of design experiment .......................................................... 71
3.3.1.1 Cycle 1: Within-group metacognition ................................................ 74 3.3.1.2 Cycle 2: Within- and between-group metacognition .......................... 89
3.3.2 Stage 2: Development of a unified conceptual model ................................. 99 3.4 Conclusion ...........................................................................................................100
CHAPTER 4: RESULTS FROM CYCLE 1 ...................................................................103 4.1 Organisational themes ..........................................................................................104
4.1.1 Theme 1 ..................................................................................................... 104 4.1.2 Theme 2 ..................................................................................................... 106 4.1.3 Theme 3 ..................................................................................................... 110 4.1.4 Theme 4 ..................................................................................................... 112 4.1.5 Theme 5 ..................................................................................................... 117 4.1.6 Theme 6 ..................................................................................................... 120 4.1.7 Organisational themes summary ................................................................ 122
4.2 Cognitive themes .................................................................................................124 4.2.1 Theme 7 ..................................................................................................... 124 4.2.2 Theme 8 ..................................................................................................... 127 4.2.3 Cognitive themes summary ........................................................................ 128
4.3 Metacognitive themes ..........................................................................................129 4.2.1 Theme 9 ..................................................................................................... 130 4.3.2 Theme 10 ................................................................................................... 134 4.3.3 Metacognitive themes summary ................................................................ 143
4.4 Focus-group interview .........................................................................................144 4.5 Summary and conclusion .....................................................................................146 4.6 Implications for Cycle 2.......................................................................................147
CHAPTER 5: RESULTS FROM CYCLE 2 ...................................................................151 5.1 Organisational themes ..........................................................................................152
5.1.1 Theme 1 ..................................................................................................... 153 5.1.2 Theme 2 ..................................................................................................... 155 5.1.3 Theme 3 ..................................................................................................... 157 5.1.4 Theme 4 ..................................................................................................... 159 5.1.5 Theme 5 ..................................................................................................... 162
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5.1.6 Theme 6 ..................................................................................................... 164 5.1.7 Organisational themes summary ................................................................ 166
5.2 Cognitive themes .................................................................................................167 5.2.1 Theme 7 ..................................................................................................... 168 5.2.2 Theme 8 ..................................................................................................... 171 5.2.3 Theme 9 ..................................................................................................... 172 5.2.4 Cognitive themes summary ........................................................................ 175
5.3 Metacognitive themes ..........................................................................................175 5.3.1 Theme 10 ................................................................................................... 176 5.3.2 Theme 11 ................................................................................................... 179 5.3.3 Metacognitive themes summary ................................................................ 186
5.4 Focus group interview ..........................................................................................187 5.5 Summary and conclusion .....................................................................................188
CHAPTER 6: DEVELOPMENT OF UNIFIED CONEPTUAL MODEL ......................189 6.1 Overview of results ..............................................................................................189
6.1.1 Problem-solving task ................................................................................. 190 6.1.2 Organisational factors ................................................................................ 192
6.1.2.1 Summary ........................................................................................... 195 6.1.3 Cognitive factors ........................................................................................ 196
6.1.3.1 Summary ........................................................................................... 198 6.1.4 Group metacognition ................................................................................. 199
6.2 Group metacognitive model .................................................................................203 6.2.1 Problem-solving context ............................................................................ 204 6.2.2 Organisational factors ................................................................................ 206 6.2.3 Cognitive factors ........................................................................................ 208 6.2.4 Metacognitive factors ................................................................................. 210 6.2.5 Discussion .................................................................................................. 211
6.3 Application of group metacognition model .........................................................215 6.4 Conclusion ...........................................................................................................217
CHAPTER 7: CONCLUSION ........................................................................................219 7.1 Overview of the study ..........................................................................................219 7.2 Significance..........................................................................................................221
7.2.1 Theoretical significance ............................................................................. 222 7.2.2 Practical significance ................................................................................. 224
7.3 Limitations ...........................................................................................................226 7.4 Recommendations for further research ................................................................228 7.5 Conclusion ...........................................................................................................229
REFERENCES ................................................................................................................231
APPENDICES .................................................................................................................261 APPENDIX A: Checklist to observe group behaviour ..............................................261 APPENDIX B: Metacognitive questionnaire ............................................................262 APPENDIX C: Self regulatory checklist ...................................................................263 APPENDIX D: Interview questions ..........................................................................264 APPENDIX E: Initial individual questionnaire .........................................................265
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APPENDIX F: Final individual questionnaire ..........................................................266 APPENDIX G: Group cohesiveness questionnaire ...................................................267 APPENDIX H: Lesson plan.......................................................................................268 APPENDIX I: City information .................................................................................274 APPENDIX J: Newspaper article ..............................................................................282 APPENDIX K: Group roles, skills, and problem-solving strategies .........................283 APPENDIX L: Group diary checklists ......................................................................284 APPENDIX M: Final overall ranking system: Cycle 1 .............................................288 APPENDIX N: T-chart ..............................................................................................290 APPENDIX O: Knowledge Forum guide ..................................................................291 APPENDIX P: Group categories ...............................................................................293 APPENDIX Q: List of categories ..............................................................................294 APPENDIX R: CD: Australia’s best city ..................................................................295 APPENDIX S: Excel guide .......................................................................................296 APPENDIX T: Final CD: Cycle 1 .............................................................................297 APPENDIX U: Bales’ Interaction Process Analysis .................................................298 APPENDIX V: Group metacognition coding ............................................................299 APPENDIX W: Mathematical model for Team One ................................................300 APPENDIX X: Posters ..............................................................................................302 APPENDIX Y: IPA Coding for each group ..............................................................306
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LIST OF TABLES
Table 2.1. Group roles ...................................................................................................... 29
Table 2.2. Strategic questions ........................................................................................... 39
Table 3.1. Data collection methods .................................................................................. 60
Table 3.2. Cycle 1 data collected and method of analysis ................................................ 85
Table 3.3. Formation of online teams ............................................................................... 91
Table 3.4. Cycle 2 data collected and method of analysis ................................................ 98
Table 4.1. IPA domain frequency ................................................................................... 106
Table 4.2. IPA category frequency ................................................................................. 110
Table 4.3. Responses to question two on initial individual questionnaire ...................... 118
Table 4.4. Responses to question seven on final individual questionnaire ..................... 119
Table 4.5. Responses to question three on initial individual questionnaire ................... 121
Table 4.6. Frequency of task-skills chosen ..................................................................... 126
Table 4.7. Frequency of team-skills chosen ................................................................... 127
Table 4.8. Metacognitive questionnaire .......................................................................... 131
Table 4.9. Group metacognition coding for Group C .................................................... 137
Table 4.10. Group metacognition coding for Group E ................................................... 138
Table 4.11. Group plan to solve the problem and reach the goal .................................. 140
Table 5.1. IPA domain frequency ................................................................................... 154
Table 5.2. IPA domain frequency for both cycles ........................................................... 155
Table 5.3. IPA category frequency ................................................................................. 158
Table 5.4. Responses to question three on initial individual questionnaire ................... 163
Table 5.5. Responses to question four on initial inidividual questionnaire .................... 165
Table 5.6. Frequency of group roles chosen ................................................................... 169
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Table 5.7. Frequency of task skills chosen ..................................................................... 170
Table 5.8. Frequency of team skills chosen .................................................................... 170
Table 5.9 Responses to group cohesiveness questionnaire ............................................ 174
Table 5.10. Metacognitive questionnaire ........................................................................ 177
Table Y1. IPA frequency count for each category for Group A ..................................... 308
Table Y2. IPA frequency count for each category for Group B ..................................... 311
Table Y3. IPA frequency count for each category for Group C ..................................... 314
Table Y4. IPA frequency count for each category for Group D .................................... 316
Table Y5. IPA frequency count for each category for Group E ..................................... 319
Table Y6. IPA frequency count for each category for Group F ..................................... 322
Table Y7. IPA frequency count for each category for Group G .................................... 324
Table Y8. IPA frequency count for each category for Group H .................................... 326
Table Y9. IPA frequency count for each category for Group I ...................................... 328
Table Y10. IPA frequency count for each category for Group J .................................... 330
Table Y11. IPA frequency count for each category for Group K ................................... 332
Table Y12. IPA frequency count for each category for Group L ................................... 334
Table Y13. IPA frequency count for each category for Group M .................................. 336
Table Y14. IPA frequency count for each category for Group N ................................... 338
Table Y15. IPA frequency count for each category for Group O .................................. 340
Table Y16. IPA frequency count for each category for Group P ................................... 342
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LIST OF FIGURES
Figure 2.1. Model representing organisational factors ..................................................... 23
Figure 2.2. Model representing cognitive factors ............................................................. 36
Figure 2.3. Factors influencing efficiency of group problem solving and learning ......... 42
Figure 2.4. Group problem solving and learning factors .................................................. 43
Figure 2.5. Model representing metacognitive factors ..................................................... 45
Figure 2.6. Scaffolding group metacognition ................................................................... 52
Figure 2.7. Conceptual framework ................................................................................... 56
Figure 3.1. Phases of design cycles .................................................................................. 72
Figure 6.1. Complex problem solving context ............................................................... 204
Figure 6.2. Organisational factors .................................................................................. 208
Figure 6.3. Cognitive factors .......................................................................................... 209
Figure 6.4. Group metacognition model ......................................................................... 211
Figure 7.1. Final model .................................................................................................. 220
Figure Y1. IPA domain frequencies for Group A ........................................................... 306
Figure Y2. IPA domain frequencies for Group B ........................................................... 309
Figure Y3. IPA domain frequencies for Group C ........................................................... 312
Figure Y4. IPA domain frequencies for Group D ........................................................... 315
Figure Y5. IPA domain frequencies for Group E ........................................................... 317
Figure Y6. IPA domain frequencies for Group F ........................................................... 320
Figure Y7. IPA domain frequencies for Group G ........................................................... 323
Figure Y8. IPA domain frequencies for Group H ........................................................... 325
Figure Y9. IPA domain frequencies for Group I ............................................................ 327
Figure Y10. IPA domain frequencies for Group J .......................................................... 329
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Figure Y11. IPA domain frequencies for Group K ......................................................... 331
Figure Y12. IPA domain frequencies for Group L ......................................................... 333
Figure Y13. IPA domain frequencies for Group M ........................................................ 335
Figure Y14. IPA domain frequencies for Group N ......................................................... 337
Figure Y15. IPA domain frequencies for Group O ......................................................... 339
Figure Y16. IPA domain frequencies for Group P ......................................................... 341
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STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted for a degree or a
diploma at any other higher education institution. To the best of my knowledge and
belief, the thesis contains no materials previously published or written by another
person, except where due reference is made.
Signature
Date
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ACKNOWLEDGEMENTS
Thanks to my supervisors, faculty, and family who have helped me reach this
point in my academic career.
I am most grateful to my supervisor, Associate Professor Rod Nason for his
continual support and guidance. Rod has been both mentor and friend. I also want to
thank my other supervisor Professor Cam McRobbie for his contribution to this study.
I wish to warmly thank my friends and colleagues in the School of
Mathematics, Science, and Technology (QUT) - a group in which I have the honour
of belonging to. An acknowledgement also needs to be made to the Australian
Postgraduate Award committee for their financial support.
Finally, I owe my warmest thanks to my home team – my husband Wayne and
my three inspiring daughters Kelsey, Ella, and Jenna. Thank you for your continuous
love, support, and patience.
DEDICATION
In the spirit of groups and teams, this study could not have been completed without
the support and encouragement of my own.
1
CHAPTER 1 INTRODUCTION
Problem solving and thinking mathematically are crucial tools for
participating in the twenty-first century’s knowledge society. Students need to be
able to apply mathematical knowledge to solve problems (Queensland Studies
Authority, 2004). However, effective problem solving involves not only finding a
solution but also metacognitively monitoring the problem-solving activity (Goos,
Galbraith, & Renshaw, 2002). Difficulties in problem solving can occur if
students fail to metacognitively monitor and regulate their cognitive processes
(Garafalo & Lester, 1985; Schoenfeld, 1983).
Research in mathematical problem solving and metacognition has tended
to focus on the individual learner (Hoyles & Healy, 1994; Hurme & Järvelä,
2001). However, many researchers in the field, such as Stahl (2006), feel that the
focus needs to shift from the individual to the group and how the group solves
problems and represents knowledge. This research study addresses the need for a
shift from a focus on the individual to a focus on the group within the field of
mathematical problem solving and metacognition.
A shift in focus from the individual learner to the group is necessary for
two reasons. First, the use of group problem solving is increasing both in
education and work fields (Beatty & Barker, 2004; Dundis & Benson, 2003; Salas
& Fiore, 2004). Second, the proliferation of computer supported collaborative
learning (CSCL) and computer supported collaborative work (CSCW)
2
environments in education and work fields is increasing due to the wide use of
computers (Ackerman, 2000; Bromme, Hesse, & Spada, 2005; Stahl, 2006).
Working in a group gives students access to a wide range of thinking
strategies, contributes to students’ understanding of the problem, and provides
alternative solutions (Cohen, 1994; Cullen, 1999; Gillies, 2000; Jonassen &
Kwon, 2001). However, while several studies have shown that groups are more
productive than individuals in complex problem solving, not all groups work
together cooperatively (Cohen, 1994; Johnson & Johnson, 2003; Sims, Salas, &
Burke, 2005).
In order to work effectively as a group, students need to think about their
group work by planning, monitoring, and evaluating their learning processes
within a group context (Goos et al., 2002; Hurme, Palonen, & Järvelä, 2006).
Metacognition is an essential element of group problem solving (Hinsz, 2004).
Activities such as planning how to approach a given learning task, monitoring
progress, and evaluating progress toward the completion of the task are
metacognitive processes that play a critical role in successful group learning and
problem solving.
Some researchers have suggested that computer settings can increase the
possibility of successful group learning and problem solving, as students are more
likely to work together when working on computer based tasks (Kreijns,
Kirschner, & Jochems, 2002; Light, 2004; Underwood & Underwood, 1999).
3
Computers provide a medium for group problem solving by encouraging
discussion and sharing both within- and between-groups (Beamish & Au, 1995).
The purpose of computer supported collaborative learning (CSCL) thus is
to support students in learning together effectively. CSCL supports the
communication of ideas and information among learners, collaborative accessing
of information and documents, and peer feedback on learning activities (Hurme &
Järvelä, 2001). CSCL also supports and facilitates group processes and group
dynamics in ways that are not achievable by face-to-face communication, such as
having learners label aspects of their communication (Stahl, Koschmann, &
Suthers, 2006). However, CSCL environments have often not fulfilled
expectations as researchers and practitioners have failed to provide the support
that groups need to succeed (Kreijns et al., 2002).
Therefore, the aim of this study was to develop a conceptual model to
inform the use of scaffolds for within- and between-group metacognition, for
primary school students, during mathematical problem solving in CSCL
environments. In order to meet the aim of the research study, three specific
objectives were addressed:
1. To evaluate scaffolds to facilitate within-group metacognition during
mathematical problem solving for groups working around a computer.
2. To evaluate scaffolds to facilitate between-group metacognition while
building collective knowledge within a CSCL environment.
4
3. To synthesise the findings from Objectives 1 and 2 into a unified
conceptual model to inform the use of scaffolds to facilitate within- and
between-group metacognition within CSCL environments.
1.1 Overview of the study
In order to address the aim and the three research objectives, a two stage
research study was conducted. The major focus in Stage 1 was on Research
Objectives 1 and 2 whilst the focus in Stage 2 was on Research Objective 3.
A ‘design research’ methodology incorporating a descriptive case study
was utilised in Stage 1. There were two cycles of design research experiments in
Stage 1 of the study. Each of the two cycles consisted of three successive phases
of (1) planning, (2) conducting, and (3) analysing and refinement. In Cycle 1, an
initial conceptual framework based on an analysis and synthesis of the research
literature was utilised to inform the planning of scaffolds for within-group
metacognition. The implementation of these scaffolds occurred in two primary
classrooms from two different schools. The data from the implementation of the
scaffolds were then analysed. Following this, refinements were made to not only
the scaffolds but also to the underlying initial conceptual framework. In Cycle 2,
the refined conceptual framework and set of scaffolds were applied in both
within- and between-group contexts in two classrooms from two different
schools. Following a process of planning, conducting, analysing and refinement
5
similar to that utilised in Cycle 1, further refinements were made to the conceptual
framework. In Stage 2, the outcomes from Stage 1 (Cycles 1 and 2) were
synthesised into a group metacognition model that provides a unified conceptual
framework for the field of scaffolding group metacognition.
1.2 Discussion of terms
Throughout the course of this dissertation, reference often will be made to
terminology that has its genesis in the research literature. In order to provide an
advance organiser for the detailed review of the research literature that follows in
Chapter 2, a discussion of each of the following terms is now presented:
Groups and teams
Group problem solving and learning
Group computer work
Metacognition
Group metacognition
1.2.1 Groups and teams
A group is a number of people who communicate with one another over a
period of time (Benjamin, Bessant, & Watts, 1997). Shaw (1981) defined a group
as two or more individuals who interact with each other and are influenced by
each other. A group requires at least three people in order for certain group roles,
norms, and processes to emerge (Gottlieb, 2003; Samovar, Henman, & King,
6
1996). Teams are groups of people that share a common purpose (Thomas, 1992).
All teams are groups; however, the reverse is not always true as teams focus on
both the group task and on the group relationships (Kormanski, 1999).
1.2.2 Group problem solving and learning
The use of problem-solving groups is increasing both in work and
education fields (Beatty & Barker, 2004; Dundis & Benson, 2003; Salas & Fiore,
2004). Therefore, in order to provide authentic learning opportunities for students,
it is important that they work in problem-solving groups within mathematics
classrooms (Lesh & Lamon, 1992; Light, 2004; Zawojewski, Lesh, & English,
2003). Group learning improves students’ mathematical understanding as well as
improving their communication and group skills (Haller, Gallagher, Weldon, &
Felder, 2000).
Groups can master mathematical problems too complex for individuals to
solve alone (Jonassen & Kwon, 2001). While problem solving in groups, students
have opportunities to ask questions, explain their reasoning, build upon their
knowledge, and discuss and develop problem-solving strategies (Curcio & Artzt,
1998; Gillies, & Ashman, 2000; Soller, 2001). The most effective learning
contexts for groups are problem-based (Jonassen & Kwon, 2001). Problem-based
learning increases motivation, develops critical thinking, and deepens
understanding of learning content.
7
One type of complex and open-ended mathematical problem-solving tasks
that has been found to facilitate dynamic group discussion and knowledge
building is model-eliciting activities (Lesh & Doerr, 2003; Nason & Woodruff,
2003). Model-eliciting activities are mathematical-based tasks that present
realistic problem scenarios and often require students to work together as a group
to develop a model that can be used to solve the problem situation (Lesh & Harel,
2003).
1.2.3 Group problem solving with computers
The recognition of the educational importance of group problem-solving
has resulted in groups working together around computers (Hoyles & Healy,
1994; Neufeld & Haggerty, 2001; Seymour, 1994; Stahl et al., 2006). The
computer is a medium through which groups can communicate their
understanding and provides a way to represent and store shared knowledge
(Bereiter & Scardamalia, 1989; Crook, 1999; Reyna, Branerd, Effken, Bootzih, &
Lloyd, 2001; Sherman, 2001). Students collaboratively construct knowledge using
the shared interface that can be used to support group work by providing
scaffolding for them working together (Beamish & Au, 1995; Etheris & Tan,
2004; Lee, Chan, & van Aalst, 2006).
Small groups interacting around and through the computer promotes
productive collaborative learning (Littleton & Light, 1999). Crook (1996)
investigated how computers can facilitate collaborative learning and highlighted
8
the difference between interacting through and around computers. Interacting
around computers refers to using the computer as a shared reference for a group
while interaction through computers refers to the use of a computer network.
The Knowledge Forum® software was used in this study as the CSCL
environment that allowed groups of students to engage with other groups through
a community database. Scardamalia and Bereiter (1994) stated that Knowledge
Forum© supports a student-centred open-ended learning environment where
students are actively engaged in knowledge building.
1.2.4 Metacognition
Metacognition involves students engaging in thinking about the nature of
the learning task and the social context in which learning takes place (Honess,
1986; Schoenfeld, 1983; Xiaodong, 2001). Metacognition is a form of cognitive
self-monitoring (Gama, 2000). It refers to self-knowledge about how one thinks
and includes the ability to self-regulate one’s learning, which is the degree that
students are active participants in their own learning process (Schunk &
Zimmerman, 1994).
1.2.5 Group metacognition
Group metacognition is part of a wider educational view of facilitating
self-regulation and is basically “what group members know about the way groups
process information” (Hinsz, Tindale, & Vollrath, 1997, p. 58). Groups of
9
students need to develop a type of co-cognition in order to collaboratively develop
concepts and monitor their group performance (Costa & O'Leary, 1992).
Metacognition in groups includes the expectations group members have
about the way groups process and perform tasks (Hinsz, 2004). The focus on
shared group knowledge shifts the focus away from the individual learner and
groups need to set their own learning goals and monitor their progress towards the
goals (Klimoski & Mohammed, 1994).
1.3 Significance of study
There has been a shifting focus from the individual learner to a view of
learning as a social practice (Aldag & Fuller, 1993; Lave & Wenger, 1991;
Scardamalia & Bereiter, 1994; Stahl, 2006). Students need to be engaged in group
contexts where they can express their ideas, question each other, elaborate on
their thinking and receive feedback from their peers (Gillies & Ashman, 2003;
Kramarski & Mevarech, 2003).
The current understanding of students’ group metacognition is based on a
relatively narrow body of research (Hurme & Järvelä, 2001; Xiaodong, 2001).
The research has focused mainly on the development of strategies for problem
solving. Goos et al. (2002) suggested that the potential for group problem solving
to develop students’ group skills combined with their problem-solving skills has
remained largely unexplored. This study seeks to address this void by first
investigating students’ group metacognitive strategies during a complex model-
10
eliciting problem-solving activity in a CSCL environment and second by
developing a theoretical framework to inform further research and practice in this
field.
In addition to its theoretical significance, the present research study also
has practical significance. A condition of a CSCL environment is that students are
metacognitive about their group work within the computer setting (Hurme &
Järvelä, 2001). Metacognitive strategies need to be taught and students need to be
supported in their group problem solving by providing metacognitive scaffolding
for the group process.
There is a need to bridge the cognitive skills associated with problem
solving and group work in order to develop a successful problem-solving group.
The joint construction of understanding concerned with the negotiation of
meaning in collaborative group work involves students thinking about their group
work. The combination of collaborative learning, problem solving, and
computers, leads to a learning community where metacognition is essential to
group learning.
1.4 Chapter Overviews
Chapter 1 provides information on the background of the research. The
significance of the study is examined and a summary of relevant literature is
given. Chapter 2 reviews the relevant literature and provides a foundation for the
study pertaining to group work, metacognition, and group metacognition. Chapter
11
3 outlines the research methodology used in this study, including data collection
and analysis. The chapter examines the research design in detail. A description of
data collection is given including interviews and questionnaires used to obtain the
data, as well as details on the selection of the participants of the study. Chapter 4
presents the results from Cycle 1 of the study, which describes the effects of
introducing group metacognitive strategies to groups working around a computer.
Chapter 5 presents the results from Cycle 2, which describes the effects of
introducing group metacognitive strategies to groups working within a computer
supported collaborative learning (CSCL) environment. The findings from both
cycles of the research study are analysed and discussed in Chapter 6 in order to
develop a final unified conceptual model to inform the design of scaffolds to
facilitate group metacognition within CSCL environments. Finally in Chapter 7 a
conclusion to the study is provided, limitations are discussed, and
recommendations are made for future research.
1.5 Conclusion
This study investigates the development of group strategies by introducing
group metacognitive scaffolds within-groups of primary school students working
at the computer and between-groups working together on the Knowledge Forum®
CSCL environment. Both collaborative learning and metacognition have been
widely researched, (Blakey & Spence, 1990; Chizhik, 1998; Johnson & Johnson,
1999). However, there is limited research on the relationship between them. The
12
research study reported in the following chapters addresses this void in research
on group learning and metacognition.
13
CHAPTER 2: LITERATURE REVIEW
This chapter reviews the relevant literature from a number of research
disciplines on group work, metacognition, problem solving, and computer
supported collaborative learning (CSCL) environments and provides a foundation
for the study pertaining to group problem solving and learning (see Section 2.1)
and group metacognition (see Section 2.2). The results from the literature review
are accumulated in the conclusion of this chapter (see Section 2.3) and an initial
conceptual framework is provided (see Figure 2.7).
The major points from the literature review are synthesised into a
conceptual framework that will inform the research study. The group
metacognition framework introduces the idea of group members building a shared
model or representation in order to develop a shared understanding during group
problem solving.
The shared group understanding is facilitated by CSCL environments,
such as the Knowledge Forum® software used in this study, which scaffolds the
problem-solving process. This review will focus on how to scaffold group
metacognition in order to develop successful problem solving within-groups
working around a computer and between-groups working together on the
Knowledge Forum® CSCL environment.
14
2.1 Group problem solving and learning
Within the research literature, group problem solving and learning is often
referred to as either collaborative or co-operative learning (Gut, 2000; Mueller &
Fleming, 1994; O’Neil, Chuang, & Chung, 2003; Oxford, 1997). Collaborative
learning is distinguished from cooperative learning in that cooperative learning is
described as the sharing of a task where each person is responsible for a portion of
the task, whereas collaboration involves the coordinated effort of group members
to achieve the task together (Dillenbourg, Baker, Blaye, & O' Malley, 1996).
Collaborative learning is a coordinated activity resulting from a continual
attempt to construct and maintain a shared understanding (Teasley & Roschelle,
1993). It occurs when a group of students work together to accomplish a shared
learning goal and is linked to a wide range of positive learning outcomes
(Chizhik, 1998; Teasley & Roschelle, 1993). Cooperative learning is the use of
small groups in order to accomplish a group task (Johnson & Johnson, 1999).
Cooperative learning involves the sharing and exchange of ideas among students
and is effective for achieving intellectual as well as social learning goals (Cohen,
1994; Haller et al., 2000).
The corpus of knowledge about group problem solving and learning,
derived from research into collaborative and co-operative learning over the last
thirty years, indicates that students’ learning in successful groups can achieve
higher cognitive levels than working alone (Brown & Palincsar, 1989; Johnson &
Johnson, 1999; Vygotsky, 1978). When students interact with their peers during
15
problem-solving activities, cognitive restructuring can occur (King, 1989).
Working together on a common goal, students encourage one another’s learning,
leading to a co-construction of ideas that could not be achieved individually
(Slavin, 1995). Groups can share ideas, develop common goals, as well as learn
from and support each other’s learning (Benjamin et al., 1997). Students share
understanding and encourage each other to complete the group task and learning
occurs through this collaborative interaction with peers (Barron, 2000).
According to Crook (1996) computers can support collaboration by
providing students with a point of shared reference that supports a group
understanding. Group learning tasks incorporating the computer tend to encourage
interactions amongst students (King, 1989). The computer focuses the group
attention on the mutually shared object (Crook, 1999; O’Malley, 1995;
Puntambekar, 2006; Stahl et al., 2006). Students also engage in more task-related
interaction when they work on computer tasks in cooperative groups (Jonassen &
Kwon, 2001; Poole & Zhang, 2005).
In recent years, a new dimension has been added to collaborative learning
with computers in the form of Computer Supported Collaborative Learning
(CSCL) environments. CSCL environments support and scaffold collaborative
problem-solving and knowledge building and students can collaboratively
construct knowledge using a shared interface that supports group work and
scaffolds their working together (Jonassen & Kwon, 2001; O'Malley , 1995;
Wang, Hinn, & Kanfer, 2001).
16
While numerous studies suggest that group problem solving is more
productive than individual problem solving, merely organising students into
groups around the computer and telling them to work together does not guarantee
they will cooperate and learn as a group (Fiore & Schooler, 2004; Gillies, 2003;
Johnson & Johnson, 1999; McWhaw, Schnackenberg, Sclater, & Abrami, 2003;
Shah, Dirks, & Chervany, 2006; Stahl, 2006). As West (2004) pointed out, ‘good’
groups do not occur naturally. A review of the research literature indicates that
most prior research and practice into collaborative group learning tended to focus
on either organisational or cognitive factors. Both the organisational and cognitive
factors need to be considered to provide the conditions necessary for successful
group problem solving and learning.
2.1.1 Organisational factors
Organisational factors influence how students successfully work as a
group to solve problems. In most classes, when students are assigned to group
work, they tend to seek information from each other and work “in” groups rather
than “as” a group (Johnson & Johnson, 1999; Ogden, 2000). Working in groups
involves students working individually on the same task while working as a group
involves students working together to complete the one task. If students do not
know how to work as a group, they will need constant supervision (Cohen, 1994).
Learning how to work successfully as a group is not a simple process
(Cohen, 1994; Johnson & Johnson, 1999; Tuckman & Jensen, 1977). To become
17
a successful problem solving and learning group often entails students proceeding
through a series of stages. Many researchers have studied how groups develop
and have identified definable stages of group development (Bales, 1970; Bales &
Cohen, 1979; Mennecke, Hoffer, & Wynee, 1992; Tubbs, 1995; Tuckman &
Jensen, 1977).
Bales (1970) analysed group statements and formed a model of the
structure of group discussion which included three stages of group development:
orientation, evaluation, and control (Bales & Cohen, 1979). Mennecke et al.
(1992) identified five group development stages: orientation, exploration,
normalisation, production, and termination. Tubbs’ (1995) stages included:
orientation, conflict, consensus, and closure. While Wheelan’s (1990) stages of
dependency and inclusion, counterdependency and flight, trust and structure,
working productively and finalisation, are similar to the stages proposed by
Tuckman and Jensen (1977). All of these models have highlighted a progression
through the stages of group development from the initial orientation, or inclusion
stage to the final control, closure, or finalisation stage.
Tuckman and Jensen’s (1977) group development stages are the most
widely used group development model. Tuckman and Jensen identified five
stages through which groups typically develop: forming, storming, norming,
performing, and adjourning. During the group forming stage, group members
form a group, either online or face-to-face. Group members seek acceptance by
the group and conflict is avoided as members get to know one another. The major
18
group orientation concerns the task and relationships begin to form among group
members.
Groups enter the storming stage when members begin to risk conflict as
they deal with issues such as who is responsible for what, and conflicts occur over
leadership, structure, and authority (Tuckman & Jensen, 1977). Conflict is often
an inevitable part of group work and can enhance the group decision-making
process (Goos et al., 2002; Korsgaard, Brodt, & Sapienza, 2003; West, 2004).
Students can gain a shared understanding of the task by engaging in task-related
conflict (Crook, 1996; Rentsch & Zelno, 2003). However, West (2004) cautioned
that conflict can also be destructive and lead to poor team performance.
Group conflict can be based on either task or team issues. Task conflicts
tend to be related with positive group outcomes and usually pertain to group
procedures, roles, and resources. Team based conflict involves socio-emotional
conflict that is associated negatively with group work (Rentsch & Zelno, 2003;
Wheelan, 2005). West (2004) also highlighted three types of conflict: task, team,
and interpersonal. Task conflict leads to differences of opinion and is desirable for
effective teamwork while team and interpersonal conflict can be destructive to the
team. The major group task during the storming phase is the development of an
ability to listen and seek productive resolutions to conflict.
As groups begin dealing with conflicts, the third stage of development,
norming, occurs as groups achieve group cohesion and are able to work
productively. Leadership is shared and members share both task and socio-
19
emotional information. Members begin to experience a sense of belonging to the
group and have positive feelings regarding the resolution of group conflicts.
Membership of the group is maintained by groups reinforcing acceptable group
behaviours (Benjamin et al., 1997). When students work toward a group goal they
tend to form behaviour norms in order for the group to succeed (Benjamin et al.,
1997; Slavin, 1995). Norms tend to regulate group learning. Each group defines
its own norms for their group and depends on how group members accept and
apply norms in order to achieve a balance between task work and team work
(Beatty & Baker, 2004). Movement to the next stage requires evolving group
interdependence.
The fourth stage, performing, involves members working interdependently
as a group. Group members are task and team oriented. This productive phase of
group development is one that is achieved by only a relatively small percentage of
groups (Tuckman & Jensen, 1977). The final stage of group development,
adjourning, involves groups completing the group task and involves giving
members opportunity for reflection and encouraging an open discussion of
feelings.
Tuckman and Jensen’s (1977) model of team development suggested a
progression through the stages. However, many teams can waver between stages
(Langan-Fox, 2003). Tuckman and Jensen (1977) also suggested that most groups
fail to achieve and move past the third stage of development, norming, which
occurs as groups achieve group cohesion and are able to work productively
20
together. The fourth stage, performing, which involves members working together
interdependently as a group, occurs in only a small percentage of groups (Langan-
Fox, 2003).
Johnson, Johnson, and Johnson-Holubec (1993) suggested that in order for
students to work together productively, five elements must be incorporated into
learning activities.
These five elements are:
1. Face-to-face interaction
2. Social skills
3. Individual accountability
4. Positive interdependence
5. Group processing
Face-to-face interaction enables learners to encourage and assist each
other’s learning. Research in face-to-face education contexts confirms the benefits
of group learning (Archer-Kath & Johnson, 1994). However, some researchers
have questioned this assumption and have noted benefits of group learning
mediated by computer networks rather than by face-to-face interaction (Hiltz,
1994; Hron & Friedrich, 2003). Jonassen and Kwon (2001) suggested that groups
communicating face-to-face are more personal, while using computers group
communications are more task-orientated. In both face-to-face and online groups,
21
students can share resources and support and encourage each other’s learning, as
well as maintain an awareness of what other group members are doing.
Group skills such as social skills, communication skills, and conflict
resolution skills are important components of achieving a successful group.
Dishon and O’Leary (1984) divided group skills into task and maintenance skills.
Task skills are associated with the specific problem-solving task and maintenance
skills are the social skills used in order to maintain the group in working order.
According to Armstrong and Priola (2001), groups must perform two kinds of
processes: one concerned with completing the task, and the other with
maintaining the group. Hayes (2002) suggested that groups require regular
maintenance to be effective and that groups need scaffolds in order to adopt group
maintenance behaviours. Group maintenance behaviours include contributing
ideas, expressing feelings, active listening skills, expressing support, encouraging
others, checking for understanding, and performing various group roles (Cohen,
1994; Dishon & O’Leary, 1984).
Individual accountability is where each group member is accountable for
the group goal and leads to a situation where individual group member’s learning
maximises the group’s learning (Johnson & Johnson, 1999). Archer-Kath and
Johnson (1994) suggested one way to structure individual accountability is to
provide feedback on the extent to which group members are engaging in targeted
group roles or skills.
22
Positive interdependence is a group state where each group member must
depend on other group members to accomplish the shared task. Members share
common goals and encourage each other’s efforts to reach the group goals.
Interdependence combines goal interdependence, task interdependence, resource
interdependence, role interdependence, and reward interdependence (Johnson &
Johnson, 1999). Johnson and Johnson (1987) stated that when positive
interdependence is present students will be sitting close together, talking about the
task work, sharing ideas, and encouraging each other to learn.
Finally, group processing allows a general assessment of how groups are
functioning to achieve their goals (Benjamin et al., 1997). Group processing
involves groups reflecting on how they are functioning and adjusting behaviours
and strategies in order to have a successful group outcome (Johnson et al., 1993).
The purpose of group processing is to constantly improve the effectiveness of
group learning (Johnson & Johnson, 1999).
Most of the organisational factors identified and discussed in this section
of the literature review do not operate in isolation; they operate in an interrelated
way such as indicated in Figure 2.1. In this figure, the interrelationship between
key seminal ideas from Cohen (1994), Johnson and Johnson (1999) and Tuckman
and Jensen (1977) have been integrated into a model of organisational factors that
influence group problem solving and learning. This model highlights that the six
elements of interaction, constructive conflict, social skills, individual
accountability, positive interdependence, and group processing, need to be
23
incorporated in order for a group to progress through the group development
stages.
Organisational factors
Forming
Storming
Norming
Performing
Adjourning
Interaction face-to-face and on-line
Constructive conflict
Social skills
Individual accountability
Positive interdependence
Group processing
Figure 2.1. Model representing organisational factors.
2.1.1.1 Strategies to address organisational factors
The following section discusses specific strategies that address the
organisational factors relevant to group problem solving and learning, including
problem-solving skills, group skills, conflict management skills, observation and
feedback, group roles, computer-support for group problem solving and learning,
and problem-solving tasks.
24
Problem-solving skills: Problem solving is a multi-step procedure where
the group needs to develop a plan to reach a solution (Hoover, 2002). Groups
need to develop a range of skills for solving problems (Dishon & O’Leary, 1984;
Jonassen & Kwon, 2001). There is inconsistency within the literature regarding
the teaching of problem-solving skills. Some propose explicit teaching of skills
(e.g., Hoek, Terwel, & van den Eeden, 1997; Malouff, 2006). Others suggest that
choosing appropriate skills is learnt by solving a variety of problems and
reflecting on the effective skills used (e.g., Delclos & Harrington, 1991; De Corte,
Greer, & Verschaffel, 1996). However, there is general agreement in the literature
that groups need to learn to monitor and adjust the problem-solving skills they are
using as they solve a problem (Garofalo & Lester, 1985).
Problem-solving skills can be classified into two categories; skills to help
represent the problem and skills to help solve the problem. Skills to help represent
the problem include restating the problem, stating the goal of the problem,
simplifying the problem, drawing a diagram, making a table, making a list, and
acting the problem out (Berardi-Coletta, Buyer, Dominowski, & Rellinger, 1995;
De Corte et al., 1996; Dominowski, 1998; Malouff, 2006). While skills to help
solve the problem include solving a simpler problem, working backwards,
guessing and checking, and looking for patterns (Bransford & Stein, 1993;
Nickerson, 1994).
Structuring mathematics lessons so that students work in groups to discuss
the problem and explain their use of problem-solving skills helps students engage
25
in the components of problem solving (Johnson & Johnson, 1990; Yackel, Cobb,
& Wood, 1991). Talking through mathematical problems in groups helps students
understand how to solve the problems correctly together (Johnson & Johnson;
Puntambekar, 1999).
Group skills: Students need to be taught specific group skills in order for
them to work successfully in groups. Cohen (1994) noted that some students have
no group strategies other than physical or verbal assault. Students need to be
taught how to work together and specific teaching should deal with the
cooperative behaviours that are required by group work. Therefore, the first step
in preparing students for working together is to teach specific group skills (Cohen,
1994).
Group skills such as social skills, communication skills, and conflict
resolution skills are important components of achieving a successful group.
Groups must perform two kinds of processes: those concerned with completing
the task, and others concerned with maintaining the group (Armstrong & Priola,
2001). Group skills can be divided into task skills and maintenance skills (Dishon
& O’Leary, 1984). Task skills are associated with the specific problem-solving
task and maintenance skills are the social skills used in order to maintain the
group in working order.
Task skills included checking group understanding (Johnson et al., 1993),
giving ideas (Farivar & Webb, 1994), sharing information (Barron, 2000), talking
26
about the work, getting the group back to work (Tjosvold, West, & Smith, 2003),
repeating what has been said (Dillenbourg et al., 1996), and asking questions
(Johnson, & Johnson, 1990). Maintenance skills included encouraging, checking
for agreement, encouraging other members to talk, sharing feelings, keeping
things calm (Johnson et al., 1993), responding to ideas (Dickson & McIntyre,
1997), using eye contact (Gillies & Ashman, 2000), and saying ‘thank you’
(Farivar & Webb, 1994).
Students need to learn what group skills are available and when they
should be used appropriately (Hayes, 2002; Johnson et al., 1993). One way to
improve the effectiveness of a group is to improve the interaction skills of its
members (Barker, Abrams, Tiyaamornwong, & Seibold, 2000). Group skills need
to be explicit and involve basic social skills such as sharing responsibility,
discussing group goals, active listening, as well as negotiating conflicts (Cohen,
1994; West, 2004).
Conflict management skills: Skills for managing conflict constructively
are important for the success of the group (Johnson et al., 1993). Therefore,
groups need to be taught conflict management skills just the same as academic
subjects. Furthermore, students need to be involved in working out reasons for
conflict and trying to solve them within their group (Benjamin et al., 1997).
27
Students need to be taught two sets of skills for dealing with group
conflicts (Johnson et al., 1993). First, they need to know how to manage conflicts
that occur in their group. Second, they must be taught how to negotiate a
constructive resolution to any group conflict. Johnson et al. (1993) caution not to
intervene more than necessary during group conflict as group members should be
involved in working out solutions to their own conflicts. When intervention is
necessary, the group should be asked to create three possible solutions to the
conflict and then decide as a group which solution to try first.
West (2004) recommended four stages for conflict mediation: Step One
involves exploring the feelings of the team members involved in the conflict; Step
Two involves exploring the facts from the perception of each member; during
Step Three, group members agree to goals for avoiding a reoccurrence of the
conflict; and finally, in Step Four, the group members agree on an action plan. In
order to discourage destructive conflict, group member roles and responsibilities
should also be made clear to all group members (West, 2004).
Observation and feedback: Observations should be made of interactions
among group members engaged in group problem solving and group members
should receive feedback from these observations about their group performance
(Johnson et al., 1993). The feedback should include how the group is performing
and how the group is completing the task. Observations can be made about the
28
task progress as well as the use of group skills and students can also be trained to
be observers (Johnson et al., 1993).
Observations based on group maintenance skills need to be shared with
students in order for them to monitor and evaluate their own group performance
(Dishon & O’Leary, 1984). To facilitate this process, Dishon and O’Leary (1984)
compiled a checklist of indicators to observe group behaviour (see Appendix A, p.
261). Feedback is also important to discover students’ ideas of the group problem-
solving process (Dishon & O’Leary, 1984; Goos et al., 2002). In order to reflect
on their problem-solving processes and increase their use of cooperative skills,
students need to receive feedback on their group’s problem-solving performance
(Chizhik, 1998; Mevarech, Siber, & Fine, 1991; Xiaondong, 2001).
Group roles: One problem that affects teamwork is the lack of clarity
about group roles (West, 2004). Therefore, assigning roles during group problem
solving is seen as an effective method for students to learn the specific social
skills needed for group learning (Cohen, 1994). Cohen suggested that in order to
make the roles public and give students authority to act in the group role, teachers
should set up a chart for role assignments. The chart also helps to clarify the role
to other group members.
Many different classifications of group roles have been produced. Group
roles in most of these classifications can be classified into two distinct categories:
29
task roles and team roles (Bales, 1970; Bales & Cohen, 1979; Hoover, 2002).
Task roles relate to the focus of the group toward a solution, while team roles
focus on building and maintaining the group (Bales & Cohen; Gottlieb, 2003).
Some of the most cited group role classifications, found in the literature, are
presented in Table 2.1.
Table 2.1
Group Roles
Task roles
Checker (Cohen, 1994; Dishon & O'Leary, 1984;
Hayes, 2002) Coordinator (Gottlieb, 2003; Tyson, 1989) Elaborator (Gottlieb, 2003) Follower (Gottlieb, 2003) Information and opinion giver (Bales & Cohen,
1979; Gottlieb, 2003; Tyson, 1989) Information and opinion seeker (Gottlieb, 2003;
Tyson, 1989) Keyboarder (Cohen, 1994) Recorder (Dishon & O'Leary, 1984; Gottlieb,
2003; Johnson et al., 1993; Tyson, 1989) Summariser (Johnson et al., 1993; Dishon &
O'Leary, 1984; Tyson, 1989)
Team roles Conflict manager (Bales & Cohen, 1979; Gottlieb, 2003; Tyson, 1989)
Encourager (Bales & Cohen. 1979; Cohen, 1994; Dishon & O'Leary, 1984; Gottlieb, 2003; Hayes, 2002; Johnson et al., 1993; Tyson, 1989).
Moderator (Johnson et al., 1993) Spokesperson (Tyson, 1989) Supporter (Tyson, 1989)
30
Computers: Computers have the potential to support group problem
solving and learning (Light, Littleton, Messer, & Joiner, 1994). However, in order
for this potential to be realised, there is a need for students to apply group skills
when engaged in problem solving and learning around a computer (Cohen, 1994;
Dishon & O’Leary, 1984). Assigning group roles is an effective way to develop
group skills for groups working around a computer (Cohen, 1994). The group
roles need to be rotated so all group members participate and have equal access to
the computer (Cohen, 1994).
CSCL is increasingly being used to support group decision making by
scaffolding online groups’ communication. However, Kreijns and Kirschner
(2001) pointed out that CSCL environments do not go far enough with regard to
supporting group problem solving and learning. CSCL environments need to
encourage group maintenance as well as task orientated discussion. According to
Kreijns et al. (2002), within the field of CSCL research, most of the focus has
been on the development of cognitive-technological scaffolds.
The cognitive scaffolds provided within Knowledge Forum® are typical
examples of technology scaffolds. However, as Bielaczyck and Collins (1999)
pointed out, cognitive/technology scaffolds by themselves are not sufficient to
ensure that the engagement and interaction necessary for knowledge building
discourse to occur within CSCL environments; they, like Kreijns et al. (2002),
contend that social interactions also need to be planned for within CSCL
environments. In both computer and non-computer contexts, the task also
31
influences how well the group interacts and works together (Crook, 1999;
Jonassen & Kwon, 2001; Light & Littleton, 1999; Underwood & Underwood,
1999).
Problem-solving task: The problem-solving task administered to learners
can influence how well groups will work together (Jonassen & Kwon, 2001; Light
& Littleton, 1999; Underwood & Underwood, 1999). Problem tasks that are
closed, or only require one answer tend to not facilitate cooperative discourse and
interactions with other students in a group (Cohen, 1994; Lesh & Doerr, 2003).
Closed problems require low levels of cooperation as students do not need to
discuss how to proceed; nor do they need to restructure their own ideas taking into
account other members’ perspectives (Cohen, 1994).
However, according to Cohen (1994), groups are more likely to be
productive if tasks are complex, ill-defined, ill-structured and open-ended. Such
problems have vague or unclear goals, multiple solutions, multiple solution paths,
multiple criteria, and provide opportunities for students to engage in collective
meaning making (Cathcart, Samovar, & Henman, 1996; Jonassen & Carr, 2000;
Jonassen & Kwon, 2001). When problem tasks are complex and ill-defined,
students need to be involved in high levels of cooperation, as they work together
(Lesh & Kelly, 2002; Puntambekar, 1999). Students need to work as a group in
order to solve the problem and need to discuss how to proceed and reconstruct
ideas taking into account other members’ perspectives (Puntambekar, 1999).
32
Research regarding model-eliciting activities confirms that the use of
realistic ill-defined problems allows students to engage in collective meaning
making (English, Fox, & Watters, 2005; Lesh & Lamon, 1992; Zawojewski et al.,
2003). Model-eliciting activities are mathematical-based tasks that present
realistic problem scenarios and often require students to work together as a group
to develop a shared model that can be used to solve the problem situation (Lesh &
Doerr, 2003; Lesh & Harel, 2003). The activities are designed to encourage
students to build mathematical models in order to solve complex problems.
Model-eliciting activities are based on six specific principles (Lesh, Hoover,
Hole, Kelly, & Post, 2000):
1. Model construction principle: problems must be designed to allow for the
creation of a model dealing with elements, relationships and operations
between these elements and patterns and rules governing these
relationships.
2. The reality principle: problems must be meaningful and relevant to the
students.
3. Self-assessment principle: students must be able to self-assess or measure
the usefulness of their solutions.
4. Construct documentation principle: students must be able to reveal and
document their thinking processes within their solution.
33
5. Construct shareability and reusability principle: solutions created by
students should be generalisable or easily adapted to other situations.
6. Effective prototype principle: others should easily be able to interpret
solutions.
2.1.2 Cognitive factors
Cognitive factors influence how group members develop a shared
knowledge and understanding about the problem (Lesh et al., 2000). A degree of
shared knowledge about the team is necessary for teams to work effectively
(Cannon-Bowers & Salas, 1998; Lim & Klein, 2006). This knowledge contributes
to the group’s ability to accomplish their task work (Canon-Bowers & Salas,
2001) and ensures that problem solving becomes a co-construction of ideas by
group members (Chizhik, 1998; Light & Littleton, 1999).
The development of shared knowledge about a problem is predicated on
the construction of a shared understanding of the problem (Cohen & Gibson,
2003). As Barron (2000) pointed out, group members must establish a shared
understanding to make sense of the problem as a group. The following sections
highlight that groups are more likely to construct shared internal knowledge and
understandings if they develop shared external representations about the
problem(s) being investigated.
34
Shared external representation: In order to develop a shared
understanding of the problem, group members must first negotiate a shared
external representation or model of the problem (Fiore & Schooler, 2004). Groups
of students need to develop an external representation of the problem in order to
articulate their thinking, making their group understanding explicit and visible in
order to collaborate with group members (Lewis, 1997; Mohammed & Dumville,
2001). By sharing their ideas, students are able to gain a joint understanding of
not only of how their group works but also of the problem-solving task they are
collaboratively completing (Antaki & Lewis, 1986; Cathcart et al., 1996; King,
1989). External representations facilitate the process of articulating students’
thinking and allow group members to formulate accurate shared internal
representations of both their team-work and task-work (Cannon-Bowers & Salas,
2001; Klimoski & Mohammed, 1994; Webber, Chen, Payne, Marsh, & Zaccaro,
2000).
Shared internal representations: The development of shared knowledge
by a group is facilitated by groups developing shared internal representations
regarding both task- and team-related information (Rentsch & Klimoski, 2001).
The two dimensions of group functioning, that is, the task a group is required to
complete and the group as a social unit, need to be focused on in order for groups
to achieve a shared understanding of the task and how to work successfully as a
team (West, 2004). Group efforts need to be made to help all group members
35
understand the task and the team requirements (Johnson et al., 1993). The
development of shared knowledge by a group can be facilitated by the
development of schema similarity among group members (Rentsch & Klimoski,
2001; Woehr & Rentsch, 2003).
In order to evaluate schema similarity, Rentsch and Klimoski (2001)
created the construct of Team Member Schema Similarity (TMSS). TMSS is the
degree of similar or overlapping team knowledge that members hold of teamwork
and task work (Langan-Fox, Anglim, & Wilson, 2004). According to Woehr and
Rentsch (2003), teamwork schema similarity leads to improved team processes,
while task work schema similarity leads to improved task performance. Each
group member’s understanding, of what they are working on, needs to merge into
a similar cognitive or mental model during collaboration (Cannon-Bowers &
Salas, 2001; Klimoski & Mohammed, 1994).
In a construct similar to Rentsch and Klimoski’s (2001) TMSS, Cannon-
Bowers and Salas (1998) focused on groups constructing shared mental models. A
shared mental model is a mental representation of shared knowledge (Halford,
1993; Mathieu, Heffner, Goodwin, Cannon-Bowers, & Salas, 2005). This shared
knowledge combines knowledge about the task and the team, including
declarative knowledge (knowledge about) and procedural knowledge (knowledge
how) (Cooke, Salas, Kiekel, & Bell, 2004; Mohammed & Dumville, 2001).
In order to build an effective shared group mental model during group
problem solving, group members must also hold a similar shared and accurate
36
knowledge about the components of successful groups and the problem-solving
task (Cooke et al., 2004; Fiore & Schooler, 2004; Mathieu, Goodwin, Heffner,
Salas, & Cannon-Bowers, 2000; Rentsch & Klimoski, 2001; Smith-Jentsch,
Campbell, & Milanovich, 2001). Groups are more likely to work effectively when
members develop a shared model together (Woehr & Rentsch, 2003).
The cognitive factors discussed in this section of the literature review and
represented in Figure 2.2 highlight that groups are more likely to develop a shared
knowledge and understanding if they develop a shared internal representation as
well as a shared external representation.
Cognitivefactors
Shared knowledge and understanding
Shared external representation
Shared internalrepresentation
Figure 2.2. Model representing cognitive factors.
2.1.2.1 Strategies to address cognitive factors
In order to develop a shared knowledge and understanding, group
members need to articulate their problem-solving plans and group strategies
(Fiore & Schooler, 2004). Group members develop shared understandings of the
group process and the problem-solving task by asking other group members to
37
justify and clarify ideas they do not understand (Fiore & Schooler, 2004; Goos et
al., 2002; Klimoski, & Mohammed, 1994). Groups also need to reflect on the
solution process, as well as the group collaboration process (Klimoski &
Mohammed, 1994; Puntambekar, 1999).
In order to improve the effectiveness of group problem solving and
learning, group members need to reflect on how they are accomplishing the
shared task and how their group is working as a team. Reflecting on group
problem solving helps students understand how the team goals of the group are
related to the task goals (Beamish & Au, 1995). Scaffolds need to be provided to
help students reflect on their problem solving (Puntambekar, 1999). The
following sections discuss specific strategies that help students address the
cognitive factors relevant to group problem solving and learning, including the
use of scaffolds, strategic questions, and CSCL environments.
Scaffolds: Scaffolds are an important aspect of students’ learning during
group problem solving and learning (Hamilton, 1986; Hartman, 2001;
Puntambekar, 1999). Scaffolds support, guide, and cue thinking (Vygotsky, 1978)
and are needed to help students develop a shared model as well as reflect on their
group problem-solving process (Klimoski & Mohammed, 1994).
Scaffolding can be initially provided to groups in order for them to
understand what the problem is asking, plan how the group will go about solving
38
it, monitor the group’s progress towards a solution and finally evaluate the
effectiveness of their group problem-solving process. Beamish and Au (1995)
suggested that this process can be facilitated by encouraging students to question
what they know about a specific problem, what they want to know, and what they
must learn to solve the problem.
Strategic questions: The use of strategic questions such as those utilised
by Gama (2000), Johnson et al. (1993) and King (1991) scaffold the problem
solving as well as the group process (see Table 2.2). The series of structured
questions assists students with their problem solving. According to King (1991),
students also need to be trained to ask scaffolding questions of each other during
group problem solving. King (1991) categorised these scaffolding questions into
planning, monitoring, and evaluating questions. Johnson et al. (1993) also
suggested that groups need checklists and questions to structure the group
learning process. Strategic questions and scaffolds can also be incorporated with
CSCL to promote reflection and positive interaction (Puntambekar, 1999).
39
Table 2.2
Strategic Questions
Types of questions Examples
Planning:
Gama (2000)
What is our plan?
What is the problem?
What do we know about the problem?
King (1991) What is the nature of the task?
What is the goal?
What information is needed?
What strategies can be used?
How much time and what resources are needed?
Monitoring:
King (1991)
Do you understand what to do?
Does the task make sense?
Are the goals being reached?
Do changes need to made?
Johnson et al. (1993) What are three things your group is doing well and
one thing that needs to improve?
Evaluating:
King (1991)
Have the goals been reached?
What worked?
What didn’t work?
What would be done differently next time?
Johnson et al. (1993) How frequently did each member:
Explain how to solve the problem?
Correct or clarify other member’s explanations?
40
CSCL: Scaffolding group problem solving in the Knowledge Forum®
CSCL environment requires supporting students with their problem solving and
group work around the computer, as well as supporting problem solving between
groups working online. The Knowledge Forum® software can help support group
online problem solving as students collaboratively construct knowledge using the
shared interface (Hakkarainen, Lipponen, Jarvela, & Niemivirta, 1999; O’Malley,
1995; Wang et al., 2001).
Knowledge Forum© supports a student-centred open-ended learning
environment where students are actively engaged in knowledge building
(Scardamalia & Bereiter, 1994). The database software supports groups of
students in constructing “notes” about a problem through structures such as model
building and model critiquing scaffolds. Other groups can view the database,
adding text, graphics, questions, and comments on each other’s work.
However, Cannon-Bowers and Salas (2001) warned that, if not enough
support is given to online teams, they will fail. They indicated that in order to
scaffold effective online problem-solving groups, there is a need to identify
successful group skills that combine task-related knowledge and skills with team-
related knowledge and skills.
41
2.1.3 Summary
Participating in successful group problem solving and learning, within the
CSCL Knowledge Forum® environment, entails students co-constructing a
shared understanding by combining task- and team-related knowledge and skills.
This shared understanding is also essential for groups working together on non-
computer tasks. The shared understanding is facilitated by groups developing a
shared mental model or external representation of their group problem-solving
process (Fiore & Schooler, 2004; Klimoski & Mohammed, 1994; Mohammed &
Dumville, 2001).
Students cannot form a shared understanding or interact successfully as a
group, if they have had no preparation for group work (Cohen, 1994; Johnson et
al., 1993; Ogden, 2000). A number of factors influence how groups work
effectively and form a shared understanding, including organisational factors such
as how the group develops and resolves conflicts, and cognitive factors such as
how the group forms a shared understanding (see Figure 2.3).
42
Organisational factors
Forming
Storming
Norming
Performing
Adjourning
Interaction face-to-face and on-line
Constructive conflict
Social skills
Individual accountability
Positive interdependence
Group processing
Cognitivefactors
Shared knowledge and understanding
Shared external representation
Shared internalrepresentation
Figure 2.3. Factors influencing efficiency of group problem solving and learning.
43
However, incorporating organisational and cognitive strategies to help
scaffold group problem solving is insufficient. Group problem solving and
learning activities also need students to metacognitively reflect on the
organisational and cognitive factors influencing their group work (see Figure 2.4).
When students reflect on their group problem solving, both their problem solving
and their group work is said to improve (Cohen, 1994; Johnson et al., 1993).
Cognitivefactors
Organisationalfactors
Metacognitivefactors
Group problem solving and learning
Figure 2.4. Group problem solving and learning factors.
2.2 Group metacognitive factors
This section first highlights the varied definitions of metacognition, as
well as setting the stage for the establishment of group metacognition. It then sets
out to combine theories on group work and metacognition in order to focus on
how to scaffold group metacognition within groups working around a computer
44
and between groups working together on the online Knowledge Forum® CSCL
environment.
There are many varied definitions of metacognition (Antaki & Lewis,
1986). Flavell, Friedrichs, and Hoyt (1970) first introduced the concept of
metacognition as an individual’s awareness, choice, and control of their cognitive
processes. Metacognition is defined as “one’s knowledge concerning one’s own
cognitive processes and products or anything related to them” (Flavell, 1976, p.
232). Schoenfeld (1987) focused on metacognition as students’ beliefs based on
past experiences, knowledge of own thinking processes and self-awareness of the
process of problem solving. Metacognition is a conscious effort to identify
learning strategies and being able to apply strategies across various knowledge
domains (Beamish & Au, 1995).
Metacognitive research has focused on three main components of
metacognition:
1. Metacognitive beliefs and attitudes (Brown & Palincsar, 1989;
Schoenfeld, 1992).
2. Metacognitive control (Beamish & Au, 1995; Blakey & Spence, 1990)
3. Metacognitive knowledge (Flavell, 1976; Schoenfeld, 1987)
Metacognitive belief is based on previous experience, skills, and
knowledge and affects motivation to direct metacognitive knowledge and use
metacognitive strategies (Brown & Palincsar, 1989; Desoete, Roeyers, & Buysse,
45
2001; Desoete, Roeyers, & De Clercq, 2003). Metacognitive control is the use of
strategies including planning, monitoring, and evaluating and the strategies are
essential for the self-regulation of thought processes (Beamish & Au, 1995;
Garofalo, & Lester, 1985). Metacognitive knowledge consists of knowledge about
thought processes (Flavell, 1976; Schoenfeld, 1987).
Metacognitive knowledge can be manifested either as declarative or
procedural knowledge (Azevedo & Hadwin, 2005; Desoete et al., 2001).
Declarative metacognitive knowledge focuses on what students know about
knowledge and learning where procedural knowledge is what students know
about the process of using their declarative knowledge (Efklides, 2006;
Schoenfeld, 1992). Procedural metacognitive knowledge is necessary in order for
students to apply declarative knowledge and is important for successful problem
solving (Berardi-Coletta et al., 1995).
Metacognitive knowledge
Metacognitive belief
ProceduralMetacognitive
controlDeclarative
Metacognitive strategies
Planning
Monitoring
Evaluating
Metacognitivefactors
Figure 2.5. Model representing metacognitive factors.
46
Figure 2.5 highlights the main metacognitive factors identified in the
research literature. As the figure shows, metacognitive knowledge is distinguished
from metacognitive control. Palincsar and Brown (1984) believed it was
important to distinguish between the two as metacognitive knowledge deals with
students’ knowledge of thinking whereas metacognitive control, also called
executive control, is concerned with learners actively planning, monitoring,
revising, and evaluating their own learning.
Most research on metacognition has considered the role of metacognition
as an individual learning process (Hoyles & Healy, 1994; Hurme & Järvelä,
2001). By focusing solely on the individual student, researchers have failed to
address the dynamics required for progressive knowledge building by
collaborative learning groups (Scardamalia & Bereiter, 1994). It is in this context
that Hurme and Järvelä (2001) called for more research on the metacognition
process as a socially shared practice.
The shared understanding and shared mental representations group
members have about the way their group performs the task and works as a team
are examples of group metacognition (Hinsz, 2004). According to Hinsz (1995,
2004), the understanding group members share about the way groups operate and
function represents how group members think about the way groups process
information and perform cognitive tasks.
Group metacognition is facilitated by interaction between group members
(McNeese, 2000). The use of metacognition facilitates successful group problem
47
solving, as learners reflect on their learning processes more readily in groups
(Antaki & Lewis, 1986; Hamilton, 1986; Murphey & Jacobs, 2000). Group
members can discuss and compare their thoughts and behaviour with other group
members. Metacognition of groups also requires group members to understand
how effective groups process information and perform tasks (Hinsz, 2004).
Planning to achieve the group task goal, as well as monitoring the group’s
progress required to achieve the group goal, are group metacognitive processes.
Effective learners need to know how to plan, monitor, and regulate their
learning processes, including those involved in cooperative learning contexts
(Antaki & Lewis, 1986). Metacognitive individuals plan, monitor, and evaluate
their learning processes (Schraw, 2001). These abilities are also essential for
groups building a shared knowledge (Bereiter & Scardamalia, 1989). Groups of
students need to develop co-cognition in order to collaboratively develop concepts
and monitor their own group performance (Costa & O’Leary, 1992). Co-cognition
requires the cooperative development of strategies used to plan, monitor, and
evaluate group behaviour.
2.2.1 Group metacognitive strategies
Studies have shown that students do not engage in metacognitive thinking
unless they are encouraged to do so (Gillies, 2000). The three main metacognitive
strategies of planning, monitoring, and evaluating are identified in the
48
metacognitive literature for individual learners (Flavell, 1976; Gourgey, 2001).
These strategies can also be used in a group context where students can note any
difficulty with working in their groups and solve the problem as a group (Johnson
et al., 1993).
The use of strategy training in metacognitive research has been frequently
used and includes students planning how to approach a given task, monitoring
their progress in the task and finally, evaluating their learning process (Flavell,
1976). However, students also need instruction on strategies including how, when,
and why to use each strategy (King, 1991; Palincsar, 1986). Metacognitive
strategies of planning, monitoring, and evaluating are needed in problem-solving
groups in order to attain specific learning goals (Blakey & Spence, 1990; Flavell,
1976; Lesh et al., 2000; McNesse, 2000; Tombari & Borich, 1999).
Group metacognition facilitates the use of appropriate metacognitive
strategies during group problem solving and learning. The strategies assist groups
to progress towards a solution and reflect on their group learning process. For
groups to be successful depends on the members knowing how and when to use
specific problem-solving and group strategies (Johnson et al., 1993). According to
Desoete et al. (2001), strategies can be selected to solve the group problem
situation in order to improve the group learning process. Groups can use
metacognitive strategies to determine whether their group problem-solving is
successful and what remedial action needs to be taken to make the group
problem-solving process more effective (McNeese, 2000). Students can develop a
49
shared understanding of specific group problem-solving behaviours and strategies
helpful for their group (Cohen, 1994). Using the student-generated criteria group
members can plan, monitor, and evaluate their own group performance (Davidson
& Worsham, 1992; Gillies, 2000).
As noted previously, research studies have shown that students do not
engage in self-regulated or metacognitive thinking unless they are encouraged to
do so (Flavell, 1976; Gillies, 2000; Tombari & Borich, 1999; Xiaodong, 2001).
While there are several approaches to metacognitive instruction, the most
effective involves providing learners with: knowledge of problem-solving and
group learning strategies (Wilson & Johnson, 2000); practice in using the
strategies (Flavell, 1976); and opportunities to plan, monitor, and evaluate the
strategies used (Xiaodong, 2001).
2.2.2 Group metacognitive scaffolds
As students do not engage in metacognitive thinking unless it is structured
in learning activities, it is important to include metacognitive scaffolds for the
group learning process (Gillies, 2000). Metacognitive scaffolds can be provided
so students are able to regulate their own learning. The metacognitive scaffolds
encourage students to gradually take responsibility for group problem solving by
developing a shared understanding regarding effective group work and problem
solving (Hinsz, 2004). Group metacognitive scaffolds can be gradually withdrawn
50
as students generate their own strategies and develop a shared knowledge
(Chizhik, 1998).
One framework for scaffolding problem solving is the metacognitive
questionnaires developed by Fortunato, Hecht, Tittle, and Alvarez, (1991) (see
Appendix B, p. 262) and King (1991). The questionnaire developed used
metacognitive strategies to scaffold questions based around the problem-solving
process. The three main metacognitive scaffolds used in King’s study were
planning, monitoring, and evaluating. Puntambekar (1999) also devised a
cognitive/metacognitive framework for group problem solving, involving four
categories: orientation, organisation, execution, and verification. Orientation is
concerned with assessing and understanding the requirements of the problem;
organisation involves monitoring behaviours, planning actions and choosing
strategies; execution involves monitoring progress towards a solution; verification
consists of evaluating decisions made.
The group learning context requires that groups have knowledge of
specific group problem-solving strategies that emphasise both the task and the
team work (McNeese, 2000). Figure 2.6 is compiled from a review of the
literature concerning group problem solving, learning, and metacognition, and
highlights that group metacognition needs to be scaffolded in the following ways:
explicit instruction of problem-solving and group strategies (Wilson & Johnson,
2000; Xiaondong, 2001); provision of a supportive environment, where students
can practise their group problem-solving strategies (Gourgey, 2001); mediation of
51
metacognitive strategies of planning, monitoring, and evaluating by using diaries
and checklists (Blakey & Spence, 1990; Wilson & Johnson, 2000).
Wilson and Johnson (2000) stated that students need to be provided with
knowledge of group problem-solving strategies, practice in using the strategies
and opportunity to evaluate the outcomes of the strategies (Flavell, 1976;
Xiaodong, 2001). The importance of a supportive environment in developing
students’ metacognition was emphasised by Brown and Palincsar (1989).
Fostering a learning environment that encourages metacognition requires
developing students’ awareness of their own thinking (Blakey & Spence, 1990).
Blakey and Spence (1990) stated that class discussion should focus on the
learning and thinking processes used, in order to develop students’ awareness of
learning strategies.
It is important to encourage groups to reflect on their relationships and
achievement. This requires a continuous analysis of how group effectiveness can
be enhanced (Beatty & Barker, 2004). Groups need to spend time discussing how
well they work together and planning how to improve future group work
(Murphey & Jacobs, 2000). West (2004) stated that ‘task reflexivity’ and ‘social
reflexivity’ are when teams reflect on the social climate of the group and how
they achieved their group goal. Students need to be encouraged to communicate
with each other, thinking aloud while working together and reflecting on their
learning processes, in order to develop a shared understanding (Murphey &
Jacobs, 2000).
52
Instruction on problem solving skills
and group skills
Provision of a supportive
environment to practise skills
Metacognition scaffolded by diaries
and checklists
Scaffolds
Metacognitive factors
Cognitivefactors
Organisationalfactors
Figure 2.6. Scaffolding group metacognition.
53
One way to encourage self-reflection and the use of metacognitive
strategies is through the use of scaffolded questions in a journal or learning diary
(Blakey & Spence, 1990; Walker, 1985). Students, who write about and monitor
their learning process through the use of a diary, or journal, have been shown to
be more efficient learners (Gourgey, 2001). Wilson and Johnson (2000) used four
scaffolds to develop primary students’ metacognitive thinking: written reflections
in a journal; self assessment orally with peers and team leaders as well as in the
students’ journals; cooperative group work in order for students to reflect on their
small group practices; and concept mapping both as a reflective and a self-
assessment activity.
Diaries and journals are used as a means to develop metacognition as
students can write and reflect upon their thinking while making note of
inconsistencies and progressively commenting on any difficulties (Blakey &
Spence, 1990). Reflective writing is related to the development of metacognitive
skills and writing in mathematics helps students reflect on their work and helps to
clarify and deepen understanding (Pugalee, 2001). Writing helps to develop the
vocabulary students need for thinking and talking about their learning (Blakey &
Spence, 1990).
Including a checklist in the diary, in which students can monitor their
learning, assists students to be reflective learners and scaffolds their
metacognitive processes (Blakey & Spence, 1990; Mueller & Fleming, 1994;
Wilson & Johnson, 2000). An effective way to develop metacognition is for
54
students to answer a series of metacognitive questions that focuses on the
planning of the problem task, monitoring progress towards completion, and
evaluating the learning process (Kramarski & Mevarech, 2003). Schraw (2001)
proposed a checklist for improving students’ thinking about their learning (see
Appendix C, p. 263). The checklist includes questions students could ask
themselves during the planning, monitoring, and evaluating stages of their
problem solving.
2.2.3 Summary
The review of the literature indicates that metacognitive strategies are
important for developing group metacognition; applying metacognitive strategies
for group problem solving allows students to focus on the organisational and
cognitive factors that influence how groups perform their problem-solving task
and work together as a team. Also, the literature clearly points out that students do
not engage in metacognitive strategies unless they are structured within the
learning activity (Gillies, 2000). Scaffolds such as checklists, diaries, and a
supportive environment need to be provided in order to develop group
metacognitive strategies. Groups can plan, monitor, and evaluate group strategies
specific to their team and the group problem-solving task. They can also apply
these strategies to develop a shared group understanding.
55
2.3 Conclusion
There is a definite relationship between positive group work outcomes and
group metacognition. However, the majority of research in metacognition has
tended to look at individual student’s learning process (Gourgey, 2001; Hartman,
2001). A number of factors influence how groups work effectively, including
organisational factors such as how the group develops, works together, and
resolves conflicts, and cognitive factors such as how the group forms a shared
understanding. Group metacognition depends on the degree to which the
cognitive representations that group members have for the task and learning
situation are shared (Hinsz, 2004).
Results from research literature have resulted in an initial conceptual
framework (see Figure 2.7) to inform the research study. The framework
highlights the fact that effective group problem solving requires groups to think
about organisational, cognitive, and metacognitive factors. These factors
influence how groups work together and develop a shared understanding. This
shared understanding is facilitated by groups developing a shared internal
understanding and a shared external representation of their group problem-solving
process (Fiore & Schooler, 2004; Klimoski & Mohammed, 1994; Mohammed &
Dumville, 2001).
56
Organisational factors
Forming
Storming
Norming
Performing
Adjourning
Interaction face-to-face and on-line
Constructive conflict
Social skills
Individual accountability
Positive interdependence
Group processing
Cognitivefactors
Metacognitivefactors
Metacognitive Knowledge
Metacognitive belief
Metacognitive control
Procedural
Declarative
Metacognitive strategies
Planning Monitoring Evaluating
Shared knowledge and understanding
Shared external representation
Effective group problem solving and
learning
Shared internalrepresentation
Figure 2.7. Conceptual framework.
57
CHAPTER 3: RESEARCH DESIGN AND METHOD
The aim of this research study was to develop a conceptual model that
provides guidelines for scaffolding within- and between-group metacognition in
Computer Supported Collaborative Learning (CSCL) environments. This chapter
describes the research design used in this study, the methods of data collection
and analysis, as well as how the study proceeded to achieve the research aim.
3.1 Research design
In order to meet the aim of this study, a design research methodology was
utilised. Design research methodology is increasingly being utilised and is
regarded as having a key role in advancing both practical and theoretical
knowledge in a variety of educational contexts (Bereiter, 2002; Edelson, 2002).
Design research, also called development research or design experiment,
is a research methodology used in a range of research contexts concerned with
refining theory and developing instructional materials (Barab, 2006; Collins,
Joseph, & Bielaczyc, 2004; O’Donnell, 2004). Design research looks at the key
elements of the research setting and the intervention and how they work together
toward an educational goal (Collins et al., 2004). The methodology allows for the
collecting and analysing of large amounts of data and analysing in terms of key
elements in order to understand the context in detail. Woodruff and Nirula (2005)
58
stated that this allows the whole learning context to be taken into account when it
is difficult to study one aspect independently.
Design research methodology includes cyclical phases of preliminary
design, teaching the activity, also called the teaching experiment, and data
analysis (Shavelson, Phillips, Towne, & Feuer, 2003). Teaching experiments are
used in order to develop activities and instructional tools or for studying the
influence of instruction upon students (Romberg, 1992). The cyclical nature of
the design research methodology ensures that the teaching experiment is revised
for each successive research cycle (Collins et al., 2004; Woodruff & Nirula,
2005).
A design research methodology thus was adopted for this study because,
unlike other methodologies, it allows for multiple cycles of design, experiment,
and analysis in order to not only develop instructional materials but also to refine
theory (Bereiter, 2002; Collins et al., 2004; Shavelson et al., 2003; Woodruff &
Nirula, 2005). The multiple cycles of design, experiment, and analysis also
enabled the researcher to progressively test and refine the educational designs
based on theoretical principles utilised during the course of the study (Collins et
al., 2004).
However, design research is not a fully defined methodology and other
methods may also be employed to understand the research context (Bereiter,
2002; Confrey, 2006). Therefore, a descriptive case study method was also used
for data collection to incorporate multiple sources of data and in order to bring out
59
the viewpoint of the group members involved in the study (Stake, 1995; Tellis,
1997; Yin, 1993). A descriptive case study research method facilitates the
development of 'thick descriptions' (Huberman & Miles, 2002; Stake, 1995).
3.2 Data Collection and Analysis
Data collection was conducted in an ongoing hermeneutic cycle (Guba &
Lincoln, 1989). Collected data were thus were analysed as they were collected in
order to inform further collection (Huberman & Miles, 2002). Yin (1994) also
suggested three principles of data collection for case studies: first, use multiple
sources for the triangulation of data; second, create a case study database; and
finally, maintain a chain of evidence. Stake (1995) suggested using multiple
sources of data to bring out the details of the study. Following the principles of
data collection proposed by Yin (2003) and Stake (1995), multiple data were
collected from transcripts of classroom interaction, participant observation,
interviews, and classroom artefacts such as the computer printouts, diaries, and
checklists (see Table 3.1).
60
Table 3.1
Data Collection Methods
Source of data Nature of data collected Time/frequency of data
collection
Observations Participant observation
Videotapes
Audio (MP3) transcriptions
Throughout study
Throughout study
Throughout study
Group interviews Focus group interviews After each cycle
Classroom
artefacts
Diaries
Checklists
Questionnaires
Knowledge Forum notes
Mathematical ranking
models
Throughout study
Throughout study
Prior to and after each cycle
Throughout study
After each cycle
3.2.1 Observations
Observations involved the collection of a variety of data including the use
of a video camera to record groups as they worked together, the use of MP3
digital recorders to record what group members were saying to each other, as well
as participant observations of the learning situation.
Johnson et al. (1993) suggest observing the interactions among group
members in order to assess students’ use of group skills and behaviours.
61
Observations can lead researchers toward a greater understanding of the case
(Stake, 1995). Observation is the recording and describing of behaviour as it
occurs (Johnson & Johnson, 2004).
A video camera and MP3 digital recorders were used to supplement the
direct observation by the researcher. Transcripts of the recordings provided a
record of group interaction and tally sheets were used to mark when students and
groups engaged in one of the targeted actions or behaviours.
3.2.1.1 Participant observation
Participant observation is a valuable research tool as it involves observing
as well as participating in the research context (Bositis, 1988). The participant-
observer role enabled the researcher to gain insights from the students as they
were involved in the study activity. Thus, information derived from the analysis
of the participant observation data enabled the researcher to constantly develop
and refine the classroom instructional activities utilised during the course of the
study.
Bositis (1988) stated that participant observation allows researchers to
both observe certain behaviours as well as being able to provoke certain
behaviours to be observed. During design research the researcher is directly
involved in the situation and can participate as well as observe (Bereiter, 2002).
The researcher was a participant observer with all classes involved in this
research, introducing the activity to the students, and interacting with the students
62
as they completed the activity. During observation a record was kept of certain
events for further analysis and reporting. Video and MP3 digital recordings were
also transcribed for analysis.
3.2.1.2 Video recordings
Groups of students were videotaped to capture the discourse within their
groups. One camera was used and one group from each class was videotaped from
each learning activity phase. A video camera was used with one group from each
class in order to capture the group work around the computer and in order to
follow the group’s development.
Video recordings preserve aspects of interaction including talking,
gestures, and eye gaze. Walker (1985) warned that no recording is a full account
of what actually happens in a context. However, group work is complex and the
use of videotapes is an extension of participant observation and allows for
numerous revisits in order to observe the full extent of the learning context. The
weekly video recordings enabled the researcher to replay sequences of interaction
repeatedly.
3.2.1.3 Audio (MP3) recordings
MP3 recorders were also used in order to capture the discourse of all the
groups. These provided an excellent record of the group’s interactions as students
adapted to them quickly and the majority of students tended to forget they were
63
being recorded. Each group had one MP3 recorder and one student from each
group wore the MP3 recorder around their neck on a lanyard. The wearing of the
MP3 recorders was rotated weekly to make sure that recordings were clearly
captured from each student.
The MP3 audio recordings were transcribed for further analysis. The
transcripts were saved into the Nvivo® software and categories were coded
according to the factors identified in the initial conceptual framework (see Figure
2.7).
3.2.2 Focus group interview
At the end of each research cycle, a focus group interview was used to
record students’ reactions towards the group work, as well as to ascertain
students’ perceptions, feelings, attitudes and ideas regarding the group work and
the group processes. Eder and Fingerson (2003) recommend interviewing children
as a group to make the context more natural and less intimidating than individual
interviews.
Interviews are considered interactive encounters as the social interaction
can shape the nature of the knowledge gained (Fontana & Frey, 2000). However,
data from a focus group is often richer than data from individual interviews as
participants can interact amongst themselves leading to an open participant-led
discussion (Maykut & Morehouse, 1994; Vaughn, Schumm, & Sinagub, 1996).
64
During the interview, students were encouraged to discuss their experience
in their own words. They were asked what they thought about the activity and
what they had learnt about working together. Interviews were conducted using a
format designed to elicit responses about thinking about cooperative group work.
Charmaz (2003) listed examples of questions to use during interviews (see
Appendix D, p. 264). Charmaz’s questions were used as starting points for the
group interviews. For example: What advice would you give to someone who has
discovered they will be working in a group?
The interviews were conducted in the week following the last computer
session. Students were invited to attend group meetings where they could discus
the research project. All interviews were recorded and transcribed in order to have
a detailed record for analysis. Pertinent comments were noted for further analysis.
3.2.3 Classroom artefacts
Five types of classroom artefacts were collected and analysed during the
course of the study: diaries, checklists, questionnaires, Knowledge Forum notes,
and mathematical ranking models.
3.2.3.1 Diaries
Students were encouraged to maintain a group diary to document issues
the group encountered in the process of working together (Hare & O’Neill, 2000;
Walker, 1985). Diaries can be used as a means to develop metacognition as
65
students reflect upon their group thinking, make note of their group
inconsistencies, and progressively comment on how the group deals with any
difficulties (Blakey & Spence, 1990).
The students made all of their notes regarding the task and their team work
in their group diaries. The groups of students were also asked to plan, monitor,
and evaluate their team work in their diaries using the checklists provided.
3.2.3.2 Checklists
Group checklists are a good way to monitor group issues and can be used
to provide immediate feedback to groups regarding their use of cooperative skills
(Reid, Forrestal, & Cook, 1989). Checklists were used to monitor the
effectiveness of instruction and groups were asked to complete a group-
processing checklist in their group diary during the computer session.
The checklists included metacognitive questions based on the studies by
King (1991) and Schraw (2001) that focused on planning, monitoring, and
evaluating. King (1991) suggested using strategic questions to guide students’
cognitive and metacognitive activity during problem solving. Schraw (2001) also
used metacognitive questioning to help students to monitor their performance.
Students were asked to complete the planning checklist in the first
computer session prior to commencing the problem-solving task. The planning
checklist asked the groups to describe both the problem and their plan to solve it.
The initial planning checklist included the following questions:
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What do we know about the problem?
What is the goal?
What is our plan to solve the problem and reach the goal?
What group roles will we use?
What group skills will we use?
In the following three computer sessions, the students completed
monitoring checklists in which they were asked questions regarding how their
group was completing the problem-solving task and how their group was
functioning as a team. These questions were based on King’s (1991) study
regarding the effects of training students in strategic questioning on children's
problem-solving performance. The initial monitoring checklist asked groups to
complete the following questions:
Are we following the group plan?
Do we need to make changes?
What group roles will we use?
What group skills will we use?
Johnson and Johnson (1999) suggested that groups also need opportunity
to describe what group actions are helpful and unhelpful and make decisions
about what behaviours to continue or change. In order to focus group members on
the positive aspects of their team as well as what improvements could be made to
the team problem solving, the checklists also asked groups:
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What are two things our group is doing well and one thing that
needs to improve?
The second monitoring checklist asked the students three questions to help
them plan their computer session and to focus members on the positive aspects of
their group. The following questions were asked:
What group roles will we use?
What group skills will we use?
What is our group is doing well?
The third and final monitoring checklist from Cycle 2 also included a
further question in order for students to plan their Knowledge Forum team work
and included:
What group skills will we use on Knowledge Forum?
The final evaluation checklist, based on questions used by King (1991)
and Schraw (2001), was completed at the final computer session and asked groups
to comment on the following:
Have we reached our goal?
What worked?
What didn’t work?
What could we do differently next time?
The groups were also asked to comment on how the diary and Knowledge
Forum could be improved. This question is consistent with Woodruff and Nirula’s
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(2005) view of student participants as co-investigators in order to discover how
technology could be used better within specific activities.
3.2.3.3 Questionnaires
Students were also asked to individually complete questionnaires prior to
and after the learning activity. The initial questionnaire (see Appendix E, p. 265)
contained five questions that elicited students’ initial thoughts on group work. The
first two questions asked were:
What is a group?
What do you like about working in a group?
These two questions are based on questions from Carley’s (1997) study on
information systems. The first question was designed to elicit students’ shared
declarative knowledge, while the second question combined both declarative and
procedural knowledge. The following two questions asked were derived from
questions used in a study by Whicker, Nunnery, and Bol (1997) in which students
were interviewed on their perception of cooperative group work. These questions
focused on the student’s prior experiences with group work and included:
What do you not like about working in a group?
Where did you learn to work with other people?
The final question added was taken from Charmaz’s (2003) guide on questions to
use during interviews (see Appendix F, p266). The final question asked students:
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What advice would you give to someone who has just discovered
that they will be working in a group?
A final questionnaire (see Appendix F, p. 266) was also completed at the
conclusion of each research cycle. The questionnaire incorporated questions asked
in the initial questionnaire in order to ascertain any changes in students’
perceptions about group work. The questionnaire also included three questions
designed to elicit students’ feelings about their group learning:
What do you feel was easier to understand or learn in your group?
What do you feel would have been easier to understand or learn on
your own?
What would you change about the group?
An individual Likert scale questionnaire was used to measure group
cohesiveness (see Appendix G, p. 267). The group cohesiveness questionnaire
focused on students’ perceptions of their group and other group members. Group
cohesiveness is important for group performance as cohesive groups perform
better than less cohesive groups (Brannick & Prince, 1997; McIntyre & Salas,
1995).
Groups were also asked to complete a metacognitive questionnaire at the
final computer session. This questionnaire was based on Fortunato et al. (1991)
metacognitive questionnaire (see Appendix B, p. 262) and focused on planning,
monitoring, and evaluating strategies. Previous studies have demonstrated the
reliability and validity of the metacognitive questionnaire (e.g., Schwartz,
70
Andersen, Hong, Howard, & McGee, 2004; Sperling, Howard, Miller, & Murphy,
2002.). Students were asked to respond to 21 statements that reflect their thinking
while solving a problem. The questionnaires were used in conjunction with
participant observations, group interviews and other classroom artefacts such as
the Knowledge Forum group notes.
3.2.3.4 Knowledge Forum notes
Knowledge Forum® was used in this study in order for groups to engage
with other groups online. Scardamalia and Bereiter (2006) stated that on
Knowledge Forum® the knowledge is publicly produced by students as they
collectively build knowledge using the posted discussion site. Knowledge
Forum® supported the group’s learning by representing the group’s model and
groups could also construct ‘notes’ about their problem. Other groups could view
the database adding text, questions, and comments on each group’s work. The
Knowledge Forum notes were collected from the computer sessions following
students constructing their mathematical ranking models using Excel®.
3.2.3.5 Mathematical ranking models
The mathematical model ranking activity was developed taking into
account previous literature on mathematical modeling activities (Doerr & English,
2001; English et al., 2005; Lesh et al., 2000; Lesh & Lamon, 1992; Nason &
Woodruff, 2003) and the initial conceptual framework (see Figure 2.7). The
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framework informed the group metacognitive scaffolds of planning, monitoring,
and evaluating the group skills and roles that the groups needed to successfully
work together and develop a shared understanding. This shared understanding
was facilitated by the groups developing a shared external representation of the
mathematical problem using Excel®.
Each team was required to complete an Excel® spreadsheet ranking model
prior to posting it onto the Knowledge Forum® database. Jonassen and Carr
(2000) state that spreadsheets are a ‘mindtool’ that assists with knowledge
representation. Spreadsheets are frequently used as a tool for developing
mathematical problem solving (Abramovich, 2003). For example, teams used the
Excel® spreadsheet to rank the major Australian cities according to various
categories in order to ascertain the ‘best’ city in Australia.
3.3 Procedure
In order to achieve the research aim, the study proceeded in two stages:
Stage 1: Cycles of design experiment (Research Objectives 1 and 2)
Stage 2: Design of unified conceptual model (Research Objective 3)
3.3.1 Stage 1: Cycles of design experiment
Stage 1 involved two cycles investigating within- and between-group
metacognition in order to develop a unified conceptual model in Stage 2. Cycle 1
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involved the design of within-group metacognitive scaffolds during mathematical
problem solving for groups working around a computer (Research Objective 1).
Cycle 2 involved the design of within- and between-group metacognitive
scaffolds for groups building collective knowledge within the Knowledge
Forum® learning environment (Research Objectives 1 and 2). Knowledge
Forum® is a computer supported collaborative learning environment that was
used in this study in order for groups to engage with other groups through a
database (Stein, 1998).
Each of the two cycles consisted of three successive phases of planning,
conducting, analysing, and refinement, which enabled the outcomes of Cycle 1 to
be fed into the next cycle (see Figure 3.1).
Figure 3.1. Phases of design cycles.
The first phase of each cycle involved preparing for the research setting by
planning the learning activity. Relevant literature was reviewed and a conceptual
73
framework was developed in order to inform the development of the learning
activity (see Figure 2.7). The second phase involved conducting the teaching
experiment, or learning activity, in the classroom setting. Aspects of a teaching
experiment approach were incorporated in order to study the influence of group
metacognition instruction on the co-operative groups (Cohen, Manion, &
Morrison, 2000). The learning activity was constantly under development during
the design experiment and data were collected throughout the learning activity to
inform future activities. The third and final phase of each cycle involved the
analysis of data from the teaching experiment in order to refine the problem, the
group roles, and group skills.
Cycle 1 was conducted in 2005 in two classrooms in different primary
schools. Cycle 2 was conducted in 2006 in the same schools used in the first
cycle. The school principals and class teachers volunteered their students to be
part of the research study. Ethical clearance was obtained from the educational
authorities involved, and students and their parents from both cycles of the study
signed a consent form in order to be involved in the study. Cycle 1 resulted in a
preliminary theoretical framework informing strategies for scaffolding within-
group metacognition as well as a preliminary instructional activity. Cycle 2 was
informed by the analysis of the previous cycle as well as insights gained from an
updated literature review. The design was constantly modified throughout the
design cycles.
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3.3.1.1 Cycle 1: Within-group metacognition
Cycle 1 involved the design of within-group metacognitive scaffolds
during mathematical problem solving for groups working around a computer
(Research Objective 1).
Participants
The participants selected for Cycle 1 consisted of 47 students, 27 girls and
20 boys, from two classes from different primary schools. One class was a
combined Year 4-7 class while the other class was a Year 4 class. The Year 4
teacher formed seven groups of three students and one group of four students of
mixed ability and mixed gender, while the Year 4-7 students were allowed to
form six friendship groups of three students and one group of four students. The
Year 4 teacher chose to mix students of different gender and ability in order for
students to learn to work with students other than their close group of friends.
Groups were made up of three members to allow certain group processes
to emerge, as a three person group is considered the minimum size for a group
and is a small enough number for groups to work comfortably around a single
computer (Samovar et al., 1996). The group of four students was formed in one
class due to computer availability. In the second class one group of four students
was formed to include one student new to the class.
The classroom teachers assigned the students to the groups from the same
school and the students remained in the same groups throughout the study. Each
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group worked together on their mathematical ranking model which was placed on
the Knowledge Forum® database. All groups, from both schools, could view the
database and comment on any group’s model.
Procedure for Cycle 1
This cycle proceeded in three phases: Phase 1: Planning the teaching
experiment; Phase 2: Conducting the teaching experiment; Phase 3: Analysis of
data from the teaching experiment.
Phase 1: Planning the teaching experiment
The first phase of this cycle involved preparing for the research setting by
planning the learning activity (see Figure 3.1). The learning activity was
developed from the conceptual framework developed from the literature review in
Chapter 2 (see Figure 2.7). The framework identified organisational factors,
cognitive factors, and group metacognition factors. Strategies for addressing these
factors were incorporated into this phase of Cycle 1.
In order to address the organisational factors (see Section 2.1.1), this first
cycle focused mainly on the face-to-face interaction that occurred amongst the
group. Strategies such as group skills, team roles, and checklists to monitor the
use of the skills and to provide scaffolds for feedback, were included as support
for the organisational factors identified in the theoretical framework from Chapter
2.
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The type of problem-solving task used was also identified in Chapter 2 as
being an important strategy to ensure that students used teamwork as well as task
work in order to work together (Dishon & O’Leary, 1984). An open-ended model-
eliciting problem-solving task, ‘Best City’, incorporating core learning outcomes
from the Queensland Mathematics Syllabus: Years 1-10 (Queensland Studies
Authority, 2004) was planned for the group work (see Appendix H, p. 268). The
mathematical problem-solving task, ‘Best City’, involved students working
together around the computer to rank information about the capital cities in
Australia (see Appendix I, p. 274). The design of this mathematical problem-
solving task was informed by Lesh et al. (2000) principles for model-eliciting
activities. The ‘Best City’ problem-solving task met all of Lesh et al.’s six
principles for model-eliciting activities.
Groups were to externally represent their knowledge by producing a
mathematical ranking model on Excel®. The catalyst of this problem-solving task
was a newspaper article published in the Herald Sun (see Appendix J, p. 282), in
October 2005, ranking the livability of cities throughout the world. The groups
involved in this cycle needed to come up with an overall ranking system in order
to find the ‘best city’ in Australia.
Specific skills and group roles, were identified from the literature review,
and were used for the groups working around the computer (see Appendix K, p.
283) (Cohen, 1994; Dishon & O’Leary, 1984). These group skills and roles were
included in a group diary in order for the students to choose group skills
77
appropriate for their group and in order to allocate the group roles to each member
of the group (see Appendix K, p. 283).
In order to address the cognitive factors (see Section 2.1.2) of group
problem solving, the groups needed to form a shared understanding of the task
they were completing and how to work effectively together. Strategic questions
and scaffolds were identified from the literature review and from the conceptual
framework in Chapter 2 (see Figure 2.7). The scaffolds were included to
encourage students to question what they knew about the specific problem, what
they wanted to know, and what they needed to learn to solve the problem. The
strategic questions were included in order to scaffold the group processes as well
as the problem-solving process. The questions were used to develop
questionnaires and checklists to scaffold a shared understanding by each group of
how they were working together as a group to solve the problem (see Appendix L,
p.284). Incorporating the use of Excel® sheets and the Knowledge Forum®
database also enabled students to articulate their problem solving in order to build
a shared understanding about the problem-solving task.
In order to address the metacognitive factors (see Section 2.2) identified in
the literature review, group problem-solving checklists were also used in the
group diary to encourage groups to plan, monitor, and evaluate their problem
solving and their group work. The checklists were included in the group diaries in
order for the groups to plan, monitor, and evaluate their problem solving and how
they worked together (see Appendix L, p. 284).
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Phase 2: Conducting the teaching experiment
This phase of the cycle involved conducting a teaching experiment, or
learning activity, in the classroom setting (see Figure 3.1). This phase ran for six
weeks with one computer lesson per week. The computer sessions were of one
hour duration. Prior to the first computer session, the students were given the
initial individual questionnaire (see Appendix E, p.265) regarding their
perceptions on group work and what problems they had encountered previously
when working in a group. A final individual questionnaire was completed at the
end of the study (see Appendix F, p. 266). A focus group interview was also
conducted, and recorded, at each school where students were asked about the
group task and their use of Excel® and Knowledge Forum® and what they
thought worked well and what did not work well. This is similar to Nirula and
Woodruff’s (2005) design study in which students were viewed as co-
investigators in order to discover how technology and pedagogy could be used in
a specific activity.
The mathematical model building activity was introduced to the groups of
students from the same class, working around the computer (Jonassen & Kwon,
2001; Lesh & Harel, 2003; Light & Littleton, 1999; Underwood & Underwood,
1999). The model building activity required groups to work together to develop a
mathematical ranking model that could be used to solve the problem situation (see
Appendix H, p. 268).
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During the first computer session students were shown the newspaper
article (see Appendix J, p. 282) ranking the cities of the world and asked their
opinion on whether they thought that the Australian cities were ranked correctly.
Students from both classes decided that they would rank the cities differently and
it was decided that an overall ranking would be compiled from an amalgamation
of each group’s mathematical ranking model (see Appendix M, p. 288).
Cannon-Bowers and Salas (2001) and Klimoski and Mohammed (1994)
suggested that external representations facilitate the process of articulating
students’ thinking and allow group members to formulate an accurate shared
understanding of both teamwork and task work. The group skills, roles and
problem-solving strategies, derived from relevant literature were included in the
group diary (see Appendix K, p. 283), as well as the metacognitive checklists of
planning, monitoring, and evaluating.
Students were also asked to complete the initial planning checklist in the
group diary (Appendix L, p. 284). The planning was based on the listed problem-
solving skills and team skills included in the group diary (see Appendix K, p.283).
Each group was asked to answer the following questions on their planning sheet:
What do we know about the problem?
What is the goal?
What is our plan to solve the problem and reach the goal?
What group roles will we use?
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What group skills will we use?
Each group skill was introduced using a T-chart (see Appendix N, p. 290),
with one column titled ‘looks like’ and the other column titled ‘sounds like’,
where students were asked to describe behaviours that exhibited the skill. For
example, students suggested that for the group skill of ‘encouraging other
members to talk’ they could smile at the group member and look at them as they
spoke. They also suggested they could ask students who were usually quiet what
they wanted to do. Groups were asked to nominate one task skill and one
maintenance, or team skill, their group could concentrate on during the following
computer session.
Groups also assigned roles to each group member including: keyboarder,
checker, elaborator, researcher, recorder, encourager, and observer (Dishon &
O'Leary, 1984; Johnson et al., 1993). Assigning roles for groups working on the
computer ensures equal keyboard access for all members, as well as being an
effective method for students to build social skills (Cohen, 1994; Johnson &
Johnson, 1993).
In the second computer session, groups chose the categories on which they
were going to rank the major cities from sheets containing information about the
major cities (see Appendix I, p.274). Groups were also asked to monitor their use
of group skills and what they were doing well and needed to improve (see
Appendix L, p. 284). The groups reallocated group roles so each group member
81
would have a turn at the keyboard and each group was asked to answer the
following questions on their monitoring sheet:
Are we following the group plan?
Do we need to make changes?
What group roles will we use?
What group skills will we use?
What are 2 things our group is doing well and 1 thing that needs to
improve?
Groups were also asked to complete monitoring sheets after the third and
fourth computer sessions where they were asked to nominate the group roles and
skills they were going to use within their groups and what group skills they were
going to use on Knowledge Forum® (see Appendix L, p. 284). Students were also
asked to complete the monitoring checklist in the group diary regarding how their
group was completing the problem-solving task and how their group was
functioning as a team.
A brief introduction to the Knowledge Forum® was provided at the
beginning of the third session in which groups were shown how to post a note and
how to reply to others’ notes. A guide to the Knowledge Forum® database was
also given to the groups (see Appendix O, p. 291). The groups became familiar
with the Knowledge Forum® database as they wrote welcome notes to each other.
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The groups were also required to place the categories they were going to rank
their cities with onto their monitoring sheet and the Knowledge Forum ® database
(see Appendix P, p. 293). The categories chosen by the groups were placed on a
CD (see Appendix Q, p. 294) and information was included from the various
websites so that students could obtain further details about their chosen categories
(see Appendix R, p.295).
The fourth computer session involved groups completing a further
monitoring sheet, as well as replying to the welcome notes posted onto
Knowledge Forum ® during the previous session. Groups also developed their
Excel® rankings, using the categories they chose in the previous session. A 10-
minute lesson was given to students on how to add columns and create formulas
in Excel®. A guide was also given to the groups to help them use the Excel®
spreadsheets (see Appendix S, p. 296).
Only one of the classes had prior experience with Excel®. However, this
experience was limited to having received a brief introduction on spreadsheets
from a parent helper. While the class had experience in reading and filling out
columns in Excel®, they had no experience with adding the columns or using
formulas. The other class had no prior experience with Excel® spreadsheets.
During the fourth computer session, following the development of their
initial Excel® ranking model, each group of students was required to post their
model to Knowledge Forum®. The groups also posted “notes” regarding their
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ranking model in order to explain their ranking and to help develop online
communication. Other groups could view the Knowledge Forum® database and
include their own “notes” adding questions and comments on each other’s
spreadsheet.
In the fifth computer session, the groups revised their ranking systems
based on comments received from other groups and from further categories
chosen. The groups also added comments to their Excel® sheet to explain how
they had ranked the cities according to the categories they had chosen (see
Appendix Q, p.294). During this fifth computer session, groups added all the
ranked categories from the Knowledge Forum® database onto their Excel®
spreadsheet. The groups then sorted the combined rankings to find the best city in
Australia. The final ranking model included the categories from all the groups’
spreadsheets (see Appendix M, p. 288). The final model was added to the Best
City CD and a comment was added by one of the classes involved in the study
(see Appendix T, p. 297).
The sixth and final computer session involved groups completing an
evaluation checklist in their group diary (see Appendix L, p. 284). Groups were
asked to comment on what worked with their group, what didn’t work and what
they might do differently next time they worked together. During the final session
groups also wrote farewell messages to the other groups on the Knowledge
Forum® database. For example, one group wrote:
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Merry x-mas and a happy new year thats (sic) for the last week of the
school (Group M)
Phase 3: Analysis of data from the teaching experiment
This third and final phase of Cycle 1 involved the analysis of data from the
teaching experiment conducted in Phase 2 (see Figure 3.1). Triangulation
occurred in this study with the use of multiple sets of data and the data were
analysed using several different coding methods. Following the principles of data
collection and analysis proposed by Yin (1994), the data collected and method of
data analysis are presented in Table 3.2. Yin’s three principles proposed were:
first, use multiple sources for the triangulation of data; second, create a database;
and third, maintain a chain of evidence. A sample of the data coding was checked
by a senior researcher (R. Nason, personal communications, 2007) until all
categories were agreed upon.
As the study focused on the group metacognition that is shared amongst
team members, the unit of analysis focused on the group. This approach is
consistent with an approach adopted by Stahl (2006) who suggested that learning
can take place at the group level as well as with the individual student. It is for
this reason that Bales’ Interactive Process Analysis (IPA) has been included in the
data analysis (Bales, 1970; Bales & Cohen, 1979; Miller, 1991). The data analysis
also included categories based on the conceptual framework from Chapter 2 (see
85
Figure 2.7). The categories included group development stages and group
metacognitive strategies. The analysis also incorporated a constant comparison
method as recommended by Strauss and Corbin (1998).
Table 3.2
Cycle 1 Data Collected and Method of Analysis
Source of data Type of data collected Method of data analysis
Observations Videos Transcriptions of audio
(MP3) recordings
Interactive Process Analysis (IPA)
Identification of group development stages (derived from conceptual framework)
Identification of metacognitive strategies (derived from conceptual framework)
Classroom artefacts Group diaries Checklists Metacognitive
questionnaires Individual questionnaires
Identification of task and team skills (derived from literature review)
Constant comparison Identification of
metacognitive strategies (derived from conceptual framework)
Constant comparison
Group interview Transcription of focus
group interview
Constant comparison
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The transcriptions of the MP3 recordings of the groups working together
were analysed using Bales’ IPA system which has been used previously in group
research (Hare & Hare, 1996). Armstrong and Priola (2001) stated that the IPA
system is one of the most widely employed schemes for assessing group
interaction. Previous studies have demonstrated the reliability and validity of the
IPA method of analysis (e.g., Underwood & Underwood, 1999).
The IPA consists of a content analysis that looks at the communication
patterns of the groups involved in the study. The IPA divides group
communication into acts, or sentences, where each member’s speech can be
composed of one or more acts (Bales & Cohen, 1979). The ‘act’ of
communicating which is directed at other group members, is coded. The content
is not recorded, rather the behaviour it represents is recorded (Bales, 1970).
Coding consists of making a tally when certain group communication acts occur.
Bales’ (1970) IPA coding system identifies a set of twelve categories that
identify group communication behaviours or acts (see Appendix U, p. 298). The
behaviours are divided into two main domains: those behaviours concerned with
the group task and those focusing on the maintenance of group relationships
(Hoover, 2002). Each group was recorded during each computer session and the
recordings were transcribed. The transcriptions were coded using the IPA coding
scheme.
Transcribed interviews, group interactions, diary checklists, and group
questionnaires were also analysed according to the existing conceptual framework
87
from Chapter 2. The initial coding system, using concepts from the literature, was
based on the metacognitive strategies of planning, monitoring, and evaluating
identified in Chapter 2. The metacognitive strategies were used as a basic
framework in which to begin to categorise the group data. The coded planning,
monitoring, and evaluating stages of group metacognition, were further
categorised using Schraw’s (2001) regulatory checklist for improving students’
thinking about their learning processes (see Appendix C, p. 263). The final coding
system (see Appendix V, p. 299) reflects the use of group metacognitive strategies
by the groups involved in the study.
The aim of using previously identified concepts from the literature was to
find any emerging patterns common to a number of groups. Miles and Huberman
(1994) suggested researchers initially use themes derived from the literature. An
advantage of using the concepts from literature is that they are already loaded
with analytical meaning. Collected data in the form of observations, individual
interviews, and diary inserts also informed further data collection during the
group interviews (Strauss & Corbin, 1998; Walker, 1985).
A constant comparison approach, where theory is derived from the data,
was also adopted in this study in order to extend the analysis from ‘coding and
counting’ to ‘exploring and understanding’ (Stahl, 2006). Coding occurred in two
main stages. The first stage involved a process of open coding in which
transcripts, interviews, individual questionnaires, and classroom artifacts were
coded in a process of ‘in vivo coding’ (Strauss & Corbin, 1990). ‘In vivo coding’
88
consists of a set of procedures for analysing qualitative data in order to build a
theoretical framework (Strauss & Corbin, 1998). As the study already consisted of
an initial conceptual framework the analysis focused on discovering themes and
refining concepts identified in the existing framework.
Categories were identified from the data collected using the constant
comparison method. Constant comparison relies on the emergence of theoretical
categories from an on-going data collection and analysis (Huberman & Miles,
2002). The continual analysis of the questionnaires, and group diaries followed
the constant comparison method and included comparing:
1. Data from the groups at different points in time
2. Data within categories
3. Data across categories (Charmaz, 2000; Denzin & Lincoln, 1998; Ryan
& Bernard, 2003; Silverman, 2001; Strauss & Corbin, 1998).
Huberman and Miles (2002) stated that the key to comparison making is
looking at the data in divergent ways and to define categories before identifying
within-group and between-group similarities and differences (Strauss & Corbin,
1998). Categories were identified from the data as they emerged in order to
inform the final conceptual model (see Figure 6.4).
Data analysis was conducted in an ongoing hermeneutic cycle (Guba &
Lincoln, 1989). Collected data was entered into NVivo® software allowing data
to be organised into codes and categories. As patterns were identified, they were
89
compared with existing theory and a coding scheme was created. Further
categories were added as data were collected and analysed.
All data from this cycle were analysed in order to inform the design of a
conceptual model that would scaffold within-group metacognition while building
collective knowledge with groups working around computers. Data were also
analysed in order to ascertain where modifications were to be made to the initial
conceptual framework and instructional activity to be used in Cycle 2 of the
study.
3.3.1.2 Cycle 2: Within- and between-group metacognition
Cycle 2 involved the design of within- and between-group metacognitive
scaffolds for groups building collective knowledge within the Knowledge
Forum® learning environment (Research Objectives 1 and 2).
Participants
The participants in the final cycle of this study were chosen from one Year
4 class and one combined Year 4-7 class from the same schools used in the first
cycle of this study. All students from both classes were involved in the study. The
students from the Year 4 class were not involved previously with the study while
some students in the Year 4-7 class had been involved in the first cycle of the
study. The same students were included in the second cycle in order to ascertain if
90
students who had previous experience with the task and with the structured group
activity could transfer their knowledge to the second cycle.
The class teachers formed the groups with the Year 4 teacher forming
mixed-ability groups of mixed gender and the Year 4-7 teacher allowing students
to form their own groups. Gillies and Ashman (2000) found the effect of different
ability and gender composition in trained co-operative groups was minimal, so the
teachers chose the group composition based on their preferred method.
Three groups from each class were chosen for an in-depth study based on
teacher observations of the students involved. These six groups (18 students),
were selected by means of theoretical sampling, a purposive sampling technique
in which maximum diversity is sought in characteristics considered salient to the
research question (Case & Gunstone, 2002; Glaser & Strauss, 2004; Lincoln &
Guba, 1985). Theoretical sampling involves choosing groups which are likely to
extend the emerging theory on group metacognition, while maximum diversity or
variation involves selecting a wide range of participants in order to achieve the
maximum variation possible (Guba & Lincoln, 1989; Huberman & Miles, 2002).
The comparative method of data analysis also requires deviant cases to be
identified in order to account for all of the data collected in the study (Silverman,
2001).
One group from each class was chosen as they were nominated as being
able to work well in groups, while one group was chosen due to the students being
identified as not working well with other students due to their disruptive
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behaviour. A final mixed-gender group was also selected from each class in order
to achieve a wide variation of groups. The six groups formed two online teams
consisting of groups from both schools (see Table 3.3).
Table 3.3
Formation of Online Teams
School 1 School 2
Team One Group A
Group C
Group B
Team Two Group F Group D
Group E
Procedure for Cycle 2
Cycle 2 proceeded in three phases: Phase 1: Planning the teaching
experiment, which involved refining the experiment from Cycle 1; Phase 2:
Conducting the teaching experiment; Phase 3: Analysis of data from the teaching
experiment.
Phase 1: Planning the teaching experiment
Phase 1 of this second cycle involved refining the teaching experiment, or
learning activity, based on the results from Cycle 1. The problem-solving task
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involved extending the activity from Cycle 1 by having groups form online
Knowledge Forum® teams with other groups (see Table 3.3). Each group created
their own mathematical model and then combined their model with the other
groups in their team to find the best city in Australia (see Appendix W, p. 300).
This task differed from Cycle 1 in which groups made a combined ranking model
between the two classes (see Appendix M, p. 288). The CD incorporating the
categories from Cycle 1 was used in this cycle (see Appendix T, p. 297). A
number of new websites were also included on the CD for students to further
research their chosen categories in Cycle 2.
The results from Cycle 1 were used to inform the design of within- and
between-group metacognitive scaffolds for groups building collective knowledge
within the Knowledge Forum® learning environment. Specific group roles and
skills that students from Cycle 1 had highlighted as being necessary for effective
groups were placed on posters and displayed in each class (see Appendix X, p.
302). The use of social skills, such as those used in the poster, influences the
effectiveness of cooperative groups (Johnson & Johnson, 1993) and the posters
were based on Dishon and O’Leary’s (1984) task- and team-skills as well as
group roles identified in the first cycle. Conflict management skills were also
placed on a poster and displayed, due to students in Cycle 1 identifying conflicts
and disagreements as the things they liked least about working in a group.
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Phase 2: Conducting the teaching experiment
The second phase of this study focused mainly on the online interaction
that occurred amongst the groups. This phase of the study ran for six weeks with
one computer lesson per week. The computer sessions were of one hour duration.
Prior to the first computer session, individual students were asked to complete an
initial questionnaire regarding their previous experience with group work. Follow-
up questionnaires were also completed by the students at the completion of the
computer sessions.
The group diary was introduced during the first lesson to scaffold
between-group metacognition. The students were asked to use the group diaries to
plan, monitor, and evaluate the introduced group roles and skills. Ten minutes of
instruction was also given at the start of the computer sessions where the groups
were shown the posters and introduced to the specific skills needed for effective
co-operative groups (see Appendix X, p.302). All groups also completed the
group planning checklist during the first computer session (Johnson & Johnson,
1993). Students were also made aware of the group roles of Keyboarder, Checker,
and Encourager, as these were the roles that groups in Cycle 1 had frequently
chosen. The group roles were written in the group diary in order to publicly
clarify the roles (see Appendix K, p. 283).
Instructions were given at the beginning of the first two computer sessions
where groups were introduced to Excel® spreadsheets and to the Knowledge
Forum® environment and shown the CD compiled from various websites
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detailing information about each major city (see Appendix T, p. 297). In order to
find the “best city”, in Australia, students were asked to evaluate information
taken from the various websites in order to rank the major cities in Australia.
During this phase of Cycle 2, each group of students formed an online
Knowledge Forum® team with two other groups and each online team included at
least one group from each school (see Table 3.3). The three groups in each team
initially developed their own ranking models using information they gained from
the CD database and from an Internet search. Incorporating the use the
Knowledge Forum® database enabled the groups to share their models and co-
construct a shared team model (see Appendix W, p. 300).
The new online team needed to collaborate online in order to create a
combined mathematical ranking model by providing feedback (such as comments
and questions) to each other about their ranking models. They also simultaneously
engaged in the process of revising and improving their ranking models based on
feedback they received from other online teams. Groups were asked to rank two
categories each and then to work out an overall ranking for their online team
compiled from an amalgamation of each group’s categories. The groups ranked
the categories they had chosen by using the information they gained from the CD
database (see Appendix T, p. 297) and from additional websites included on the
CD. The ranked categories from each group were then combined into an Excel®
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spreadsheet for each online team. The teams then sorted the combined rankings to
find the best city in Australia (see Appendix W, p. 300).
In order to scaffold within-group metacognition, the metacognitive
scaffolds of planning, monitoring and evaluating were introduced, by the use of a
learning diary, to the groups working around the computer (see Appendix L, p.
284). Groups were required to reflect on how their group was functioning using
the planning, monitoring, and evaluating scaffolds: planning how to approach the
given learning task, monitoring progress of the task, and evaluating their progress
toward the completion of the task.
Students also completed a questionnaire after the activity on how they
thought the group had functioned; focusing on both the task and team aspects of
group work (see Appendix F, p.266). The questions were similar to the questions
used in a study by Whicker et al. (1997), in which students were interviewed on
their perception of co-operative group work.
Prior to the first computer session, students from the Year 4 class were
asked to complete the initial group work questionnaire regarding their previous
experience with group work (see Appendix E, p. 265). The Year 4-7 class had
been asked the same questions during the first cycle, a year earlier. A final
individual group-work questionnaire was completed at the end of the computer
sessions by all students involved in this second cycle of the study. The final
questionnaire encouraged students to comment on their group work during the
96
study and what they thought worked well and what did not work (see Appendix F,
p. 266).
While most CSCL studies have looked at the frequency and length of
messages, they rarely indicated why the messages happened (Henri, 1991; Mason,
1991). For this reason, groups were interviewed regarding their use of the
Knowledge Forum® database. Silverman (2001) advocates using open-ended
interview questions in order to gain a more effective understanding of students’
group experiences (see Section 3.2.2).
The focus-group interviews focused on the problem solving and the team
aspects of the teaching experiment (Hoyles & Healy, 1994). During the interview,
students were also asked questions based on those used by Charmaz (2003) (see
Appendix D, p. 264), and based on answers received in the first cycle. Students
were asked to elaborate on their answers and further questions were asked
depending on the answers given during the interview (Morse, 1998). Students
were also asked to complete a group questionnaire on their metacognition during
problem solving (Appendix B, p. 262).
Phase 3: Analysis of data from the teaching experiment
The final phase of Cycle 2 focused mainly on the online interaction that
occurred between the groups. The focus of the data analysis in this phase was on
data that reflected students’ knowledge and understanding of group context. A
qualitative descriptive analysis approach was used for bringing out the details
97
from the viewpoint of the group members and provided information about the
context, the participants, and the activities involved (Johnson & Christensen,
2004).
Data for this stage of the study were derived from classroom artefacts (see
Section 3.2.3), including group diaries, checklists, questionnaires, and Knowledge
Forum® notes, that showed the groups working together. A focus-group interview
was also conducted. The data collected and method of data analysis are presented
in Table 3.4.
The data analysis focused on how teams form a shared-team monitoring of
their group process. Categories coded included the task and team skills selected
by the groups in Cycle 1 (see Section 4.1.2) and categories based on the
conceptual framework from Chapter 2 (see Figure 2.7). Tindale, Kameda, and
Hinsz (2003) stated that metacognition in groups can be considered to be how
group members think about the ways they process and share knowledge in an
attempt to reach group decisions. Therefore, the Knowledge Forum® notes were
coded according to the metacognitive and group strategies taken from the
conceptual framework (See Figure 2.7).
The Knowledge Forum® notes were also coded using the Bales’ IPA
system that was used in Cycle 1 to code the MP3 audio transcripts of the groups
working together. The Knowledge Forum® notes were divided into two main
domains: those concerned with the task and those concerned with the team. These
98
two domains were compared to the domains coded in Cycle 1 from the MP3
transcriptions.
Table 3.4
Cycle 2 Data Collected and Method of Analysis
Source of data Type of data collected Method of data analysis
Classroom
artefacts
Group diaries (Within-group metacognition)
Checklists and metacognitive questionnaires (Within-group metacognition)
Individual questionnaires
Knowledge Forum® notes (Between-group metacognition)
Identification of task and team skills (derived from Cycle 1)
Identification of metacognitive strategies (derived from conceptual framework)
Constant comparison
IPA Identification of group
development stages (derived from conceptual framework)
Identification of metacognitive strategies (derived from conceptual framework)
Group interview Transcription of focus group interview
Constant comparison
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Mohammed, Klimoski, and Rentsch (2000) stated that the most common
methodologies used to study shared-team mental models are Likert-scale
questions to measure the degree the team shared their mental models. A final
Likert-scale questionnaire was issued to group members where they were asked
questions based on Schraw’s (2001) metacognitive checklist (see Appendix C, p.
263). For example, ‘What is our goal?’ was one of the planning questions asked.
After groups completed the questionnaire, the answers were analysed in order to
discover the degree to which each team shared an understanding of the group
metacognitive process.
Students were also asked in their final interview if they would be willing
to work in the same groups in future activities. Tindale et al. (2003) state the team
members need to have a similar understanding of the team processes groups need
to use in order to work effectively. The shared teamwork schema leads to team
members being more willing to work together in future activities. The answers
given by students in this cycle were compared to the answers given by students in
Cycle 1.
3.3.2 Stage 2: Development of a unified conceptual model
During this stage, the findings from Cycles 1 and 2 were cumulated into a
unified conceptual model to inform the design of scaffolds for within- and
between-group metacognition within CSCL environments. The unified conceptual
model generated in this stage had its genesis in the initial conceptual framework
100
presented in the summary of Chapter 2 (see Figure 2.7). This initial framework
was developed from an analysis and synthesis of the relevant research literature.
During each of the two cycles in Stage 1, various aspects of the initial framework
were evaluated. The outcomes of these cyclic evaluations were able to inform on-
going modifications of the initial framework and also inform the design of the
final unified conceptual model (see Figure 6.4).
3.4 Conclusion
This study proceeded in two stages. Stage 1 included the two cycles of the
design experiment (see Figure 3.1). Stage 2 involved cumulating the results from
both cycles into a unified conceptual model to inform the design of scaffolds for
within- and between-group metacognition within CSCL environments.
Each cycle in Stage 1 included three phases of planning the experiment,
teaching the experiment, and analysing the results, in order to study the influence
of group metacognitive scaffolds on primary school groups. The focus of the
design experiment was to develop scaffolds for group metacognition that could be
used for instructional tools and to inform theory. In each cycle, a case study was
presented and data was collected and analysed to inform the development of
scaffolds for within- and between-groups working in CSCL environments. The
problem as well as the group roles and skills were refined following the analysis
of each cycle.
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Analysis involved a content analysis, categories from the literature review
including group-development stages and metacognitive strategies, and constant
comparison. The analysis allowed for the development of theory, from the data
collected, on how to establish and maintain shared metacognitive group thinking
within- and between- cooperative groups working around and through the
computer. All data from Cycle 1 and Cycle 2 were analysed, in order to inform
the design of a conceptual model in Stage 2 of the study that would scaffold
within- and between-group metacognition while building collective knowledge in
CSCL environments (see Figure 6.4).
The following chapter presents the results from Cycle 1 of the study which
introduced group-metacognitive scaffolds for groups working around the
computer. Chapter 5 presents the results from Cycle 2 of the study which
introduced group-metacognitive scaffolds for groups working within a computer
supported collaborative (CSCL) environment. Chapter 6 combines the results
from Cycles 1 and 2 into a unified conceptual model that can be used to scaffold
within- and between-group metacognition within CSCL environments.
102
103
CHAPTER 4: RESULTS FROM CYCLE 1
Within-group metacognition
The aim of this study was to develop a conceptual model to inform the use
of scaffolds to facilitate group metacognition during mathematical problem
solving in CSCL environments. In order to achieve the study aim, a design
research methodology incorporating two cycles was used. Cycle 1 focused on
within-group metacognition for groups working around the computer (Research
Objective 1); Cycle 2 focused on both within- and between-group metacognition
for groups working within a computer supported collaborative learning (CSCL)
environment (Research Objectives 1 and 2).
This chapter presents the results from Cycle 1 which focused on within-
group metacognition. Data sources (see Table 3.2) included observations (see
Section 3.2.1); a focus group interview (see Section 3.2.2); and classroom
artefacts (see Section 3.2.3) including group diaries, checklists, metacognitive
questionnaires, and individual questionnaires.
Three categories of themes that mirror the three main factors for
successful problem solving and learning identified in the conceptual framework
presented in Chapter 2 were derived from the analysis of data: (1) organisational,
(2) cognitive, and (3) metacognitive.
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4.1 Organisational themes
Six organisational themes were derived from the analysis of the data:
1. The groups engaged in a higher number of task-related than team-related
behaviours.
2. The groups adopted task- and team-orientated behaviours in order to work
together efficiently.
3. Task-related disagreements increased during the course of the study for
some groups.
4. The groups went through a development process which was less linear and
more convoluted than that proposed by Tuckman and Jensen’s model
(1977).
5. Students identified five aspects important for group work: having fun,
working together, listening, helping, and sharing ideas.
6. Students identified disagreements and conflicts as aspects they liked least
about working in a group.
4.1.1 Theme 1
The groups engaged in a higher number of task-related than team-related
behaviours.
Theme 1 was derived from the analysis based on Bales’ Interactive
Process Analysis (IPA) (Bales, 1970, Bales & Cohen, 1979; Hare & Hare, 1996;
Miller, 1991) of the video and MP3 recordings of the groups working together.
The IPA method employs a set of 12 categories divided into two domains: task-
related and team-(or socio-emotional) related behaviours.
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An example of task-related interaction can be seen in this conversation
from Group A when the group members were ranking the cities according to
rainfall.
Student 1: Who has the most rain?
Student 2: Um Darwin, Melbourne
Student 1: Which one, which one has the most rain?
An example of team-related interaction can be seen in the following
conversation from Group C during the third computer session when they were
discussing how well their group was working together:
Student 1: It is fun working with all these people it's great
Student 2: We could all write something
Student 3: Yeah but it’s fun working with…because it's really nice
Student 1: We're good friends and good to gets along with
Student 3: It's quite nice
The IPA coding of the transcriptions of the recordings presented in Table
4.1 indicates that the groups had a much higher number of task-related behaviours
(77.8%) than team-related behaviours (22.2%).
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Table 4.1
IPA Domain Frequency
Domains Number of behaviours Percentage of total
1. Task-related 2567 77.8%
2. Team-related 734 22.2%
Total 3301 100%
A further analysis of the video and MP3 recordings found that a major reason
for why there were more task-related behaviours than team-related behaviours
was due to the open-ended model-eliciting nature of the problem task
administered to the students. This finding is consistent with findings from
previous research studies that indicate that the task affects the type of interaction
that groups engage in while problem solving (Cohen, 1994; Dishon & O’Leary,
1984; Jonassen & Kwon, 2001; Puntambekar, 1999). Complex, open-ended
problems such as the model-eliciting mathematical ranking activity utilised in this
study require a high level of task-related interaction.
4.1.2 Theme 2
The groups adopted task- and team-orientated behaviours in order to work
together efficiently.
Theme 2 was also derived from the analysis based on Bales’ Interactive
Process Analysis (IPA). With the IPA, the task and team domains are divided into
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twelve categories. Categories 1-3 (seems friendly, dramatises, agrees) relate to
positive team behaviours, categories 4-9 (gives suggestion, gives opinion, gives
information, asks for information, asks for opinion, and asks for suggestion) are
task-related, and categories 10-12 (disagrees, shows tension, and seems
unfriendly) relate to negative team behaviours.
The IPA categories that had high frequency counts were the task-related
categories of: gives information (29.8%), gives opinion (15%), and gives
suggestion (14.9%) and the positive team-related category of agrees (15.4%).
An example of gives information (29.8%) can be seen in this exchange by
members in Group E during the first computer session when the groups were
working on their ranking models:
Student 1: Our plan is to get information to use to find the top eight which
is the best
Student 2: And also, And also use information to find the best of them all
An example of gives opinion (15%) can be seen in this conversation by
Group F during the second computer session when group members were deciding
on how they wanted to rank the size of the city:
Student 1: I think big cities are best though
Student 2: I hate big cities
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The category gives suggestion (14.9%) was evident in the discussion from
Group P during the third computer session when they were working out how to
rank movie theatres:
Student 1: Let’s take a vote
Student 2: Let’s count
The category of agrees (15.4%) was the positive team-related behaviour
most frequently coded for this cycle. The category agrees was coded for
behaviours or acts that show agreement, passive acceptance, understanding,
concurring or compliment. An example of when group members showed this
category was when Group H was working together to rank the top cities:
Student 1: Then we'll do pollution (Gives suggestion)
Student 2: OK (Agrees)
The categories with the lowest frequency counts were the negative team-
related categories of: seems unfriendly (0.3%) and shows tension (0.5%). Seems
unfriendly was coded in the first computer session for Group L when the group
members were posting their first note to the Knowledge Forum ® database:
Student 1: I don’t like Evan (Student 2) as much I like you Larry (Student
3)
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An example of shows tension was evident from Student 1 in Group E,
during the second computer session, when the group was choosing the group
skills to focus on in the following computer session:
Student 1: Come on I’ve already told you
Student 2: So we got to pick one?
Student 1: We all have to agree on this one alright
Table 4.2 displays the IPA category frequency for this cycle of the study.
The IPA data coding was discussed with a senior researcher (R. Nason, personal
communications, 2007) and all observed behaviours were able to be categorised
under the IPA categories. The results from the IPA category count showed all
groups exhibited group behaviours that focused mainly on the task-related
behaviours of gives information (29.8%), gives opinion (15%), and gives
suggestion (14.9%) and the positive team-related category of agrees (15.4%).
This finding is consistent with previous studies that suggested that groups
working on open-ended problems need a high level of discussion to clarify the
goal and work together efficiently (Cohen, 1994; Gillies, 2000; Jonassen & Carr,
2000).
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Table 4.2
IPA Category Frequency
Categories Number of behaviours Percentage of total
Positive team behaviours
1. Seems friendly
24
0.7%
2. Dramatises 77 2.3%
3. Agrees
Task-related behaviours
508 15.4%
4. Gives suggestion 491 14.9%
5. Gives opinion 494 15%
6. Gives information 983 29.8%
7. Asks for information 280 8.5%
8. Asks for opinion 153 4.6%
9. Asks for suggestion
Negative team behaviours
166 5%
10. Disagrees 99 3%
11. Shows tension 16 0.5%
12. Seems unfriendly 10 0.3%
Total 3301 100%
4.1.3 Theme 3
Task-related disagreements increased during the course of the study for some
groups.
Theme 3 was derived from the analysis based on Bales’ Interactive
Process Analysis (IPA). IPA frequency count tables were completed for each of
the 16 groups (see Appendix Y, p. 306). The percentage of behaviours is
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presented in Appendix Y (p. 306) for each group as well as a brief description of
each group’s activities, including examples of group behaviours, in order to
highlight why certain ‘acts’ or ‘behaviours’ occurred.
Group conflict can be classified into either task or team issues (Rentsch &
Zelno, 2003). Task conflict leads to differences of opinion and is desirable for
effective teamwork while team conflict can be destructive to the team. The
majority of the disagreements in the first computer session tended to be team-
related. The following example, from the first session, shows Group B involved in
a team-related conflict regarding what member was doing which group role:
Student 1: You’re not the recorder, I am (disagrees)
Student 2: It's recording (gives information)
Student 1: You’re not allowed to record (disagrees)
Eight groups had behaviours coded for the category disagrees (4.3%).
However, in terms of knowledge building, most of the disagreements towards the
end of the study were task-based in nature and tended to be resolved quickly. The
category disagree was observed and coded during the last session, from Group E,
when the group was discussing how to rank their final categories. The following
example shows the task-related disagreement with Group E was minor and
resolved quickly:
Student1: Brisbane doesn't have a lot of hospitals.
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Student 2: It does but
Student 3: Canberra doesn't
Student 1: What about we start from number eight. What about number
eight should be….
Student 2: Darwin doesn't have that many
Student 1: This isn't how many hospitals they have
Student 2: Oh
Student 1: I was going to say cause Brisbane that's going to be
Student 2: Melbourne
Student 3: No Melbourne you've got
Student 2: Ok do all them Melbourne being number 8
Student 1: No we all have to agree on them
Student 2: That's number one
Student 3: Yep
Student 1: We have to agree on every single one
Student 2: So let's pick them together
4.1.4 Theme 4
The groups went through a development process which was less linear and more
convoluted than that proposed by Tuckman and Jensen’s model (1977).
Theme 4 was derived from an analysis of the transcripts of the videos and
MP3 recordings. The transcripts were coded using constructs derived from
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Tuckman’s model of group development (Tuckman & Jensen, 1977). Tuckman
and Jensen’s model suggests that groups progress through five linear stages of
development: forming, storming, norming, performing, and adjourning. The
analysis of data found that the groups went through a development process much
less linear and more convoluted than that proposed by Tuckman and Jensen’s
(1977) model. For example, in this study, eight of the 16 groups in the initial
computer session when they were supposedly going through the forming stage of
team development engaged in conflict.
According to Tuckman and Jensen (1977), during the forming stage,
conflict is generally avoided as members get to know one another. However, in
these eight teams, the students engaged in team-related conflict about who was
going to take up each group role during the initial session. Unlike many of the
group formation studies reported by Tuckman and Jensen, the members of each
group in this study came from the same classroom. Therefore, the conflict
observed in the first session with these eight groups may have been related more
to past events than the forming of the teams in this study.
Kormanski (1999) stated that the forming stage involves groups getting
orientated to the task and getting to know other members. The groups showed no
behaviours related to getting to know each other, as all 16 groups had prior
knowledge of their group members. However, a brief forming stage, where groups
were orientated to the task, occurred during the first computer session when
groups were involved in planning the task.
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Two basic tenets of Tuckman and Jensen’s (1977) model are that all
groups go through the stage of storming and that storming types of behaviour
occur early on during group development immediately after the forming stage.
The analysis of the observation data in this study revealed that only nine of the 16
groups engaged in storming types of behaviour during the course of the study.
Furthermore, storming types of behaviour in these nine groups occurred
throughout the study rather than just after the forming stage where Tuckman and
Jensen’s (1977) model predicts it will occur. The major group task during
storming is the development of an ability to listen and seek productive resolutions
to conflict (Tuckman & Jensen). The nine groups engaged in resolving a number
of conflicts. The following example shows how Group K resolved their team
conflict during the fourth computer session, as they reached an agreement about
who was doing what role and what each group role entailed:
Student 1: Then I get the MP3 player
Student 2: No you don't. Student 2 gets the MP3 player you get to be
keyboarder. You’re keyboarder, you get to type
Student 3: And I help him
Student 2: No, he doesn't need help
Student 1: Yeah the encourager helps
Student 2: No the encourager just goes your do you need help
Student 3: Yeah I'll ask that and help
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Student 1: Yeah and I'll help too
Tuckman and Jensen’s (1977) model also posits that the process of group
norming (establishing the norms of behaviour) predominantly occurs during the
third stage of group development. From the transcripts (of the audio MP3
recordings), it was evident that the norming process took place at the beginning of
each session as the groups allocated the group roles and worked out which group
skills their group needed to focus on during the following session. For example,
during the first session as Group C was allocating member roles, Student 1
defined what they needed to do when they were allocated the group role of
encourager:
Student 1: And I'm the encourager and, and I'm the encourager that keep
(sic) people happy and that
Group P also discussed what the encourager role entailed:
Student 1: You’re the encourager so you've got to say things like say “Oh
wow!”
Student 2: Encourage
Student 1: Say like “You’re doing really good, really good”
Norming negotiations occurred amongst group members about who was
doing which role. For example, during the second session the group members
116
from Group E worked out who was doing the group roles of keyboarder and
recorder.
Student 1: You can be the keyboarder and I'll be the recorder
Student 2: I'm the keyboarder and I get it (the recorder role) next week
Tuckman and Jensen’s (1977) model also includes a fourth development
stage, performing, which involves members working interdependently as a group.
Langan-Fox (2003) stated that the performing stage occurs in only a small
percentage of groups. However, the analysis of data in this study found that the
groups were working interdependently throughout the study incorporating
effective task- and team-oriented behaviours, and not just throughout the later
phases of the study.
Adjourning is also an important stage identified by Tuckman and Jensen
(1977). Kormanski (1999) stated that the adjourning stage involves the
disengagement of the group and the finalising of the task. All 16 groups finalised
the task by posting their final mathematical ranking model on to the Knowledge
Form® database.
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4.1.5 Theme 5
Students identified five aspects important for group work; having fun, working
together, listening, helping, and sharing ideas.
Theme 5 was derived from an analysis of the individual questionnaires.
The questionnaires were coded according to a constant comparison method of
data analysis (Charmaz, 2000; Denzin & Lincoln, 1998).
Question two on the initial questionnaire asked students what they liked
about working in a group. The responses tended to fall within four categories,
having fun (10%), sharing ideas (15%), helping (20%), and working together
(25%). Table 4.3 presents the questions asked, results from a constant comparison
method of analysis, and examples of the responses in order to highlight why
certain concepts emerged.
Question one on the final individual questionnaire also asked students
what they liked about the learning groups. The responses fell into similar
categories to the responses to the same question on the initial questionnaire. Three
categories were similar including working together (21%), fun (14%), and sharing
ideas (12%).
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Table 4.3
Responses to Question Two on Initial Individual Questionnaire
Question Responses For example
What do you like about
working in a group?
Having fun
(10%)
Other poeple (sic) can
help one enouther (sic)
and it’s rather fun
(Student 1, Group H).
Share ideas
(15%)
You can share you (sic)
ideas with other people
(Student 3, Group O).
Helping (20%) You can help each other
(Student 3, Group K).
Working
together (25%)
That you can work
together and get to know
people better (Student 1,
Group I).
Question five on the initial individual questionnaire asked students what
advice they would give to someone who has just discovered they will be working
in a group. The fun aspect of working with others was highlighted by students
(50%). This response supported the fun aspect highlighted from the third question
which asked students what they liked about working in groups (10%).
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Question seven on the final individual questionnaire also asked students
what advice they would give to someone who has just discovered they would be
working in a group (Table 4.4). The responses that were made included comments
that fell into four main categories including have fun (17%), listen (12%), work
together (12%), and share ideas (7%), as well as a variety of other comments
(26%). These findings differed from the responses to the same question on the
initial individual questionnaire.
Table 4.4
Responses to Question Seven on Final Individual Questionnaire
Question Responses For example
What advice would you give to someone who has just discovered they would be working in a group?
Share ideas (7%) I would encourage them to have a go at sharing their ideas and if that doesn’t work out have another go (Student 1, Group I).
Listen (12%)
Listen to everyone's ideas (Student 3, Group N).
Work together
(12%) Get your group to work
together (Student 1, Group M).
Have fun (17%)
That it is really fun and just ask if you need help plus that everyone is nice (Student 2, Group H).
Other comments
(26%) To relaxe (sic) because
nothing is rough with working with other people (Student 3, Group A).
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Responses to the initial questionnaire mainly focused on the fun aspect
(50%) while the responses to the final questionnaire went beyond having fun to
include knowledge building behaviours such as sharing ideas, listening, and
working together. The perceptions of students regarding this aspect of group work
is important for understanding what students consider important for effective
group work.
4.1.6 Theme 6
Students identified disagreements and conflicts as aspects they liked least about
working in a group.
Theme 6 was also derived from an analysis of the individual
questionnaires. On the questionnaires students were encouraged to comment on
their group work and what they thought worked well and what did not work well.
Question three on the initial questionnaire asked students what they did
not like about working in groups. Students commented that disagreements and
conflicts (55%) were the things they liked least about working in groups (Table
4.5). Students also included comments about dominant group members (20%) and
others not being listened to (10%).
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Table 4.5
Responses to Question Three on Initial Individual Questionnaire
Question Responses For example
What don’t you like
about working in
groups?
Not listened to (10%) Sometimes you don’t
get to have a say
(Student 2, Group
O).
Dominant group
members (20%)
When there is a
bossey (sic) peson
(sic) (Student 1,
Group P).
Disagreements and
conflicts (55%)
That sometimes you
can disagree and
things get into a
fight (Student 2,
Group I).
Question two on the final questionnaire asked students what they did not
like about working in the group. On the initial questionnaire 55% of students had
commented on disagreements and conflicts while on this questionnaire, only 29%
made comments about disagreements and conflicts. One student commented:
There was a little bit of a fight but we got over it and went on with
our job (Student 2, Group J).
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The comments on the initial questionnaires focused on the fights that
occurred with previous group work. The comments regarding conflicts decreased
in the final questionnaire and focused on the disagreements that had occurred
during the activity and how the groups had worked through them.
4.1.7 Organisational themes summary
Groups engaged in a higher number of task-related than team-related
behaviours. Task-related behaviours such as gives information, gives opinions,
and gives suggestions were the most prevalent behaviours shown throughout the
course of the study. The high number of task-related knowledge building
behaviours could be attributed to the nature of the task in which the students were
engaged. This assertion is consistent with the literature that indicates that groups
involved in solving complex open ended problems tend to engage in task-related
knowledge building interactions (Dishon & O’Leary, 1984; Jonassen & Kwon,
2001).
The groups adopted effective task- and team-orientated behaviours in
order to work effectively together. The number of positive team behaviours
increased over the study, while the negative team behaviours of seems unfriendly
and shows tension decreased from the first to the last session. These two
behaviours were disruptive and unproductive to the work of the group. Cathcart et
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al. (1996) stated that such unproductive behaviours can lead to a feeling among
group members that they are not accepted by other group members.
Task-related disagreements increased during the course of the study for
some groups. Disagreements increased from the first session. However, the
disagreements were more task-related (as opposed to team-related) in the final
sessions. This finding is consistent with reports in the literature that indicates that
task-related conflicts tend to be related with positive group outcomes (Rentsch &
Zelno, 2003).
The groups performed well but not in the linear group development
process suggested by Tuckman and Jensen (1977). The group forming stage only
occurred briefly at the beginning of the activity, as groups were involved in
planning the task. Storming and norming stages occurred throughout the activity
rather than in a linear pattern or at certain ‘stages’. The storming stage occurred
throughout the study as groups sought productive resolutions to conflicts.
Norming occurred throughout the study as the groups allocated group roles and
chose group skills to focus on at the beginning of each session. Most groups
worked interdependently during the study and developed their norms of behaviour
at the beginning of each computer session. Performing occurred throughout the
study as groups incorporated effective task- and team-oriented behaviours. The
groups were all involved in the final adjourning phase as the task was finalised
and the groups were disbanded.
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The results showed the groups organised their task- and team-orientated
behaviours in order to work efficiently together. Students identified a number of
aspects important for group work including having fun, working together,
listening, helping, and sharing ideas. The students also identified arguments and
fighting as the things they liked least about working in a group.
4.2 Cognitive themes
Two cognitive themes were derived from the analysis of the data:
7. The groups developed a shared knowledge of the task and how they
wanted to perform as a team.
8. The groups developed and focused on their own task- and team-skills.
4.2.1 Theme 7
The groups developed a shared knowledge of the task and how they wanted to
perform as a team.
Theme 7 was derived from the analysis of the group diaries. The group
diaries were used by the groups to organise their task- and team-skills and to
delegate group roles while they completed their mathematical ranking models.
The task- and team-skills adopted and utilised by the groups were initially
identified from the literature review in Chapter 2. Further team- and task-skills
then were identified using a constant comparison method of analysis.
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Task-skills included check group understanding, give ideas, share
information, talk about the work, get the group back to work, repeat what has
been said, and ask questions. Team-skills included encourage, check for
agreement, encourage other members to talk, respond to ideas, using eye contact,
say ‘thank you’, share feelings, and keep things calm. The skills chosen were used
by the groups during the following computer session.
In Session 3, Group C planned to focus on the task-skills of check group
understanding and share information; the group used these skills in the following
computer session where groups were ranking the capital cities in Australia:
Student 1: Today we’re going to be ranking, ranking the city (Check group
understanding)
Student 2: What do you think would make a good city? (Check group
understanding)
Student 3: Not leaving rubbish behind and riding (Share information)
Student 2: And what do you think would make a good city? (Check group
understanding)
Student 1: Less pollution, good hospitals (Share information)
Student 2: I think a good city would have lots of good schools and parks,
good committees and groups, good theatres umm beautiful
parks that's what I think would make a good city (Share
information)
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As shown in Table 4.6, the group task-skills of talk about the work (9),
check group understanding (8), and ask questions (8), were the task-skills most
chosen by the groups to focus on in the computer sessions.
Table 4.6
Frequency of Task-Skills Chosen
Check group
understanding
Give ideas Share
information
Talk about
the work
Ask questions
8 5 5 9 8
Table 4.7 shows the group team-skill of encourage was the team-skill
most chosen (12) from the list of group skills for the groups to focus on in the
computer sessions, followed by check for agreement (8), use eye contact (7), and
keep things calm (7).
By planning which team-skills would be focused on, group members were
able to identify skills needed to be improved. For example, in session 3, Group A
planned to focus on the team skill of encourage, the use of this skill was evident
during the following session.
Student 1: You've done a good draft (encourage)
Student 2: Does that make you satisfied? (Check for agreement)
Student 1: You've done well (Encourage)
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Table 4.7
Frequency of Team-Skills Chosen
Encourage Check for
agreement
Use eye
contact
Say ‘Thank
you’
Keep things
calm
12 8 7 4 7
There was an overlap of skills nominated by the groups as task- or team-
skills. Some groups nominated the same skill as the task- and the team-skill they
were going to focus on in the next computer session. For example, Group D chose
the skill of be positive for their task- and team-skill during the third computer
session. The overlap of task- and team-skills chosen by the groups shows that the
group members were developing a shared understanding about what their group
needed to be efficient.
4.2.2 Theme 8
The groups developed and focused on their own task- and team-skills.
Theme 8 was also derived from the analysis of the group diaries. The
analysis showed that seven groups chose skills to focus on that were not on the
list of group skills included in the diary. The seven groups nominated group skills
relevant to the specific needs of their group, combining both task- and team-skills.
The main task-skills nominated by the groups included, doing the work,
seek opinions and information, working together, and contributing ideas. The
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main team-skills nominated by the groups included: listening to each other,
communicating, be positive, and being quiet. Benjamin et al. (1997) and Cathcart
et al. (1996) stated that students should be encouraged to create their own list of
group skills appropriate for their group to be effective. The findings show that
from the second computer session, the seven groups began to nominate their own
group skills relevant to their group. Group members took a shared responsibility
for nominating skills relevant to their group, rather than just copying from the list
of group skills.
4.2.3 Cognitive themes summary
During this cycle, the diaries helped the groups to organise their
knowledge of the task- and team-skills into a shared understanding of how they
wanted to perform as a team. Group members showed a shared-group
understanding by nominating their own group skills, adopting what Scardamalia
(2002) describes as a collective cognitive responsibility. Scardamalia stated that
this is a necessary condition for knowledge building behaviour.
The development of an external representation regarding team work and
task work enabled groups to develop a shared understanding of how their group
was performing. Researchers such as Cannon-Bowers and Salas (2001) and
Klimoski and Mohammed (1994) have stated that external representations, such
as the group diary used in this research study, help groups formulate a shared
129
understanding of both their team-work and their task-work as well as allowing
them to articulate their thinking. During this study, group members were able to
use the diary to organise their knowledge of the group task, roles, and skills into a
shared team model of how their group needed to perform.
It was noted that the groups incorporated the nominated group skills into
their co-operative group behaviour. The task- and team-skills nominated by the
groups, from the group skills listed in the group diaries, were used in the
following computer sessions. This is consistent with Gourgey’s study (2001)
which found that students who monitor their own learning process, through the
use of diaries or learning journals, become more proficient group learners.
Benjamin et al. (1997) and Cathcart et al. (1996) stated that students
should also be encouraged to create their own list of group skills. Groups in this
study also nominated group skills to use that were not listed in the group diary.
The group diary enhanced the co-construction of a shared understanding about
what skills the groups needed to be effective and helped the groups develop a
consensus of skills relevant to their group.
4.3 Metacognitive themes
Two metacognitive themes were derived from the analysis of the data:
9. The groups reflected on the strategies specific to the problem-solving task.
10. The groups used metacognitive scaffolds to plan, monitor, and evaluate
their task- and team- work.
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4.2.1 Theme 9
The groups reflected on the strategies specific to the problem-solving task.
Theme 9 was derived from the analysis of the answers from the group
metacognitive questionnaire that the groups were asked to complete (see
Appendix B, p. 262). The metacognitive questionnaire was completed at the end
of the study to scaffold group reflection on the three main metacognitive
strategies of planning, monitoring, and evaluating (Fortunato et al., 1991). The
questionnaire asked the groups to respond to 21 statements which described
metacognitive behaviour relating to the task that the groups had engaged in during
their problem solving. The 21 statements were categorised under four main
questions. The responses to the four questions are presented in this section as well
as separate examples of responses from the 21 statements (see Table 4.8). The
examples highlight the specific strategies that groups adopted for the problem-
solving task.
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Table 4.8
Metacognitive Questionnaire
Yes No Maybe BEFORE YOUR GROUP BEGAN TO SOLVE THE PROBLEM WHAT DID YOUR GROUP DO?
1 We read the problem more than once. 7 1 8
2 We understood what the problem was asking us 7 2 7
3 We tried to put the problem into our own words 11 2 3
4 We tried to remember if we had worked a problem like this before 2 12 2
5 We thought about what information we needed to solve this
problem 6 1 9
6 We asked ourselves, is there information in this problem that we
don’t need 2 4 3
AS YOUR GROUP WORKED ON THE PROBLEM WHAT DID YOUR GROUP DO?
7 We thought about the steps as we worked on the problem 9 0 7
8 We kept looking back at the problem after we did a step 6 8 2
9 We had to stop and rethink a step we had already done 5 7 4
10 We checked our work step by step as we worked the problem 7 4 5
11 We did something wrong and had to redo our step(s) 10 4 1
AFTER YOUR GROUP FINISHED WORKING THE PROBLEM WHAT DID YOUR GROUP
DO?
12 We looked back to see if we did the correct procedures 6 1 8
13 We checked to see if our calculations were correct 6 3 7
14 We went back and checked our work again 6 8 2
15 We looked back at the problem to see if our answer made sense 6 4 6
16 We thought about a different way to solve the problem 7 4 4
DID YOUR GROUP USE ANY OF THESE WAYS OF WORKING?
17 We drew a picture to help us understand the problem 1 15 0
18 We guessed and checked 2 9 5
19 We picked out the operations we needed to do this problem 4 4 7
20 We felt confused and could not decide what to do 4 6 6
21 We wrote down important information 6 3 5
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The first question (Before your group began to solve the problem what did
your group do?) contained six statements regarding what the group had done prior
to solving the problem (Table 4.8). Eleven groups (69%) indicated that in the
early stages of the problem solving, they had tried to put the problem into their
own words. The response to Statement 3 relates to the findings from the group
diary checklists where groups had to state what the problem was and how they
were going to solve it. All groups had used the diary to restate the problem.
Dominowski (1998) stated that restating and explaining the problem promotes
metacognitive processing. The groups used the group diaries to explain the
problem in their own words and to describe the categories they had considered.
The response to the metacognitive statement confirmed that groups had restated
the problem in their own words and showed that groups were reflecting on the
processes they had used when solving the task.
The second question (As your group worked on the problem what did your
group do?) related to how the groups had monitored their problem solving. Ten
groups (66%) stated that they had to redo their step(s) if they did something
wrong (Statement 11). Fortunato et al. (1991) stated that metacognition is the
awareness and reflection of cognitive activities engaged in during problem
solving. This metacognitive activity showed students’ awareness of their task
performance as they monitored their problem solving and had to redo steps
(Schraw, 2001).
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The third question (After your group finished working on the problem
what did your group do?) contained five statements regarding how the groups had
evaluated their problem solving. Seven groups (47%) indicated that they thought
of a different way to solve the problem (Statement 16). This was evident in the
focus group interview where students discussed how they could vote on the
different cities.
The final question (Did your group use any of these ways of working?)
was designed to prompt students to consider the strategies they had used to solve
the problem. Six groups (43%) stated that they did write down important
information (Statement 21). This was evident in the groups’ use of the group
diaries that helped scaffold the team- and the task-work of the group. All 16
groups used the diaries to plan, monitor, and evaluate strategies for both the
problem-solving task and their team-work.
The group metacognitive questionnaires, completed by the groups at the
end of the study, helped the groups reflect on their problem solving. These
reflections indicated that the groups had adopted strategies specific to the
problem-solving task as they tried to put the problem into their own words, redo
their step(s) if they did something wrong, wrote down important information, and
thought of a different way to solve the problem.
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4.3.2 Theme 10
The groups used metacognitive scaffolds to plan, monitor, and evaluate their task-
and team- work.
Theme 10 was derived from an analysis based on the three metacognitive
strategies of planning, monitoring, and evaluating. These strategies were used as a
basic framework with which to begin the metacognitive analysis of the audio
transcripts and the metacognitive checklists. The transcriptions and metacognitive
checklists were also coded according to Schraw’s (2001) regulatory checklist for
improving students’ thinking about their learning processes (see Appendix C, p.
263). Schraw’s checklist included questions that focused on the planning,
monitoring, and evaluating strategies.
The coding of the transcripts found that the groups were involved in
planning, monitoring, and evaluating discussions as they completed the group
metacognitive checklists in their group diaries. There were 24 planning, 23
monitoring, and 23 evaluating episodes coded from the 16 groups. For example,
planning from Group L occurred when the group was working out their plan to
find the best city in Australia:
Student1: Our goal is to rank cities
Student 2: Yes we've got ranking cities
Student1: Ok what's our plan?
Student 2: What's our plan?
135
Student 3: Rank the top cities in Australia
Student 1: Ask questions
Student 2: What else?
Student 3: Encourage
Student 1: Rank the 8 cities
Students also monitored and evaluated their progress with the task and
their team work. An example of monitoring occurred with Group M occurred
during the second session when they were completing the monitoring sheet in
their group diary:
Student 1: Are we following the group plan? Yes. Do we need to make
changes?
Student 2: I don't think we need to make changes
An example of evaluation occurred from Group D when the group was
completing the evaluation sheet in their group diary. During the final computer
session Group D discussed what their group did well and what they could
improve:
Student 1: What worked? What do you think what worked or you know
still do we have to do?
136
Student 2: What didn’t work?
Student 3: No nothing we just had fun
Student 1: What do we do?
Student 2: Finish work quicker. Well we could all finish work quicker
couldn’t we?
The literature, reviewed in Chapter 2, suggested that metacognition is a
linear process where planning is the first group metacognitive process and
evaluating is the last. The coding of the transcripts, using Schraw’s (2001)
checklist, shows that the group metacognitive process was not necessarily linear;
the groups were involved in a constant iterative process of planning, monitoring,
and evaluating within each of the sessions throughout the study (see Table 4.9 &
Table 4.10).
The groups combined the strategies of planning, monitoring, and
evaluating within each computer session in order to facilitate their group work.
Table 4.9 shows Group E’s metacognitive processes during the first computer
session and Table 4.10 shows Group C’s metacognitive processes during the final
computer session.
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Table 4.9
Group Metacognition Coding for Group C
Coded Checklist Text
Monitoring 1. Do I have a clear understanding of what I am doing?
Student 1: You're the encourager
which means that you have this and
I'm the coordinator
Student 2: Which also means I
encourage people
Planning
1. What is the nature of the task? 3. What kind of information and strategies will I need?
Student 1: We're just going to go and
try Knowledge Forum
Student 2: We could put how we're
going to reply to someone
Student 3: That's great
Planning
1. What is the nature of the task?
Student 1: We can write about that
Evaluation
1. Have I reached my goal? 2. What worked?
Student 1: What's 1 Melbourne, Sydney Student 2: Darwin I like Darwin Student 3: I like Brisbane Student 2: Yeah Student 1: We had fun today
138
Table 4.10
Group Metacognition Coding for Group E
Coded Checklist Text
Planning
1. What is the nature of the task?
Student 1: Right, OK so we haven't started filling that in yet which we're about to do
Evaluating 3. Am I reaching my goals?
Student 1: We got a fair bit done on our one actually
Planning
2. What is my goal? 3. What kind of information and strategies will I need?
Student 1: And we have for the goal finding the top cities in Australia Student 2: The top do we have to find the top eight and the best of the top eight? Student 1: We have a plan We have a plan Student 2: Our plan is to get information to use to find the top eight which is the best Student 1: And also And also use information to find the best of them all
Monitoring
1. Do I have a clear understanding of what I am doing? 2. Does the task make sense?
Student1: We all have to agree on this one alright Student 1: This is the task what are we going to do?
Planning
3. What kind of information and strategies will I need?
Student 1: Get group back to work Student 2: Ask questions Student 1: Share information Student 2: Yeah share information
Evaluating 2. What worked?
Student 1: We are doing that, that's what we are doing well
139
The group metacognitive checklists were completed by the groups at the
beginning of each computer session. The group checklist included questions
based on Schraw’s (2001) regulatory checklist (see Appendix C, p.263).
The initial planning checklist included the following questions:
What do we know about the problem?
What is the goal?
What is our plan to solve the problem and reach the goal?
The analysis of data revealed that these three questions successfully
scaffolded the groups’ planning of their model-building activity in this study. For
example, Group N indicated that they needed to rate all the cities in Australia
while all the other groups indicated that they knew they had to rank the cities in
Australia. When stating the goal, Group B responded that their goal was to learn
and have fun, while the other groups’ responses indicated the goal was to either
find the top city or the best city in Australia.
When stating what their plan was to solve the problem and reach the goal,
the groups provided a variety of responses. Group C stated that they would draw
a chart, Group E stated they would get information, use to find top eight and
which is best, while Group M stated they would use computer. The remaining
thirteen groups listed the categories they would use to rank the cities (see Table
4.11).
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Table 4.11
Group Plan to Solve the Problem and Reach the Goal
A Clean environment, nice parks, good education
B We like to go skateboarding and chilling out. Laser skirmish (sic)
C Draw a chart part
D Theme parks, sports, public health system, infrastructure (sic).
E Get information, use to find top 8, which is best
F Health, neighbours, pets, education, community,
shopping, beauty, weather, parks, government, food, water.
G Shopping, movies, theme parks, food court, park, sports
H The population, environment, wild life, food, theme parks, buildings,
education
I food, movies
J Adventure, parks, shops.
K Sport, trees, shop, rivers, school, buildings, food, culture, money, weather
L sports
M Use computer
N Theme parks, transport, safety, lifestyle, shopping, real estate, education,
population, hospitals
O Wild life, buildings, food and drink, and population
P Sport Art Showers gardens, trees, water, food.
The monitoring checklist included the following questions that focused on
monitoring and evaluating:
Are we following the group plan?
Do we need to make changes?
141
What are two things our group is doing well and 1 thing that needs
to improve?
The analysis of data indicated that these three questions successfully
scaffolded monitoring actions by the groups as they were engaged in the process
of co-constructing their ranking models. All groups responded that they were
following the group plan and did not need to make any changes to the plan.
When asked to nominate two things the group was doing well 30
responses were given by the 16 groups, including 15 task-related responses and
15 team-related responses. Five groups included the task-related behaviour of
working together; the remaining 11 groups included a variety of task behaviours.
For example:
Share information
Figuring
Follow ideas
Efert (sic)
Four groups included the team-related behaviour of listening to each other; the
remaining 12 groups included a variety of team behaviours. For example:
Cooperating
Encouraging
Being patient
Keeping things calm
142
When the 16 groups were asked what things their group needed to
improve, one group responded there was nothing they needed to improve; one
group stated that they needed to “reech (sic) to the top”. Three groups responded
with three task- related behaviours and 11 groups responded with a variety of
team-related behaviours. The task-related behaviours included:
Talk about the work
Check group understanding
Contribute ideas
The 11 team-related responses included:
Communicating
Be positive
Be nice
Include everyone
The final evaluation checklist asked groups to comment on the following topics:
Have we reached our goal?
What worked?
What didn’t work?
What could we do differently next time?
The analysis of data revealed that these four questions scaffolded the
groups’ evaluation of their task- and team-work during the final computer session.
All groups responded that they had reached the group goal nominated in their
143
planning checklist. A variety of positive responses were given to the question
what worked including: eight groups responding with comments such as
everything or most things worked, five groups responding with task-related
comments such as the CD or Knowledge Forum, and three groups responding
with team-related comments such as cooperating or communicating.
When responding to the question what didn’t work in their view, the 11
groups stated nothing or left the question blank. Five groups included a variety of
comments including:
Because people were better at something (sic) so others didn't do
anything
Listening
One group member kept on hitting keys
Finally, when the 16 groups responded to the question what could we do
differently next time, ten groups responded with either nothing or left the question
blank, five groups responded with comments relating specifically to their own
group such as try to be nice about their decisions, listen, and not talk that much.
One group responded with a comment on the organisation of the groups: choose
different groups and mix girls and boys.
4.3.3 Metacognitive themes summary
The metacognitive checklists and questionnaires used in this study
incorporated the metacognitive strategies of planning, monitoring, and evaluating.
144
The groups applied the metacognitive strategies to constantly improve on how
their group was completing the problem-solving task and working together as a
team. The metacognitive strategies were adopted by the groups in order to work
effectively together.
The group metacognitive questionnaires, completed by the groups at the
end of the study, helped the groups reflect on their problem solving. These
reflections indicated that the groups had used the three main metacognitive
strategies of planning, monitoring, and evaluating during their co-construction of
the mathematical ranking model.
The analysis of the audio transcripts showed that the groups were involved
in discussing their team- and task-work, as they completed the metacognitive
checklists in their group diaries. The results also showed that the metacognitive
process was not always linear as groups were involved in planning, monitoring,
and evaluating throughout the study.
4.4 Focus-group interview
A focus-group interview involving ten students was conducted in the
concluding phase of the study. The interview focused on eliciting the students’
thoughts on the problem-solving task used in the study. Students were encouraged
to give their opinions on what they thought worked well and what did not work
well.
145
When students were asked if there was anything they would change about
the task, the following discussion took place:
Student 1: I don’t think it was good how we took from every group cause
we thought Melbourne should have won but Brisbane won. It’s
probably because everyone lives in Brisbane made Brisbane
best city.
Student 2: By movie theatres we ranked by most movie theatres
Student 1: I don’t like it how they make Brisbane -there’s lots of others
Student 3: Better cities
Student 2: Good cities
Student 4: Cities bigger than Brisbane
Student 3: The reason I like Adelaide it’s peaceful. Darwin is good.
Perth…
Student 2: Same here
Student 1: I don’t really agree with that
Student 3: And Melbourne I think should have won because it’s got lots of
entertainment and sport.
This discussion concerning the task showed that the students involved in
the focus-group interview were not satisfied with the solution to the city ranking
problem. The students discussed the task amongst themselves and concluded that
other cities could also be ranked number one depending on the categories used to
146
rank the city. Lesh and Lamon (1992) stated that the construction of alternative
mathematical models is acceptable as the goal for students and students should be
involved in judging the usefulness of their model. The discussion from the
interview showed that students were judging their model and suggesting
alternatives.
During the focus-group interview, students were also asked if there was
anything they would change about the group diary. The students indicated that,
apart from a few minor changes such as having pictures included in the diary,
they enjoyed using them. One student commented:
Well, I don’t think we would change anything cause they’re pretty
good the way they are
Students indicated that they had fun and enjoyed the group task. When
asked if there was anything they learnt during the activity that they could take to
another group the following comment was made:
I will take the different strategies of working together
4.5 Summary and conclusion
This chapter focused on the first cycle of this study involving within-
group metacognitive scaffolds during mathematical problem solving for groups
working around a computer. The analysis of data in this cycle identified three
categories of themes that mirrored the three main components of successful
147
problem solving and learning that were presented in the conceptual framework in
Chapter 2: (1) organisational factors, (2) cognitive factors, and (3) metacognitive
factors.
Results from Cycle 1 of this study have highlighted that effective group
problem solving requires groups to think about organisational, cognitive, and
metacognitive factors. These factors influence how groups work together and
develop a shared understanding. This shared understanding is facilitated by
groups forming an external representation of how they want their group to
perform as a team and solve the problem-solving task.
The study highlighted that while organisational and cognitive factors are
important to help groups develop and form a shared understanding, metacognitive
factors are also important for groups to reflect on and improve their problem
solving and their group work.
4.6 Implications for Cycle 2
A design research methodology was adopted for this study as it allows for
multiple cycles of design, experiment, and analysis (Shavelson et al., 2003). The
design research methodology seeks to find solutions from the analysis of data and
identifies new goals for each successive iteration (Bereiter, 2002). The cyclical
nature of the design research methodology allowed for changes to be made to the
second cycle based on the results from the first cycle of the study (Collins et al.,
2004; Woodruff & Nirula, 2005).
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The findings from Cycle 1 showed that group members need to be aware
of successful group roles and skills, including conflict management skills. They
need to choose skills and roles relevant to their own group in order to build a
shared understanding of how their group is performing. The groups also need to
apply metacognitive strategies to constantly improve how their group is
completing the task and working together as a team.
A number of aspects from this cycle helped inform Cycle 2 of the study
(see Chapter 5). First, specific group roles and skills that students from this cycle
highlighted as being necessary for effective groups were placed on posters and
displayed for the second cycle of the study. Conflict management strategies were
also displayed on a poster in the second cycle as students identified arguments
and fighting as the aspect that they liked least about working in a group.
Second, the group diaries were included in Cycle 2 as all students
indicated that they had enjoyed using them. The diaries were used to organise the
group roles and skills in order to form a shared understanding of both the team
work and the task work.
Third, the metacognitive checklists successfully scaffolded groups
planning, monitoring, and evaluating of their task- and team-work in the first
cycle. The scaffolds were included in the group diaries for the second cycle for
groups to reflect on how their group was performing, using the planning,
monitoring, and evaluating strategies.
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Fourth, a group cohesiveness questionnaire (see Appendix G, p. 267) was
included in Cycle 2 in order to ascertain if the group cohesiveness observed in the
first cycle was also perceived by the students in Cycle 2. The questionnaire
focused on students’ perceptions of their group and group members.
Finally, the group metacognition study was extended in Cycle 2 to include
between-group metacognition for groups working in online teams. In order to
extend the emerging theory on within- and between-group metacognition, six
groups of students in the second cycle were chosen to form two online teams. The
mathematical ranking model-eliciting activity was also changed for the online
teams as some students indicated in the focus group interview that they were not
satisfied with the combined solution to the city ranking problem. Each online
team in Cycle 2 was asked to collaboratively create a combined mathematical
ranking model in order to find the best city in Australia.
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151
CHAPTER 5: RESULTS FROM CYCLE 2
Within- and between-group metacognition
The aim of this study was to develop a conceptual model to inform the use
of scaffolds to facilitate group metacognition during mathematical problem
solving in CSCL environments. This chapter presents the results of Cycle 2 which
focused on both within- and between-group metacognition for groups working
around the computer and working with other groups in the Knowledge Forum®
CSCL environment (Research Objectives 1 and 2). Three groups from each of the
two classes involved in the study formed two online teams. Each online team
included at least one group from each class (see Table 3.3). Data sources (see
Table 3.4) included classroom artefacts (see Section 3.2.3); including the group
diaries, checklists, metacognitive questionnaires, and individual questionnaires;
and a focus group interview (see Section 3.2.2).
The three categories of themes (organisational, cognitive, and
metacognitive) derived from the analysis of data from the first cycle of this study
were replicated in the second cycle. The results of the analysis of the data from
this second cycle also highlighted five themes not revealed during the first cycle.
There were four new organisational themes relating to the online environment and
one new cognitive theme relating to the group cohesiveness questionnaire used in
this cycle.
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5.1 Organisational themes
Four new organisational themes, relating specifically to the online
environment, were derived from the analysis of the data in this second cycle:
1. The groups posted a higher number of task-related than team-related
messages.
2. There were a higher proportion of team-related messages demonstrated
with the online teams than with the face-to-face groups in the first cycle.
3. The groups posted effective task- and team-related messages in order to
work efficiently together.
4. The online teams went through a three stage development process of
forming, performing, and adjourning rather than the five stages proposed
by Tuckman’s model.
Two of the organisational themes derived from the analysis of the data in
the first cycle of this study were replicated in this second cycle:
5. Students identified five aspects important for group work: having fun,
working together, listening, helping, and sharing ideas.
6. Students identified disagreements and conflicts as aspects they liked least
about working in a group.
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5.1.1 Theme 1
The groups posted a higher number of task-related than team-related messages.
Theme 1 was derived from the analysis based on Bales’ Interactive
Process Analysis (IPA) (Bales, 1970; Bales & Cohen, 1979; Miller, 1991) of the
Knowledge Forum® notes. The Knowledge Forum® notes were coded according
to the task- and team-domains from Bale’s IPA method. There were 12 team-
related notes, 16 task-related notes and 15 notes that contained messages relating
to both the team and the task.
The majority of team-related notes were posted as greetings when groups
formed their online Knowledge Forum® teams. For example, Group E posted the
following team-related note:
Hi where (sic) Student 1 and Student 2 (team)
The online groups sent the majority of the task-related notes whilst in the
process of co-constructing the ranking system with the other two groups in their
team. For example, one of Group B’s notes to their online team was:
We think in the best city the Government should NOT let old ladies water
their gardens whenever they want!!! We also want a large range of sports
an AFL stadium etc etc etc...
Also lots of different cultures like Aboriginal, Chinese etc etc etc...
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The Knowledge Forum® notes that related to both the team and the task
were mainly sent while the teams were engaged in compiling their categories for
their team ranking model. The following note was sent from Group A:
Cant (sic) wait to work with you [team]
We will do two categories each [task]
The 43 Knowledge Forum® notes were further coded into 60 messages.
There could be more than one message for each note. For example, Group A sent
the following note that contained two messages, one that was task-related and one
that was team-related.
We can’t wait to work wit u 2 (sic) (team)
U (sic) have good categories, but maybe we need more of them (task)
As can be seen in Table 5.1, the total domain frequency shows that the
groups had a slightly higher number of task-related messages (57%) than team-
related messages (43%).
Table 5.1
IPA Domain Frequency
Domains Number of KF notes Percentage of total 1. Task-related 34 57%
2. Team-related 26 43%
Total 60 100%
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The coding of the Knowledge Forum® notes showed all groups together
posted a higher number of task-related than team-related messages to the
Knowledge Forum® database. As in the first cycle, the high number of task-
related knowledge building behaviours could be attributed to the nature of the task
in which the students were engaged (Dishon & O’Leary, 1984; Jonassen & Kwon,
2001).
5.1.2 Theme 2
There were a higher proportion of team-related messages demonstrated with the
online teams than with the face-to-face groups in the first cycle.
Theme 2 was derived from the analysis of the Knowledge Forum® notes
based on Bales’ IPA compared to the IPA analysis of the transcripts of the face-
to-face groups working together from Cycle 1. Table 5.2 shows the task- and
team-related domain count from both cycles.
Table 5.2 IPA Domain Frequency for Both Cycles
Domains Face-to-face (Cycle 1)
Knowledge Forum (Cycle 2)
1. Task-related 77.8% 57%
2. Team-related 22.2% 43%
Total 100% 100%
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The results from this study showed that the groups working face-to-face in
the first cycle engaged in a higher percentage of task-related behaviours, or acts,
(77.8%) than the online teams in the second cycle (57%). This is counter to
Jonassen and Kwon (2001) who stated that students working with computer
conferencing are more task-directed compared to students working face-to-face.
The higher percentage of team-related (43%) messages in Cycle 2 than the
team-related (22.2%) behaviours observed with the face-to-face groups in Cycle 1
were mainly due to groups getting to know each other. Palloff and Pratt (2005)
stated that when virtual teams are formed in work environments, it is important to
spend time to get to know one another before group work is attempted. This
aspect of team forming was reflected in the Knowledge Forum® notes related to
the team. As groups formed their online Knowledge Forum® team, each group
posted their welcome notes. For example, Group B posted the following note to
their online team:
Were (sic) Group B! What grade are you in? We are in year 5!
By the way were (sic) Student 1, Student 2, Student 3! What are your
hobbies?? Ours are AFL & other sport!
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5.1.3 Theme 3
The groups posted effective task- and team-related messages in order to work
efficiently together.
Theme 3 was also derived from the analysis based on Bales’ Interactive
Process Analysis (IPA). With the IPA method, the task and team domains are
divided into twelve categories. Table 5.3 shows that the IPA categories with the
higher frequency counts are the team-related category of seems friendly (40%)
and the task-related category of gives information (35%). The groups had no
messages in the negative team-related categories of disagrees, seems unfriendly,
and shows tension.
An example of gives information from Cycle 2 of this study can be seen in
this note from Group C when they where posting their ranking model for their
online team.
Melbourne is our best city because it had great adventures.
An example of seems friendly can be seen in the welcome note posted by
Group C to their online team:
Hi were (sic) Group C. We will be happy to be working with you on
Monday.
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Table 5.3
IPA Category Frequency
Categories Number of messages Percentage of total
1. Seems friendly 24 40%
2. Dramatises 2 3%
3. Agrees 0 0%
4. Gives suggestion 7 12%
5. Gives opinion 3 5%
6. Gives information 21 35%
7. Asks for information 2 3%
8. Asks for opinion 1 2%
9. Asks for suggestion 0 0%
10. Disagrees 0 0%
11. Shows tension 0 0%
12. Seems unfriendly 0 0%
Total 60 100%
The results from the category count showed that group messages focused
mainly on either the team-related behaviour of seems friendly (40%) or the task-
related behaviour of gives information (35%). The results from the category count
in Cycle 1 also showed that group behaviours focused mainly on the task-related
159
behaviour of gives information (29.8%) as group members clarified or confirmed
what the task involved.
5.1.4 Theme 4
The online teams went through a three stage development process of forming,
performing, and adjourning rather than the five stages proposed by Tuckman’s
model.
Theme 4 was derived from an analysis of the Knowledge Forum® notes
that were coded using constructs derived from Tuckman’s model of group
development (Tuckman & Jensen, 1977). Tuckman and Jensen suggested that
groups proceed through five linear stages of development, forming, storming,
norming, performing, and adjourning.
The analysis of data from Cycle 1 found that the groups went through a
development process in a much less linear and more convoluted than that
proposed by Tuckman and Jensen’s (1977) model. The analysis of the Knowledge
Forum® notes from this cycle also found that while the online teams posted
effective task- and team-related messages, they did not progress through all of the
five stages of team development.
The online teams engaged in the forming stage as each group sent notes
introducing themselves and giving information about the task. This team
formation phase has been identified by Tuckman and Jensen (1977) as an
important step for effective development. As groups formed their online
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Knowledge Forum® team, each group posted their welcome notes and gave
information about the categories they were going to use. For example, Group C
posted the following note to their online team:
Hi were (sic) Group C. We will be happy to be working with you on
Monday. For our 2 categories are Movies & Adventure.
According to Tuckman and Jensen (1977), during the forming stage,
conflict is generally avoided as members get to know one another. There was no
conflict observed from the Knowledge Forum® notes. This differs from Cycle 1
where eight of the sixteen groups in the initial computer session engaged in
conflict.
The analysis of the Knowledge Forum® notes also suggests that the online
teams did not engage in the storming phase of group development suggested by
Tuckman and Jensen (1977). By contrast, nine of the sixteen face-to-face groups
engaged in “storming” types of behaviour throughout the first cycle. Palloff and
Pratt (2005) stated that conflict is critical to the development of the group.
However, the finding in this cycle of the study is consistent with that of Johnson,
Suriya, Won Yoon, Berrett and La Fleur (2002) who found that the rapid
movement between the stages with an online group resulted in no evidence of the
storming stage.
The third stage of group development, norming, predominantly follows
the storming stage. The groups did not post notes with norming messages.
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However, the groups posted friendly messages to their online teams. The groups
completed their group checklists regarding the team and task skills they wanted to
focus on during the following computer session. The groups also used these skills
on the Knowledge Forum® database. For example, Group B stated they would be
positive and sent the following note to their online team:
Hi!!!
This is Student 1, Student 2, & Student 3! We are Group B! We are
looking forward to helping you guys!
Tuckman and Jensen’s (1977) model also includes a fourth development
stage, performing, which involves members working interdependently. The
groups working face-to-face incorporated effective team- and task-related
behaviours. This was also evident with the online teams. For example, Group A
received this note incorporating team-and task-related messages.
Yo we totally cant (sic) wait to talk to u more
Do you need help with the websites
While some groups may go through general stages, it does not mean that
all groups do (Benjamin et al., 1997). There were three stages common to both
cycles of the study; the beginning (forming stage), which refers to the bringing
together of the group members to the groups and the groups to the online teams;
the performance (performing stage), which refers to the management of both the
162
task- and team-skills in order to perform successfully; and the ending (adjourning
stage), which refers to how the task- and team-work was finalised.
5.1.5 Theme 5
Students identified six aspects important for group work: working with friends,
having fun, working together, listening, helping, and sharing ideas.
Theme 5 was derived from an analysis of the individual questionnaires.
The initial questionnaires focused on eliciting individual student’s thoughts on
group work prior to commencing the study. The final questionnaires repeated
questions asked in the initial questionnaire in order to ascertain any changes in
students’ perceptions about group work.
The questionnaires were coded according to a constant comparison
method of data analysis (Charmaz, 2000; Denzin & Lincoln, 1998). Responses
from the initial and final questionnaire about group work were compared. The
responses from this cycle were also compared with responses from students in the
first cycle of this study.
The third question on the initial questionnaire asked students what they
liked about working in a group or a team. Table 5.4 shows the main category that
emerged was friends (43%). The categories identified in Cycle 1 of the study
included working together (25%), helping (20%), sharing ideas (15%) and having
fun (10%).
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Table 5.4
Responses to Question Three on Initial Individual Questionnaire
Question Responses For example
What do you like
about working in a
group?
Friends (43%) I like to be with my
friends and working
togethe (sic) (Student 1,
Group A).
Other comments (57%) We can help other people
when there (sic) confused
(Student 3, Group A).
I like evry (sic) ones (sic)
ideas and finding out the
best one out of evry (sic)
one (Student 1, Group F).
The first question on the final questionnaire asked students what they liked
about the learning groups. Fun was the major focus of the responses from students
(50%) from the second cycle who commented that they had fun learning in their
groups. Fun (14%) was also focused on by students on the final questionnaire in
the first cycle. The importance of being able to help and share ideas was identified
in both cycles.
The third question on the final questionnaire asked students what they felt
was easier to understand or learn in their group. All students (100%) indicated
164
that everything was easier to understand in the group. One student responded that
discussing the work was easier within the group. Students in the first cycle had
made a variety of comments including everything was easier to understand. They
also stated that “working together as a group was easier to learn within their
group”.
The final question asked students to give advice to someone who has
discovered that they will be working in a group. Have fun (29%) was the advice
given by students in this second cycle of the study. Responses from students in
Cycle 1 included have fun (17%), listen (12%), work together (12%), and share
ideas (7%). One student (7%) in Cycle 2 left this question blank. Some students
(64%) included advice on working together. Their comments included:
To work hard and enjoy (Student 2, Group D).
Listen to other people and be kind (Student 1, Group D).
They will do well (Student 3, Group C).
5.1.6 Theme 6
Students identified disagreements and conflicts as aspects they liked least about
working in a group.
Theme 6 was also derived from an analysis of the individual
questionnaires. The questionnaires related to students previous experiences with
group work and what they had learnt about group work during the study.
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The fourth question on the initial questionnaire asked students what they
did not like about working in groups. As can be seen from Table 5.5 students
(57%) commented on the group members not agreeing. The students in Cycle 1
(55%) had indicated that disagreements and conflicts were the things they liked
least about working in a group. Students from Cycle 2 (43%) also made other
general comments regarding what they did not like about working in groups.
Table 5.5
Responses to Question Four on Initial Individual Questionnaire
Question Responses For example
What don’t you like
about working in a
group?
Not agreeing (57%) Sometimes we don’t always
agree with each other
(Student 3, Group A).
Sometomes (sic) it’s a
chaleng (sic) to agry (sic)
(Student 1, Group F).
Other comments (43%) Some people take to (sic)
long! (Student 1, Group F).
When people don’t let you
help (Student 1, Group A).
The second question on the final questionnaire asked students to indicate
what they did not like about team work. Students (64%) indicated that there was
nothing they did not like about the team work. This differs to the responses for
166
this question from the first cycle where some students (29%) made comments
about disagreements and conflicts. In the second cycle, two students (14%) also
left the question blank and three students (21%) commented negatively, with only
one student commenting that sometimes the group did not agree:
Getting upset with the person thats (sic) not doing what were told
to (Student 2, Group E).
The students indicated in Cycle 1 that they disliked disagreements and
conflicts that occurred within groups. Students in Cycle 2 also indicated on the
initial questionnaire that they disliked not agreeing when they work in groups.
This response was only given by one student in the second cycle on the final
questionnaire.
5.1.7 Organisational themes summary
The findings from this study showed that the Knowledge Forum®
database functioned as a shared knowledge base and the mathematical ranking
models provided a basis for discussion amongst the groups. The analysis of the
Knowledge Forum® notes showed the groups engaged in a higher number of
task-related than team-related behaviours. The task-related messages of gives
information and the team-related messages of seems friendly were the most
prevalent messages posted.
167
As in the first cycle, the high number of task-related knowledge building
behaviours could be attributed to the open-ended mathematical ranking activity in
which the students were engaged (Dishon & O’Leary, 1984; Jonassen & Kwon,
2001). The online teams went through a three stage development process of
orientation to the task and to the group, management of both task- and team-skills,
and finalisation of the task and the team work. The advice that students gave in
both cycles, on how to work in a group, included have fun, listen, work together,
and share ideas.
5.2 Cognitive themes
Three cognitive themes were derived from the analysis of the data. Two of
the themes in this second cycle were also identified in the analysis of the data in
the first cycle of this study:
7. The groups developed a shared knowledge of the task and how they
wanted to perform as a team.
8. The groups developed their own task- and team-skills to focus on.
The third theme relates specifically to the group cohesiveness
questionnaires completed at the end of Cycle 2:
9. Group members held positive attitudes towards their groups and perceived
that the groups worked well together.
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5.2.1 Theme 7
The groups developed a shared knowledge of the task and how they wanted to
perform as a team.
Theme 7 was derived from the analysis of the group diaries. The groups
were asked to use the group diaries to organise their task- and team-skills and to
delegate group roles. The group roles and the task- and team-skills adopted and
utilised by the groups were initially identified from the group roles used in Cycle
1. Further team- and task-skills then were identified using a constant comparison
method of analysis.
The group roles were chosen by the groups from the team role poster (see
Appendix X, p. 302). Team roles included encourager (encourage others to talk
and encourage others to listen); manager (be positive, manage conflict, and share
positive feelings); checker (check for agreement, manage conflict, and keep things
calm). Task roles included keyboarder (give ideas, repeat ideas, and respond to
ideas); coordinator (seek ideas and search for information); and recorder (check
for understanding, ask questions, and talk about the work).
Only the three groups from the Year 4 class included the group roles in
their group diary. As shown in Table 5.6, the main group roles chosen by these
three groups from the group roles poster were the task roles of
keyboarder/computer (100%) and recorder/MP3 (67%). One group chose the
team role of encourager. The three groups from the Year 4 class also chose the
task role of writer (100%), a role not included in the group diary or team poster.
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Table 5.6
Frequency of Group Roles Chosen
Writer Recorder/MP3 Keyboarder/computer Encourager
3 2 3 1
The groups from the Year 4-7 did not include the group roles in the group
diary but they still changed task roles each week, so one student was at the
keyboard and one student was recorder. All the groups from the Year 4-7 class
had participated in the first cycle of this study and had clearly developed a shared
understanding of the task roles without the need for the role scaffolds included in
the diary. Because the Year 4-7 students had, in Cycle 1, co-constructed a shared
understanding of what the group roles entailed, the scaffolding provided by the
group diaries had become redundant, a finding that is consistent with the corpus
of knowledge about cognitive scaffolding (e.g., Gourgey, 2001; Hartman, 2001;
Vygotsky, 1978).
Groups were asked to choose team- and task-skills from the poster of
group skills derived from Cycle 1 (see Appendix X, p. 302). Task-skills included
share ideas (give ideas, repeat ideas, and respond to ideas); share information
(seek ideas and search for new information); and check understanding (ask
questions and talk about the work). Team-skills included encourage (encourage
others to talk and encourage others to listen); be positive (say thank you, use eye
170
contact, and say positive things); and check for agreement (manage conflict and
keep things calm).
The groups chose sixteen team-skills and nine task-skills. As shown in
Table 5.7, the most common task-skills chosen by the groups from the task-skills
poster were work together, three groups (50%) chose this skill to focus on, and
two groups (33%) chose share ideas and share information. One group included
draw a picture or make a list from the problem-solving poster.
Table 5.7
Frequency of Task Skills Chosen
Share ideas Share information
Draw a picture or make a list
Work together
2 2 1 3
As shown in Table 5.8, four groups (67%) chose the team-skill of
encourage, 5 groups (83%) chose be positive, and all six groups (100%) chose
check for agreement, as the team-skills they would focus on in the following
computer sessions.
Table 5.8
Frequency of Team Skills Chosen
Encourage Be positive Check for agreement
4 5 6
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The analysis of the diaries showed that the group diaries helped the groups
formulate a shared understanding of both their team-work and their task-work.
The diaries provided a space for groups to represent their shared understanding
and reflect on how they wanted their group to perform. This result is consistent
with Blakey and Spence (1990) who stated that diaries help students to monitor
and reflect upon their learning performance.
While the results from the second cycle are similar to the results of the
analysis of the group diaries from the first cycle, there were some important
differences. There were more task-roles than team-roles chosen and the groups
from the Year 4-7 allocated their group roles without the use of the scaffolds
included in the diaries. The Year 4-7 groups had developed an understanding of
what the group roles entailed and mainly used the task roles of recorder and
keyboarder. The finding that the groups also decided to use group skills not listed
in the group diary replicates what was found in Cycle 1. This finding shows that
groups were incorporating skills relevant to the needs of their group.
5.2.2 Theme 8
The groups developed and focused on their own task- and team-skills.
Theme 8 was also derived from an analysis of the group diaries. The
analysis was based on the task- and team-skills identified in Cycle 1. These skills
were included on the group skills poster used in Cycle 2.
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The results showed that groups included skills not identified in the posters,
including the task-skill of complete task and the team-skills of work together and
try our best. Even though work together was listed on the group skills poster as a
task skill three groups (50%) included work together as a team-skill. This
highlighted the importance the groups placed on this skill.
A number of researchers (e.g., Benjamin et al., 1997; Cathcart et al., 1996)
have stated that for groups to be effective, students should be encouraged to
incorporate appropriate group skills. The results show that groups were
nominating skills relevant to the needs of their group. This finding was also
evident in the first cycle of this study where seven groups nominated skills not
included in the list of group skills in the group diary.
5.2.3 Theme 9
Group members held positive attitudes towards their groups and perceived that
the groups worked well together
Theme 9 was derived from the analysis of the answers from the group
cohesiveness questionnaires. Eleven students were also asked to complete the
questionnaires during the final computer session. The questionnaire was based on
Gillies (2003) study on group cohesiveness. The questionnaire was added to this
cycle of the study as there was an observed solidarity built amongst the group
members in the first cycle. In order to establish if students also perceived if they
173
were cohesive, the group members were asked to complete the questionnaire in
this second cycle. This questionnaire focused on students’ perceptions of their
group and other group members.
Group cohesiveness occurs when group members begin to identify with
the group as they solve the problem (Gillies, 2003; Wheelan, 2005). As shown in
Table 5.9 the majority of students indicated that they were glad they belonged to
the group and they thought that the group worked well together. All but one
student thought the group was important. However, all students agreed or strongly
agreed that their group had worked well together.
Two positive results were identified from the questionnaires regarding the
students’ thoughts about group work. First, group members held positive attitudes
towards their groups. Second, group members perceived that the groups worked
well together. This group cohesion was developed by groups in both cycles of the
study as the group members decided how they would work together and
incorporated group behaviours necessary for their group to perform productively.
The results from the group cohesiveness questionnaire showed that group
members felt comfortable with their groups, were glad they belonged to their
group, and had developed an identity as being part of a group. This finding is
consistent with Gillies (2003) who found that cohesive groups develop when
group members begin to identify with the group as they solve the problem. All
group members indicated that they thought their group had worked well together.
This positive attitude that group members had towards each other and their group
174
was important for their group effectiveness and group cohesiveness (cf. Dickson
& McIntyre, 1997).
Table 5.9
Responses to Group Cohesiveness Questionnaire
Strongly Agree Agree Neutral Disagree
Strongly Disagree
a. I'm glad I belong to this
group 6 4 1
b. I feel held back by this
group 2 6 3
c. I am an important part of
this group 4 5 2
d. I don't fit in with other
kids in this group 1 6 4
e. I feel strongly tied to this
group 3 5 3
f. I don't think the group is
that important 1 5 5
g. I think this group worked
well together 9 2
h. I don't feel comfortable
with the other kids in this
group 1 4 6
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5.2.4 Cognitive themes summary
The group diary (see Appendix L, p. 284) scaffolded the construction of a
shared understanding in both classrooms about what relevant group skills, group
roles, conflict management skills, and problem-solving strategies needed to be
incorporated. The group diary enabled groups to form a shared understanding of
both their team-work and their task-work. The groups used the diaries to organise
the group roles, skills, and strategies they felt were important to their group
performing effectively.
The results from the group cohesiveness questionnaire showed that the
group members held a positive attitude towards their group work and the other
members of their group. Cohesive teams were developed as groups formed a
shared understanding of what team and task skills they needed to incorporate into
their group. All groups in this cycle also formed cohesive online teams with two
other groups using the Knowledge Forum® database.
5.3 Metacognitive themes
Two metacognitive themes were derived from the analysis of the data.
These two themes were also identified in the analysis of the data in the first cycle
of this study.
10. The groups reflected on the strategies specific to the problem-solving task.
11. The groups used metacognitive scaffolds to plan, monitor, and evaluate
their task- and team- work.
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5.3.1 Theme 10
The groups reflected on the strategies specific to the problem-solving task.
Theme 10 was derived from the analysis of the answers from the group
metacognitive questionnaire that the groups were asked to complete at the end of
the study (see Appendix B, p. 262). The questionnaire asked students to respond
to 21 statements which described metacognitive behaviour relating to the task that
the groups had engaged in during problem solving. The responses to this
questionnaire are shown in Table 5.10.
The responses to the metacognitive questionnaire highlight the specific
strategies that groups adopted for the problem-solving task. This first question
(Before your group began to solve the problem what did your group do?)
contained six statements regarding what the groups had done prior to solving the
problem (see Table 5.10). Four of the six groups indicated that they had read the
problem more than once (Statement 1), while two groups indicated that they
understood what the problem was asking them (Statement 2). When responding to
Statement 4: We tried to remember if we had worked a problem like this before,
only one group indicated that they had tried to remember if they had worked on a
problem like this before. This response was despite the fact that students from the
Year 4-7 class had worked on the same problem the previous year.
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Table 5.10
Metacognitive Questionnaire
Yes No Maybe
BEFORE YOUR GROUP BEGAN TO SOLVE THE PROBLEM WHAT DID YOUR GROUP DO? 1 We read the problem more than once. 4 1 1
2 We understood what the problem was asking us 2 0 4
3 We tried to put the problem into our own words 1 1 4
4 We tried to remember if we had worked a problem like this before 1 2 3
5 We thought about what information we needed to solve this
problem 3 0 3
6 We asked ourselves, is there information in this problem that we
don’t need 0 5 1
AS YOUR GROUP WORKED ON THE PROBLEM WHAT DID YOUR GROUP DO? 7 We thought about the steps as we worked on the problem 2 0 4
8 We kept looking back at the problem after we did a step 2 3 1
9 We had to stop and rethink a step we had already done 2 2 2
10 We checked our work step by step as we worked the problem 1 0 5
11 We did something wrong and had to redo our step(s) 4 2 0
AFTER YOUR GROUP FINISHED WORKING ON THE PROBLEM WHAT DID YOUR GROUP DO? 12 We looked back to see if we did the correct procedures 2 0 4
13 We checked to see if our calculations were correct 1 1 4
14 We went back and checked our work again 6 0 0
15 We looked back at the problem to see if our answer made sense 3 2 1
16 We thought about a different way to solve the problem 3 1 2
DID YOUR GROUP USE ANY OF THESE WAYS OF WORKING?
17 We drew a picture to help us understand the problem 0 5 1
18 We guessed and checked 0 0 6
19 We picked out the operations we needed to do this problem 1 2 3
20 We felt confused and could not decide what to do 0 2 4
21 We wrote down important information 6 0 0
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Groups were also asked to respond to the following question: As your
group worked on the problem what did your group do? Four of the six groups
(67%) stated that they redid their step(s) if they did something wrong (Statement
11). This is consistent with findings from the first cycle of this study. Four groups
in Cycle 1 also indicated that they had to redo their steps.
Groups were also asked to respond to the question: After your group
finished working on the problem, what did your group do? All six groups
indicated that they had gone back and checked their work again after they had
finished working on the problem (Statement 14).
Table 5.10 also shows groups’ responses to the question regarding the
question: Did your group use any of these ways of working? All groups stated that
they wrote down important information (Statement 21). Six groups in Cycle 1
also stated they wrote down important information. This was evident in the
metacognitive checklist where groups restated the problem in their own words
and listed the categories they wanted to use to rank the cities.
The group metacognitive questionnaires, completed by the groups at the
end of the study, helped the groups reflect on their problem solving. The groups
used the three main metacognitive strategies of planning, monitoring, and
evaluating during the co-construction of their mathematical ranking model. The
reflections also indicated that on average groups adopted strategies specific to the
problem-solving task as they read the problem more than once, had to redo their
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step(s) if they did something wrong, went back and checked the work, and wrote
down important information.
5.3.2 Theme 11
The groups used metacognitive scaffolds to plan, monitor, and evaluate their task-
and team- work.
Theme 11 was derived from an analysis of the Knowledge Forum® notes
and the metacognitive checklists. The metacognitive checklists were coded
according to Schraw’s (2001) regulatory checklist (see Appendix C, p. 263). The
43 Knowledge Forum® notes were placed in the initial categories of
metacognitive or not-metacognitive.
There were 25 notes coded as not-metacognitive and 18 notes coded as
metacognitive. The 18 metacognitive notes were further separated into the
categories of planning, monitoring, and evaluating. There were six planning notes,
six monitoring notes and six evaluation notes.
The six planning notes included messages regarding what groups were
going to do. Each group chose two categories to rank and then added the
categories together to form a ranking system for the team. For example, the initial
Knowledge Forum ® notes from team one included messages planning what
categories they were going to rank.
Group A: Hi! we are Group A. Cant (sic) wait to work with you. We will
do 2 categories each.
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Group C: Hi were (sic) Group C. We will be happy to be working with you
on Monday. For our 2 categories are Movies & Adventure.
The six monitoring notes included messages from groups making sure that
their team was using enough categories to rank the cities. For example, Group C
sent a note to their online team that included a message regarding the categories
they were looking at:
U have good categories, but maybe we need more of them
The monitoring notes also included messages ensuring that all the
categories the team needed for their ranking system were incorporated. For
example, Group B sent a note to their online team asking them to look at water
restrictions in order to get the city they had chosen to number one on their ranking
system:
Yo!!
Hey can u do like water restrictions & all that type of stuff to make Sydney
no 1?? Thanx!!
The six evaluation notes all included messages regarding what the groups
had done on the task. Each group incorporated the categories from their online
team and their final Knowledge Forum® notes included their final Excel®
ranking sheet. The groups used Excel® formulas to work out which was the best
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city. The final evaluation note from Group B included the formula they had used
to work out that Brisbane was the best city in Australia:
We gave extra points for Culture (*9) and Art (*5). Sydney and Melbourne
are also top cities in Australia. Melbourne has great adventures.
(=B2+C2*9+D2+E2+F2+G2+H2+I2*5) (Formula used in Excel® to
rank the cities).
The teams engaged in a constant process of planning, monitoring, and
evaluating during the online co-construction of their teams’ mathematical ranking
models. The coding of Knowledge Forum® notes showed that the metacognitive
strategies were adopted by the online teams in order to solve the task together.
The groups were involved in discussing the planning, monitoring, and evaluating
of their team and task work as they completed the metacognitive checklists in
their group diaries.
In a procedure similar to that used in Cycle 1, the group metacognitive
checklists were completed by the groups at the beginning of each computer
session. The metacognitive scaffolds of planning, monitoring, and evaluating
were included in the checklists and groups were asked to use the scaffolds with
the introduced group roles and skills.
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All groups completed the group planning checklist during the first
computer session (cf. Johnson & Johnson, 1993). The initial planning checklist
included the following questions:
What do we know about the problem?
What is our plan to solve the problem and reach the goal?
The analysis of data showed that these questions successfully scaffolded
the groups’ planning of their mathematical model-building activity. When asked
to state what they knew about the problem, two groups indicated information
about countries or information about cities. While other groups indicated either
that they were looking for the best city in Australia or had to decide the best city
first. When asked what their plan was to solve the problem and reach the goal,
four groups included group roles as part of their plan. Group skills were also
mentioned by the three of the groups including:
Don't argue! Be positive! Share ideas (Group B).
Say thank you (Group C).
Well (sic) first share ideas and find the best idea to use and then
figure it out (Group E).
Groups were also asked what their group thought would make a good city.
Two of the groups focused on one city and why they thought that city would
make the best city. The responses included:
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Brisbane is good because it has the best theame (sic) parks, the
tempriture (sic) is excellent and It (sic) is a clean place and great
movies! (Group C).
We like Sydney because of the Sydney Harbour Bridge (Group F).
Other groups focused on what they considered to be important for any
city. These responses included:
A city with enough people to support a wealthy economy but small
enough to have a rich culture in sport and food and culture (Group
D).
Good and fun, Theme parks, Good amount of rain, Atractev (sic)
(Group A).
It has to have a nice environment lots of yummy and healthey (sic)
food that isn't really expensive and a city that has peace and nice
people (Group E).
Groups were given the CD (see Appendix T, p. 297) compiled from
various websites, detailing information about each major city. The CD
incorporated the categories from Cycle 1 and students were asked to nominate
other categories they would like to rank the cities. The categories of Sport,
Movies, and Adventure were chosen by three groups. Two groups chose Culture,
Food, and Art. Other categories chosen by the groups were Heath system, Rain
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fall, and Theme parks. The additional categories were placed on the CD along
with a number of websites so students could research their chosen categories (see
Appendix T, p. 297).
The groups also completed the monitoring checklists regarding how their
group was completing the problem-solving task and functioning as a team. The
checklists helped groups develop a shared understanding of what they were doing
well and what team-skills they still needed to incorporate in order to perform as a
team. The monitoring checklists included the following questions:
Are we following the team plan?
What are we doing well and what do we need to improve?
The analysis of data indicated that these questions successfully scaffolded
monitoring actions by the groups as they were engaged in the process of co-
constructing their ranking models. All groups indicated that they were following
the group plan and did not need to make any changes. When asked what they
were doing well, comments from groups included:
Working together, being positive, completing tasks (Group B).
Saying thank you (Group C).
We are sharing information Group F).
All groups completed the final evaluation checklist during the final
computer session (cf. Johnson & Johnson, 1993). The evaluation checklist asked
groups to comment on the following:
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Have we reached the team goal?
How did we go?
What did our team do well and what do we still need to improve?
The analysis of data indicated that these three questions successfully
scaffolded the groups’ evaluation during the final computer session. All groups
responded that they had reached the group goal. A variety of responses was given
to the question how did we go including:
We think that encoareging (sic) worked and we went well (Group
A).
We did good at working together! (Group B).
Good! (Group C).
We will work as a team hard and we had fun (Group D).
Are(sic) teamwork worked (Group E).
Very good (Group F).
When responding to the question about what their team did well, three
groups stated that they did everything well, while other comments included:
We listend (sic) to other peoples (sic) comments (Group C).
We tryied (sic) to get all of our work done (Group E).
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Finally when responding to the question what they still needed to do to
improve, three groups indicated that they did not need to improve while the
remaining three groups’ comments included:
We need to improve on working as a team (Group D).
We need to work together more (Group C).
We need to improve understanding (Group E).
The analysis of data showed that the checklists scaffolded the
metacognitive strategies of planning, monitoring, and evaluating. King (1991)
found that when students were taught specific guided questioning strategies
designed to scaffold students during problem solving, it assisted them to become
aware of their own problem-solving and metacognitive skills. The planning
checklist involved groups restating the problem and showing how they were
going to go about solving it. The monitoring checklist involved groups developing
a shared understanding of what they were doing well and what team-skills they
still needed to incorporate in order to perform effectively as a team. The
evaluation checklist involved groups reflecting on the team goal, what task- and
team-skills worked well or did not work, and what still could be improved.
5.3.3 Metacognitive themes summary
The study highlighted that the metacognitive strategies of planning,
monitoring, and evaluating are essential for groups building a shared knowledge.
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Providing groups with group metacognitive checklists resulted in groups
planning, monitoring, and evaluating the task and team aspects of their group
work. The metacognitive strategies were also adopted by the online teams. The
teams engaged in a constant process of planning, monitoring, and evaluating
during the online co-construction of their teams’ mathematical ranking models.
The metacognitive strategies allowed students to build a shared understanding of
how their group was completing the problem-solving task and working together
as a team.
5.4 Focus group interview
This section focuses on the students’ perceptions with regards to the group
diaries and the posters. Group interviews were conducted in order to obtain
students’ perceptions of the scaffolds and skills included in the diaries and posters
(see Appendix D, p. 264).
The students stated that the group diaries were effective and did not need
to be changed. Students also indicated that they used the following team posters:
Team skills, Problem solving; and Conflict management (see Appendix X, p.
302). The students stated that the team skills of being positive and sharing
information were the two most important team skills included on the posters. This
is consistent with the findings from this study where giving information and seems
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friendly were the highest categories coded from the Knowledge Forum® notes
posted.
5.5 Summary and conclusion
The scaffolds used in this study affected how group members in this cycle
interacted and developed, including the problem-solving task; the posters of group
skills, roles, conflict management skills, and problem-solving strategies; the use
of group diaries to build a shared understanding of the requirements of the task
and the team, and incorporating metacognitive checklists to scaffold the planning,
monitoring, and evaluating of the groups shared understanding. The Knowledge
Forum® database and Excel® mathematical ranking models also helped groups
develop a shared understanding of the task they were collaboratively completing.
The following chapter discusses the results from Cycles 1 and 2 and
combines the findings from both cycles into a unified conceptual model that can
be used to scaffold within- and between-group metacognition within CSCL
environments. Chapter 7 concludes the study by overviewing the findings and
declaring the limitations of the study. Recommendations are made for future
research and implications for practical application of the group metacognition
model are also discussed.
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CHAPTER 6: DEVELOPMENT OF UNIFIED CONEPTUAL MODEL
The aim of this study was to develop a conceptual model to inform the use
of scaffolds to facilitate within- and between-group metacognition during
mathematical problem solving in computer supported collaborative learning
(CSCL) environments. To address the aim, the study proceeded in two stages.
Stage 1 focused on Research Objectives 1 and 2. It consisted of two cycles of
design experiments (Cycles 1 and 2). The results from these two cycles were
presented and discussed in Chapter 4 and 5. This chapter reports on Stage 2 of the
study. Stage 2 focuses on Research Objective 3. It thus discusses and cumulates
the results from Stage 1 to develop a unified conceptual model (see Figure 6.4)
that can be used to inform the use of scaffolds for within- and between-group
metacognition in CSCL environments.
This chapter begins with an overview of results from Stage 1 (see Section
6.1). The findings from Cycles 1 and 2 are further analysed and synthesised in
order to identify the elements and form the structure of the unified conceptual
model (see Section 6.2). The application of the unified conceptual model is then
discussed in Section 6.3. A summary and conclusion is presented in Section 6.4.
6.1 Overview of results
The results from both cycles in Stage 1 of the research study showed that
the problem-solving context played a crucial role in determining how the students
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worked together both within-groups and between-groups. Many of the
organisational factors identified in the initial conceptual framework (see Figure
2.7) also were found to help groups to develop into successful problem-solving
teams. The findings clearly indicate that having appropriate problem-solving
activities, and incorporating categories of organisational factors such as problem-
solving strategies, group roles, group skills, and conflict management skills in
CSCL environments, to help students during group problem solving, are
necessary but not sufficient conditions for successfully scaffolding engagement in
knowledge building within- and between-groups in CSCL environments.
Groups also need to engage in cognitive activity and develop shared
external representations of both team knowledge and task knowledge. It is only
then that they begin to internalise their shared understanding of the problem-
solving task and how to work together as a successful team. Furthermore, the
findings from Stage 1 also indicate that in order for groups to develop and
advance shared understandings of the problem-solving task and how to work
together as a successful team, they also need to metacognitively reflect overtly on
the organisational and cognitive strategies while completing the problem-solving
task. Each of these four elements will now be discussed in detail.
6.1.1 Problem-solving task
Groups from both cycles of the study were engaged in the ‘Best city’
model-eliciting problem-solving task. In this task, the groups were required to
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construct a mathematical model to rank the cities in order to find the best city in
Australia. This task was quite different from the types of mathematical tasks that
the students normally did in their classrooms. In addition to creating, sharing,
critiquing, and improving mathematical models, this task was conducted over a
period of six one hour lessons rather than a period of just ten to fifteen minutes.
The groups in Cycle 1 developed their ranking models within their group
and then the models were combined in a class model. The students from Cycle 1
indicated that they had found the model-eliciting activity interesting but they were
not completely satisfied with the combined model developed. Many of the
students expressed doubts about the validity of the combined class model and
some of the assumptions underlying this model. They felt that other assumptions
should have been adopted and that other cities should have been ranked first.
Thus, changes occurred in the students’ conceptions about the nature and
discourse of mathematics; they began to realise that mathematics was not
objective in nature but that it was a discipline in which they could engage in
discourse about the validity of the assumptions underlying, and the solutions of,
mathematical problems.
In Cycle 2, the groups initially developed their ranking model and then
worked in an online team with two other groups to form a combined team model.
Thus, the teams in Cycle 2 were provided more freedom than the groups in Cycle
1 to manipulate many assumptions during the development of their ranking model
for identifying the top city. The online teams were able to share, discuss, and
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negotiate many aspects of their ranking model such as the underlying
assumptions, what data to include or exclude from their model, what criteria
should be used to rank the cities, and what weighting should be attributed to each
criteria used in their model (see Appendix W, p. 300).
6.1.2 Organisational factors
The organisational factors that were identified in the initial conceptual
framework influenced how the groups in this study developed into successful
problem-solving teams (see Figure 2.7). While the majority of the groups did not
progress neatly through the development stages highlighted by Tuckman and
Jensen (1977), the results from this study showed that the groups performed well
and incorporated effective team- and task-behaviours. Tuckman and Jensen’s
(1977) framework was useful in identifying the different development stages that
the groups were involved in during this study. However, the findings from the
study showed that the groups and the online teams went through a three stage
development process of forming, performing, and adjourning, rather than the five
stages proposed by Tuckman and Jensen’s model (Tuckman & Jensen. 1977).
By scaffolding the norming and storming stages of group development, all
groups involved achieved the performing stage and were working
interdependently as a team incorporating both task- and team-oriented behaviours.
This performing stage of group development usually only occurs in only a small
percentage of groups (Langan-Fox, 2003; Tuckman & Jensen, 1977).
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The group roles, group skills, problem-solving strategies, and conflict
management skills scaffolded in this study helped the groups adopt group norms
that focused on the task as well as their team performance. Each group defined
their own group norms as they were involved in choosing group roles and skills to
use each computer session and were continually evaluating the use of the group
skills throughout the study. The expectations for the group were made explicit to
all group members as the chosen problem-solving strategies, group skills and
roles, and conflict management skills were written in the group diaries. All groups
showed high levels of cooperation as they discussed how they were progressing as
a group and used the group diaries to self regulate their own group processes.
During Cycle 1, group roles and skills were placed in the group diary and
the groups chose which skills they wanted to concentrate on in the following
computer session. The group skills, problem-solving strategies, and group roles
used in Cycle 1, were placed on classroom posters for Cycle 2. Conflict-
management strategies were also placed on a poster during Cycle 2 as the students
in Cycle 1 had identified arguments and fighting as the aspect that they liked least
about working together.
While Tuckman and Jensen (1977) suggest that conflict is an important
stage of group development, only six groups from the sixteen groups (37.5%) in
Cycle 1 were engaged in storming behaviours. During the initial stages of the first
cycle, the disagreements were more team- than task-related. Task-related conflict
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occurred throughout the cycle. However, by the end of the first cycle, group
disagreements tended to be more task-related than team-related and were resolved
quickly by the group members. By engaging in task-related rather than team-
based conflict, groups were able to engage in knowledge building. This is
consistent with previous research studies that showed that students can gain a
shared understanding of the task by engaging in task-related conflict (Crook,
1996; Rentsch & Zelno, 2003).
While Poole and Zhang (2005) have stated that virtual teams are also
likely to experience conflict, the groups involved in the online teams in the second
cycle of the study tended to be involved in negotiation over task issues rather than
becoming involved in conflict. Negotiation is seen by Puntambekar (2006) as the
process by which groups arrive at group decisions. The groups in Cycle 2 were
also involved in more positive negotiation about group roles and skills as group
members worked out what roles and skills would be focused on in each computer
session.
The main difference between the two cycles was that, during the second
cycle groups were overtly made aware of conflict management strategies, via
classroom posters. Group members were also made aware that disagreements are
part of developing into a productive team and that there were strategies that could
be used to work through conflicts (see Appendix X, p. 302).
Langan-Fox (2003) and Tuckman and Jensen (1977) suggested that the
performing stage of group development occurs in only a small percentage of
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groups. The results from both cycles in this study show that all groups involved
achieved the performing stage and were working interdependently as a team
incorporating both task- and team-oriented behaviours. The groups adopted the
group norms and focused on the task as well as their group performance. The
problem-solving skills, group roles, group skills, and conflict management skills
scaffolded in this study helped create interdependence among group members as
the groups involved encouraged and helped each other to reach the task goal.
6.1.2.1 Summary
The findings from this study show that successful groups are achievable
with primary school students when task- and team-related knowledge and skills
are made explicit and groups are able to plan and reflect on the skills used.
Students need to be made aware of problem-solving strategies, group roles and
skills, and conflict management skills, in order for them to gain knowledge about
the strategies used in successful groups. Groups also need to be involved in
choosing the appropriate skills and group roles relevant to their own group.
While the findings in this study were informed by Tuckman and Jensen’s
(1977) model, group development was not always a linear process. The storming
stage was not evident in the second cycle of the study. Norming was evident in all
stages of the study as groups defined their own norms by choosing and reflecting
on problem-solving strategies, group roles and skills, and conflict management
skills, throughout the study.
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6.1.3 Cognitive factors
Cognitive factors also influenced how the groups in this study developed
into successful teams and helped them form shared external understandings and
shared internal understandings, or mental models, of the task and of how their
group needed to perform. Druskat and Pescosolido (2002) stated that shared
mental models emerge as team members interact and develop shared beliefs about
the task and how they should work together. This occurred in both cycles of this
study; the collective internal models helped the team members to determine
appropriate actions and helped contribute to a sense of ownership and control of
their team work.
The groups, in both cycles, developed a shared understanding about the
problem task they were solving together. They also developed a shared
knowledge about their team work as they self-managed their team work by
allocating group roles appropriate to the needs of their team and planning what
skills they would use to work as a team. By focusing on both the task and team
aspects of their group, the groups formed a shared internal knowledge about how
successful groups perform. This is consistent with Webber et al. (2000) who
stated that groups must focus on both the task and the team work and share
knowledge of both in order to perform as a successful group. This shared
knowledge helped the groups focus on their problem solving as well as their
group processes. The shared understanding of the problem-solving strategies,
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group skills and roles, and conflict-management skills, allowed group members to
reflect on their group performance and constantly improve their problem solving.
Barron (2000) suggested that in order to establish shared understanding,
group members must first negotiate a shared external representation. Students
need to articulate their thinking and make their group understanding explicit in
order to collaborate with group members (Lewis, 1997; Mohammed & Dumville,
2001). The shared external representations in this study were facilitated by group
diaries, checklists, the mathematical ranking models, and the Knowledge Forum®
database, which all helped scaffold the group and the problem-solving process.
Explicit knowledge of effective problem-solving strategies, group roles
and group skills were shared with the students in both cycles of the study which
helped the groups to form their own shared understanding of both their task- and
team-work. Explicit knowledge about conflict management skills was also shared
with the students in Cycle 2 of this study. The shared external goals helped
students develop a sense of being part of the 'group' and the group processing
checklists, from the group diaries, allowed groups to assess how well they were
working together.
During Cycle 2, the mathematical ranking models and the Knowledge
Forum® notes helped students develop an external representation of the task they
were collaboratively completing. Groups shared their ranking models with their
online teams by posting the models onto the Knowledge Forum® database; the
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groups also posted notes that related to both the task and the team. As predicted
by Scardamalia and Bereiter (1994), the Knowledge Forum® database allowed
the task knowledge to be visible to all groups and provided a record of the
problem-solving process (Hurme & Järvelä, 2001; Jonassen & Carr, 2000;
Ngeow, 1998; Scardamalia & Bereiter, 1994; Stein, 1998).
By explicitly sharing their ideas, the students were able to gain a shared
understanding of how their group needed to work together to solve the problem-
solving task they were completing. The shared explicit understanding allowed
groups to work effectively and to build a shared internal understanding for solving
the problem and working together as a team.
6.1.3.1 Summary
The findings from this study highlight the importance of groups
developing shared external representations of problem-solving strategies, group
roles and skills, and conflict management skills, in order to develop shared
understandings of both their task-work and their team-work. The shared internal
understandings that groups formed from the shared external knowledge ensured
that the groups had common expectations of the task and the team, which allowed
them to be able to coordinate their actions to perform successfully. The findings
are consistent with Cannon-Bowers and Salas (2001) concept of shared mental
model construction for effective work teams. The findings emphasise that the
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concept of shared mental models are also important for groups developing a
shared understanding in educational settings.
This shared understanding of both their task and their team helped the
groups coordinate their actions towards achieving the solution to the task as well
as working together successfully as a team. Groups need to have a shared internal
model of how their group is developing and how effectively their group is
performing. Groups also need to reflect on and develop a shared understanding of
both their task- and their team-work.
6.1.4 Group metacognition
In this study, engagement in group metacognitive strategies of planning,
monitoring, and evaluating their shared understandings of both their task- and
team-work was scaffolded by the group diaries. By engaging in these three
metacognitive strategies, the groups identified the skills and strategies that they
could use to improve their group problem solving. Group members were able to
develop a shared understanding of their problem-solving task and their team by
planning, monitoring and evaluating their group’s success and by discarding
inappropriate team- and task-skills.
Because of these metacognitive strategies, the groups in this study
developed and advanced their knowledge about successful problem-solving
strategies, group roles and skills, and conflict management strategies, and
developed a belief that their group processes could be improved by using the
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metacognitive strategies of planning, monitoring, and evaluating. This knowledge
and belief helped members develop a positive attitude towards their group and an
understanding that they could control their own group processes.
6.1.4.1 Planning
Ward and Morris (2005) proposed that the first stage of planning is to
form a mental representation of the problem. According to Ward and Morris, the
representation needs to include the initial state as well as a range of possible
actions that need to be taken to reach the goal state. In both cycles of this study,
this was achieved by the groups using their diaries to state what the problem was
as well as what their plan was to solve the problem. The Knowledge Forum®
notes in Cycle 2 also contained planning messages regarding what categories each
group was going to use to rank the best city.
The planning phase helped build the groups’ knowledge about effective
group work and they developed a shared understanding of what needed to be done
in order to work effectively together and to achieve a solution to the problem-
solving task. The groups used the planning page of the diary, at the start of each
cycle, to focus on their group roles, group skills, and problem-solving skills.
Group members planned together which roles and skills were important for their
group to develop into an effective performing team. By planning which skills
would be focused on, group members were able to identify the skills that they
needed to improve.
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6.1.4.2 Monitoring
Students often fail to monitor their problem solving or their group work
(Carr & Biddlecomb, 1998; White & Frederiksen, 2005). In this study, this
dilemma was addressed by the including of a monitoring checklist in the group
diary. This helped the groups reflect on their learning, and scaffolded the
monitoring processes (c.f., Blakey & Spence, 1990; Mueller & Fleming, 1994;
Wilson & Johnson, 2000). The groups used the monitoring checklists to decide if
they needed to change the skills they had chosen in the planning stage. The
groups also determined what other skills needed to be included to make the group
problem-solving process more effective.
Transcripts of the audio (MP3) recordings of the groups working together
in Cycle 1 showed that groups were monitoring their shared understanding of
their team and their task work throughout the study as they used the group diaries
in each computer session to reassign group roles and identify skills that they
needed to improve their problem solving and their group work. The Knowledge
Forum® notes, from Cycle 2, showed that the groups were also monitoring their
shared understanding of their online team’s progress with the problem-solving
task (see Section 5.3.2). The monitoring notes included messages ensuring that all
the categories the team needed for their ranking system were incorporated.
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6.1.4.3 Evaluating
Each group in this study utilised an evaluation checklist to develop shared
knowledge of how to evaluate their understanding of the task and the team. The
evaluation checklist in the group diary asked groups to reflect on what had
worked well with their groups and what they could do differently next time they
worked as a group. The checklist helped the groups reflect on what task- and
team-skills they used and what skills they need to incorporate in the future. The
groups evaluated their own skill selection throughout the study reflecting on the
effectiveness of their team and their task work. This is consistent with Johnson et
al. (1993) who stated that groups need to reflect on how their group is functioning
to achieve their goals and adjust the skills needed in order to develop into a
successful performing group. By evaluating the skills used group members were
able to a shared develop understanding of how they could effectively work
together and of their problem-solving task.
At the end of each cycle, the groups were also asked to evaluate how the
activity including the group diaries, posters, and Knowledge Forum® database
could be improved. The students all agreed that the group diaries were effective
and did not need to be changed. In Cycle 2 students indicated that they found the
team skills, problem solving, and conflict management posters useful (see
Appendix X, p. 302). The students also stated that the team skills of being positive
and sharing information were the two most important team skills included on the
posters.
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6.1.4.4 Summary
This study showed that applying metacognitive strategies for group
problem solving allows students to focus on the organisational and cognitive
factors that influence how groups perform their problem-solving task and work
together as a team. Groups need to plan, monitor, and evaluate group skills and
strategies specific to the task and their team. They also need to be able to apply
these strategies to develop a shared group understanding
Groups in this study assumed responsibility for planning, monitoring, and
evaluating their group learning through the use of the metacognitive checklists.
The group metacognition led to shared understandings of team- and task-work
which helped the groups take responsibility for their own group performance.
Group members also developed knowledge about metacognitive strategies as they
answered the group metacognitive questionnaire and completed the planning,
monitoring, and evaluating checklists in the group diary.
6.2 Group metacognitive model
The results from Cycles 1 and 2 have been cumulated into a unified
conceptual model that can be used to inform the scaffolding of within- and
between-group metacognition during mathematical problem solving within CSCL
environments (see Figure 6.4). The following sections construct the group
metacognition model and describe how groups can develop a shared
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understanding of how to work successfully as a team while engaged in group
mathematical problem solving.
6.2.1 Problem-solving context
The complex problem-solving context forms the initial component of the
group metacognition model emanating from this study (See Figure 6.1).
Complex problem-s olving context
Figure 6.1. Complex problem-solving context.
Previous studies have found that the type of mathematical problem
administered to students during group problem solving has much impact on the
quantity and quality of students’ face-to-face and online discussions (Cho &
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Jonassen, 2002; Etheris & Tan, 2004; Jonassen & Kwon, 2001). When groups of
students are involved in problem tasks which are ill-defined such as the model-
eliciting problems (Lesh & Kelly 2002), groups need to be involved in high levels
of co-operation, as they work together. The outcomes of this study confirmed this.
The ‘Best city’ model-eliciting problem required the students to use task and
team-skills to work together to solve the problem (Dishon & O'Leary 1984).
As was noted in Chapter 3, the design of the ‘Best city’ model eliciting
activity was informed by Lesh et al.’s (2000) six principles for the construction of
model-eliciting activities (see Section 2.1.1.1). Based on the analysis of
observation and focus group interview data, the reality and construct shareability
principles were found to be most crucial. That is, the problem needs to be:
1. Interesting, meaningful, and relevant to students and to enable them to
engage in the problem for a longer period of time than traditional
classroom mathematical problems and exercises (Reality principle).
2. Designed to allow for the creation of mathematical model(s) that can be
shared and advanced through discourse with other groups of students
(Construct shareability principle)
A key outcome of the analysis of observation, focus group interviews, and
Knowledge Forum data was that most students came to the realisation that
mathematics was not a one-right-answer one-right-procedure type of endeavour.
In addition to helping the students gain this more advanced conceptualisation
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about the nature and discourse of mathematics, this realisation was found to be a
very motivating factor for the students. Thus, in addition to Lesh et al.’s (2000)
principles, the outcomes of this study indicate an additional principle that focuses
on the design of problem tasks that helps students to gain insights about the
subjectivity of mathematics was needed, that is a Subjectivity of Mathematics
Principle such as:
The design of the tasks should facilitate the creation of multiple and
sharable models that are open to modification, improvement, and
validation.
Problem tasks informed by these three principles would provide students
with contexts that would facilitate the development and utilisation of group
metacognitive behaviour.
6.2.2 Organisational factors
The initial conceptual framework developed from the literature review
suggested that organisational factors influenced group problem solving and
learning (see Figure 2.7). The results from this study showed that the
organisational factors could be aggregated into four categories: problem-solving
strategies, group roles, group skills, and conflict management skills, in order for
groups to gain knowledge about the strategies used by successful groups. Posters
of these skills and strategies should be made available to the groups. Groups also
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need to be involved in choosing the skills and group roles relevant to their own
group.
The findings from Cycle 1 highlighted that making the skills explicit helps
students understand the importance of using the skills. Analysis of Cycle 2
highlighted that it is also important that students are aware of group processes and
how group skills will benefit their group work. Groups must learn how to control
their own group’s learning in order to perform successfully and in order to learn
the task- and team-skills for future group work. Therefore, the following four
organisational factors were added to the model: problem-solving strategies, group
roles, group skills, and conflict management strategies (see Figure 6.2).
The process of constructing explicit knowledge about these four
organisational factors can be scaffolded by providing posters that make the
problem-solving strategies, group roles, group skills and conflict management
strategies public and shared knowledge that groups can constantly refer to and
build on when engaged in collaborative group problem solving.
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Complex problem-s olving context
Group ski lls
Problem-solving
strategies
Group roles
Confl ict management
ski l ls
Organisational factors
Figure 6.2. Organisational factors.
6.2.3 Cognitive factors
Groups who engage in ill-defined tasks, such as model-eliciting tasks need
to develop a shared understanding of the task, as they work out what they need to
achieve and how they will share relevant information to arrive at the answer
(Zawojewski et al., 2003). By explicitly sharing their ideas, groups are able to
gain a shared understanding of how their group needs to work together to solve
the problem-solving task they are completing. A shared understanding of the task
also helps groups reflect on how their group can perform and coordinate their
actions to achieve a solution. The results from this study confirmed that in order
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to successfully work together, group members also need to have shared
knowledge of effective problem-solving strategies, group roles and skills, and
conflict management skills.
The findings from this study also highlight the importance of groups
developing a shared external representation of their task- and team-work in order
to develop a shared internal understanding. The development of the external
representation of their team-work and task-work enabled the groups to develop a
shared internal understanding of the problem-solving task and how their group
was performing. Therefore, within the cognitive section of the conceptual model,
the importance of developing shared team-knowledge and shared task-knowledge
is highlighted (See Figure 6.3).
Shared task understanding
Shared team understanding
Group ski ll s
Problem-solving
strategiesGroup roles
Confl ict management
ski l ls
Organisationalfactors
Cognitive factors
Complex problem-s olving context
Figure 6.3. Cognitive factors.
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6.2.4 Metacognitive factors
The findings in this study clearly indicate that successful problem-solving
groups critically reflect on the skills used in order to constantly improve their
shared understanding of their team work and their problem-solving task.
Therefore, the conceptual model posits the need for planning, monitoring, and
evaluating strategies that help groups to reflect on their developing shared
knowledge about team- and task-work within the complex problem-solving
context (see Figure 6.4).
Applying metacognitive strategies for group problem solving allows
groups to focus on the organisational and cognitive factors that influence how
they perform their problem-solving activity and work together as a team. Groups
need to plan, monitor, and evaluate group skills, roles, and strategies specific to
their group and the group problem-solving task. They also need to apply these to
develop a shared group understanding of the team and task aspects of the group
problem-solving activity.
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Shared task understanding
Shared team understanding
Planning Monitoring Evaluating
Group ski ll s
Problem-solving
strategiesGroup roles
Confl ict management
ski l ls
Organisational factors
Cognitive factors
Metacognitive factors
Complex problem-s olving context
Figure 6.4. Group metacognition model.
6.2.5 Discussion
In this section, the interrelationships between the four components of the
group metacognition model (the complex problem-solving context, organisational
factors, cognitive factors, and metacognitive factors) will be analysed and
discussed. The analysis and discussion will highlight not only the importance of
each component of the model but also the consequences of students not acquiring
specific elements of each of the components.
The first component of the model, the context provided by complex
mathematical problems, was based on the three modifications or design principles
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(see Section 6.2.1). Therefore, the groups in both cycles were able to engage in
discourse that facilitated the advancement of both task- and team-knowledge.
If, however, problem tasks that do not adequately meet these three
principles are used, it is unlikely that the students will have opportunities to
engage in the mathematical knowledge building discourse necessary for the
adoption of the organisational, cognitive, and group metacognitive factors
identified in the group metacognition model. As Lesh et al. (2000) pointed out,
most mathematical problems generally found in mathematics textbooks and
worksheets fall into this category and do not meet the three design principles.
They usually fail to motivate groups of students to engage in sustained task-
related discourse. Furthermore, they often only have one answer and one ‘correct’
solution procedure. These two characteristics of “classroom” mathematical
problems make it highly unlikely for groups to engage in the task-related
discussion that is essential for effective mathematical knowledge building.
The second component of the model, the four categories of organisational
factors: problem-solving strategies, group roles, group skills, and conflict
management skills, enable groups to gain knowledge about the skills and
strategies used in successful problem-solving teams. These four categories are
complementary and all must be performed for groups to work together effectively.
The problem-solving strategies can be used by the groups to identify
possible solution paths specific to the problem being solved. The strategies also
provide a language of discourse for effectively allowing groups to discuss their
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solution paths as they reflect on how they solved the problem. If the students are
not conversant with the problem-solving strategies, they may not be able to start
the problem-solving process. However, the main consequence of not being
conversant with these strategies is that it could limit the task-related discourse that
is so crucial for advancement of the mathematical models by both face-to-face
and online teams.
By scaffolding group skills, groups are able to incorporate both successful
task- and team-oriented behaviours. Task-skills include sharing ideas, sharing
information, and checking for understanding (see Appendix X, p. 302). Team-
skills include encouraging others, being positive, and checking for agreement (see
Appendix X, p.302). If these group skills are not incorporated by the groups, then
they almost certainly will not focus on their team- as well as their task-
performance.
The group roles help the groups self-organise and allow each student an
opportunity to use the computer. As reported by Cohen (1994), it is important to
make these roles public and give students authority to act in the group role
allocated. This helps clarify the group role for the student and for other group
members. If the group roles are not incorporated by the groups, the groups
probably will lack direction and engage in non-productive team-conflict.
Conflict management skills are necessary as disagreements and conflicts
are often the reason why students do not like to work together in groups and/or do
not work effectively as teams. Giving the groups the tools to resolve their own
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conflicts enables conflict to be a positive rather than a negative factor influencing
group problem solving. If groups do not acquire these conflict management skills,
most conflict will be team-based rather than task-based. As was noted in the
literature review, knowledge-building behaviour is enhanced when conflict is
task-based rather than being team-based (see Section 2.1.1).
The third component of the model, the cognitive factors are important in
helping groups develop and form a shared understanding of their team- and task-
work during a complex problem-solving task. Without this shared understanding,
groups may not advance their shared knowledge of the organisational factors (i.e.,
problem-solving strategies, group skills, group roles, and conflict management
skills) that the group needs to incorporate in order to improve their group problem
solving and learning. If the groups do not acquire and utilise these cognitive
factors, then it is highly unlikely that the groups’ shared understanding of the
organisational factors will advance beyond what has been directly taught to them
by their teacher(s). That is, they will not learn how to expand their repertoire of
problem-solving strategies, group skills, group roles, and conflict management
skills beyond what the teacher has introduced to them. Without this ability,
limited growth will occur in the groups’ collaborative group learning.
While the organisational and cognitive factors are important, the fourth
component of the model, the metacognitive factors, is probably the most crucial
component of the group metacognition model. These factors are crucial for the
development and improvement of the groups’ shared understanding of their team-
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and their task-work. By planning, monitoring, and evaluating their shared team
and task understanding, groups can identify the skills and strategies that they can
use to improve their problem solving and their team work. Groups are able to
advance their shared team and task understandings by using the metacognitive
scaffolds as they plan, monitor, and evaluate their problem-solving strategies,
group skills, group roles, and conflict management skills. Without these group
metacognitive factors, advances on the groups’ shared understandings of their
task- and team-work are unlikely to occur. At best, there will be only limited
advances in these shared understandings.
6.3 Application of group metacognition model
The aim of this study was to develop a conceptual model to inform the use
of scaffolds to facilitate within- and between-group metacognition during
mathematical problem solving in computer supported collaborative learning
(CSCL) environments.
The model in the form presented in Figure 6.4 can be applied in both
within- and between-group contexts. However, the findings from this study
indicate that before the between-group online teams engage in CSCL, it is
important that they have had within-group face-to-face experience in applying the
organisational, cognitive, and metacognitive factors subsumed in the group
metacognition model. All groups worked together in their face-to-face groups in
order to plan, monitor, and evaluate their team and task work. The groups also
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worked with other groups and formed online teams. The team and task skills that
the groups used face-to-face were transferred to the online environment.
Therefore, it is a recommendation of this study that groups have extensive face-
to-face experience in applying the group metacognition model prior to engaging
in group work in an online environment.
This recommendation is consistent with prior CSCL research (e.g., Brett,
Nason & Woodruff, 2002; Brett, Woodruff & Nason, 1999, 2002; Nason, Brett, &
Woodruff, 1996) that indicates that group collaboration skills need to be learnt
and consolidated at face-to-face levels prior to their implementation within CSCL
contexts. If this is not done, group members will not be able to transfer their
collaboration skills to the online environment and will not be able to form
effective online problem-solving teams.
The findings from this study also indicate that the mathematical problem-
solving task administered to the groups enabled them to share and discuss the
mathematical models they had constructed with the other two groups contained in
their online CSCL team. This enabled them to immediately engage in online
CSCL knowledge building. Without these mathematical models to discuss,
evaluate, and advance, it is highly unlikely that this CSCL knowledge building
discourse would have occurred.
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6.4 Conclusion
In this chapter, the findings from Stage 1 of the study were cumulated into
a unified conceptual model to inform research and practice about the development
and maintenance of within- and between-group metacognition during
mathematical problem solving with primary school students. The conceptual
model posits that in order to promote group metacognition during mathematical
problem solving, the following four components need to be addressed: 1. problem
solving-context, 2. organisational factors, 3. cognitive factors, and 4.
metacognitive factors. The model highlights that organisational and cognitive
factors are important to help groups develop and form a shared understanding of
their team- and task-work during complex mathematical problem solving in a
CSCL environment. The model also highlights that metacognitive factors are
crucial as groups need to continually reflect on and improve their shared
understandings.
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CHAPTER 7: CONCLUSION
This chapter begins with a brief overview of the study in Section 7.1. The
theoretical and practical significance of the study is then discussed in Section 7.2.
Following this, the limitations of the study are identified in Section 7.3. The
chapter concludes with recommendations for future research in Section 7.4.
7.1 Overview of the study
The aim of this study was to develop a conceptual model to inform the use
of scaffolds to facilitate within- and between-group metacognition during
mathematical problem solving in computer supported collaborative learning
(CSCL) environments. In order to meet this aim, a design research methodology
was adopted. The design research methodology involved two cycles of design,
experiment, and analysis in order to generate outcomes that have application both
within and beyond the context of the present study and to build theory (Bereiter,
2002; Shavelson et al., 2003). A case study method was also used for data
collection to incorporate multiple sources of data and in order to bring out the
viewpoint of the group members involved in the study (Tellis, 1997).
The study proceeded in two cycles. Cycle 1, which focused on Research
Objective 1, involved the design, evaluation, and advancement of within-group
metacognitive scaffolds during mathematical problem solving for groups working
around a computer. Cycle 2, which focused on both Research Objectives 1 and 2,
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involved the design, evaluation, and advancement of within- and between-group
metacognitive scaffolds for groups building collective mathematical knowledge in
CSCL environments. The results from Cycles 1 and 2 were synthesised into a
unified model (Research Objective 3) that could be used to inform the design of
within- and between-group metacognitive scaffolds in CSCL environments (see
Figure 7.1).
Shared task understanding
Shared team understanding
Planning Monitoring Evaluating
Group ski ll s
Problem-solving
strategiesGroup roles
Confl ict management
ski l ls
Organisational factors
Cognitive factors
Metacognitive factors
Complex problem-s olving context
Figure 7.1. Final model.
The final model identified four categories of factors that influence how
groups work effectively within CSCL environments. These four categories are:
the problem-solving context, organisational factors, cognitive factors, and
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metacognitive factors. Without an appropriate problem-solving context, it is
highly unlikely that students will engage in knowledge-building discourse that
leads to the advancement of their mathematical knowledge. The model also
clearly identified that the scaffolding of organisational and cognitive knowledge
about the team and the task are necessary but not sufficient conditions for
facilitating effective group problem solving and collaborative learning. The model
highlighted that the metacognitive factors are crucial for groups to develop into
effective collaborative knowledge building teams; without the scaffolding of
group metacognition, it is highly unlikely that groups will learn how to advance
their organisational and cognitive strategies and skills.
7.2 Significance
The literature review presented in Chapter 2 noted that because most prior
research into collaborative group learning inside and outside of CSCL
environments had tended to focus on organisational or cognitive factors only,
relatively few recent significant theoretical and practical advances had been made
in the field. The group metacognition model (see Figure 6.4) with its focus on the
problem-solving context, organisational, cognitive, and metacognitive factors and
the symbiotic relationships between these four categories of factors thus provides
a conceptual framework to advance the field of collaborative group learning
within CSCL environments both theoretically and practically.
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The group metacognition model has what Yin (1994) refers to as
analytical generalisability but not statistical generalisability. Findings from case
studies are generalisable to theoretical propositions but not to populations (Yin,
1994). The theoretical propositions subsumed within the group metacognition
model thus can be generalised to other group contexts (Miles & Huberman, 1994)
and can be utilised to provide a conceptual framework to advance the fields of
collaborative learning and metacognition both theoretically and practically.
7.2.1 Theoretical significance
The theoretical significance of the study is predominately derived from the
four categories of factors, the structure, and the interaction between the four
categories subsumed within the group metacognition model which is presented in
Figure 6.4. This model thus provides a holistic framework for not only enabling
researchers to investigate each of these four categories of factors in isolation but
also a framework for investigating the relationship between these categories.
Most of the research focusing on collaborative group learning within
CSCL environments has not considered the influence of the type of task that
students are engaged in has on the development of effective group learning. Three
principles were used in this study to inform the design of the mathematical
problem-solving task to provide the optimal context for facilitating within- and
between-group metacognition in a CSCL environments. The set of three
principles provides researchers with starting points for research in the fields of
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CSCL, group metacognition, and mathematics. The set of principles to inform the
design/selection/modification of mathematical problems subsumed within the
group metacognition model also provides researchers with principles that can be
either supported or refuted by future research.
The group metacognition model clearly identified close relationships
between team and task organisational strategies and skills. The model thus
provides researchers with a new lens for investigating organisational factors
within CSCL environments. In particular, the model provides researchers with a
framework for proceeding beyond the investigation of the scaffolding of team and
task strategies and skills in isolation that has characterised most past research in
this area.
The shared cognitive understandings of team and task that form an
essential component in the group metacognition model had their genesis in
organisational research. The inclusion of cognitive factors in the model thus
provides conceptual artefacts that hitherto have seldomly been utilised in
educational research in general and in the field of CSCL in particular. The lenses
offered by these artefacts enable researchers to investigate how students can
advance their knowledge about team and task beyond what has been introduced to
them by their teachers.
The inclusion of metacognitive factors within the model extends theory
and research about metacognition beyond the study of individuals to the study of
metacognition within collaborative learning groups. As Costa and O'Leary (1992)
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and Stahl (2006) pointed out, this is an area within CSCL research that has been
under-researched. Prior research into group metacognition, in the main, has not
focused on the relationship between group metacognition and the three other
factors identified in the group metacognition model. Therefore, in addition to
providing a conceptual framework for extending research into metacognition
beyond the individual, the model provides a framework to inform future research
into the relationship between group metacognition and the other three factors.
The four categories of factors subsumed within the group metacognition
model provide future researchers with conceptual artefacts that can be confirmed
or refuted. This is consistent with Popper’s (1979) notion that in order to facilitate
the advancement of knowledge, researchers should present their findings in forms
that enable future researchers to confirm or refute their findings.
7.2.2 Practical significance
In addition to theoretical significance, the outcomes of the present
research study also have practical significance. The group metacognition model
presented in Figure 6.4 can provide teachers with a framework to inform the
implementation of effective CSCL groups within their classrooms.
The set of principles to inform the design of mathematical problem-
solving tasks (subsumed within the group metacognition model) can be used by
teachers to design appropriate mathematical problems to facilitate the building of
mathematical models that form the basis for knowledge building discourse by
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groups of students. The principles can also be used by teachers to select
appropriate existing mathematical problems or to modify inappropriate existing
problems into forms which will facilitate knowledge building discourse by groups
of students.
Problems need to interesting, meaningful, and relevant to students and be
able to engage students for a longer period of time than traditional classroom
problems. Problems needed to be designed to allow for the creation of
mathematical model(s) that can be shared and advanced through discourse with
other groups of students. During the solution of the problems, students should
gain an understanding about the subjectivity of mathematical models (i.e.,
mathematical models are open to criticism and revision).
The team and task organisational scaffolds subsumed within the group
metacognition model can be utilised by teachers to introduce and maintain
effective group roles, group skills, conflict management skills, and problem-
solving strategies (see Appendix X, p. 302) within collaborative learning groups.
The list of team- and task-organisational scaffolds subsumed within the group
metacognition model can also be used by teachers as a checklist for evaluating
their current applications of collaborative group learning within and between their
classrooms.
Teachers can use group diaries and the structure of CSCL interfaces
(subsumed within the group metacognition model) to scaffold the cognitive
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strategies and skills necessary for effective collaborative learning groups. Group
diaries facilitate the building of shared external representations necessary for
effective collaborative group learning. The structure of the CSCL interfaces can
facilitate online discourse that goes beyond socialisation to cognition.
Teachers can also use metacognitive scaffolds, such as those identified in
the final group metacognition model, to enable groups to focus on how their
group is completing the problem-solving task and working together as a team.
The planning, monitoring, and evaluating checklists incorporating the use of
metacognitive strategies subsumed within the group metacognition model can be
used to initiate, maintain, and advance group metacognition. In addition, teachers
can utilise the planning, monitoring, and evaluating checklists to enhance
metacognitive behaviour by individual students within their classrooms.
7.3 Limitations
During the course of the study, the following possible limitations were
noted:
1. Generalisability of the outcomes of the study
2. Researcher as participant
3. Withdrawal of the group metacognitive scaffolds
4. Design of scaffolding tools
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Because of the case-study methodology utilised in the study, the group
metacognition model generated during the study does not have statistical
generalisability (Yin, 1994). However, as was noted earlier in Section 7.2, the
theoretical propositions subsumed within the model have analytical
generalisability. Thus, it can be argued that the outcomes of the study have
analytical generalisability.
There are also limitations concerning the role of the researcher as
participant. The nature of the design research methodology used in this study is
that the design experiment is set up and implemented by the researcher. To
overcome this limitation Bereiter (2002) suggested that the research design
methodology requires ongoing collaboration with the teachers involved. A good
rapport was established between the researcher, the classroom teachers, and the
students. The classroom teachers in this study approved the activity, provided
information about the class, and helped form the groups.
A further limitation to this study was the failure to withdraw scaffolds
once the group metacognitive processes involved had been internalised. Scaffolds
are temporary supports which should be gradually decreased as the groups
competence increases (King, 1989; Vygotsky, 1978). Due to the limited duration
of the study, the scaffolds were not withdrawn as the groups were still
internalising the process. However, the groups involved in the study showed that
they were developing a shared internal understanding of both the task and team
aspects of their group work. The development of the within-group metacognition
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also negated the need for between-group online metacognitive scaffolds as the
primary school groups working face-to-face were able to transfer their shared
understandings to the online context.
Another limitation of the research study was that the study did not
generate principles to inform the advancement of the design of tools to scaffold
the development of organisational, cognitive, and group metacognitive strategies
and skills. The tools utilised in this study were derived from previous research
studies. During the course of the study, the researcher noted limitations in many
of these scaffolding tools. Many of these limitations can probably be traced back
to the limitations of the theories on which these tools were based. Research that
advances theory underlying many of these scaffolding tools is needed.
7.4 Recommendations for further research
Further research needs to address group metacognition as a process of
planning, monitoring, and evaluating shared group understandings of the task and
team aspects of effective groups. While this study addresses this issue to a certain
extent, group metacognition requires further study and has implications for a
range of educational settings. Further research could focus on different
educational levels, including secondary and tertiary, in order to demonstrate if the
results presented in this research study can be replicated.
Aspects of the group metacognition model have implications for the
design of CSCL environments. The organisational, cognitive, and metacognitive
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factors identified in the final model need to be further investigated. They also
need to be tested and refined in other group-based situations. Future research
should also focus on the development of sets of principles to inform
advancements in the design of scaffolding tools such as the posters, group diaries,
and metacognitive checklists utilised in this study.
7.5 Conclusion
Within the research literature, there is a general consensus that group
metacognitive activities such as planning how to approach a given learning task,
monitoring progress, and evaluating progress toward the completion of the task
play critical roles in successful group learning and problem solving. There is also
a general consensus within the research literature that metacognitive activities of
planning, monitoring, and evaluating need to be scaffolded. However, prior to this
research study, there were limitations in the corpus of knowledge about the
scaffolding of group metacognition; most of the current knowledge in this field
tended to be fragmented, seemingly inconsistent, and compartmentalised in
nature. For example, knowledge about planning, monitoring, and evaluating team
aspects of group problem solving rarely has been integrated with knowledge
about planning, monitoring, and evaluating task aspects of group problem solving.
Furthermore, integration with respect to problem contexts and organisational,
cognitive, and metacognitive factors is not evident in the current corpus of
research literature.
230
The major outcome of this study, the group metacognition model,
integrated key components of the field, namely complex problem-solving
contexts, organisational factors, cognitive factors, and metacognitive factors, into
a unified conceptual model. This model advances the field in at least two ways.
First, the unified model provides researchers and practitioners with a framework
to gain a holistic and better understanding of the corpus of previous research
knowledge in the field of scaffolding group metacognition. Second, the model
also provides researchers and practitioners with a conceptual framework and four
sets of conceptual artefacts to inform future research and practice, and thus
advance the corpus of knowledge about scaffolding within- and between-group
metacognition in CSCL environments.
231
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APPENDICES
APPENDIX A: Checklist to observe group behaviour
Group Members Group Skills
Checks group understanding
Gives ideas
Shares information
Talks about the work
Gets group back to work
Repeats what has been said
Asks questions
Encourages
Checks for agreement
Encourages others to talk
Responds to ideas
Uses eye contact
Says ‘Thank you’
Shares feelings
Disagrees in a nice way
Keeps things calm
Total
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APPENDIX B: Metacognitive questionnaire
NO –No, I didn’t do this. MAYBE-I may have done this. YES-Yes, I did do this. NO MAYBE YES BEFORE YOU BEGAN TO SOLVE THE PROBLEM-WHAT DID YOU DO?
1. I read the problem more than once. 2. I thought to myself, do I understand what the
problem is asking me?
3. I tried to put the problem into my own words. 4. I tried to remember if I had worked a problem like
this before.
5. I thought about what information I needed to solve this problem.
6. I asked myself, is there information in this problem that I don’t need?
AS YOU WORKED ON THE PROBLEM-WHAT DID YOU DO?
7. I thought about the steps as I worked the problem. 8. I kept looking back at the problem after I did a step. 9. I had to stop and rethink a step I had already done. 10. I checked my work step by step as I worked the
problem.
11. I did something wrong and had to redo my step(s). AFTER YOU FINISHED WORKING THE PROBLEM-WHAT DID YOU DO?
12. I looked back to see if I did the correct procedures. 13. I checked to see if my calculations were correct. 14. I went back and checked my work again. 15. I looked back at the problem to see if my answer
made sense.
16. I thought about a different way to solve the problem.
DID YOU USE ANY OF THESE WAYS OF WORKING?
17. I drew a picture to help me understand the problem. 18. I guessed and checked. 19. I picked out the operations I needed to do this
problem.
20. I felt confused and could not decide what to do. 21. I wrote down important information.
Fortunato et al., (1991)
263
APPENDIX C: Self regulatory checklist
Planning 1. What is the nature of the task?
2. What is my goal?
3. What kind of information and strategies will I need?
4. How much time and resources will I need?
Monitoring 1. Do I have a clear understanding of what I am doing?
2. Does the task make sense?
3. Am I reaching my goals?
4. Do I need to make changes?
Evaluation 1. Have I reached my goal?
2. What worked?
3. What didn't work?
4. Would I do things differently next time?
Schraw (2001)
264
APPENDIX D: Interview questions
Initial questions Intermediate questions Ending Questions
1. Tell me about what happened 2. When, if at all, did you first experience/notice…? 3. (If so,) What was it like? What did you think then? How did you happen to? Who, if anyone, influenced your actions? Tell me about how he/she or they influenced you. 4. Could you describe the events that led up to … 5. What contributed to..? 6. How would you describe how you viewed…before… happened? How, if at all, has your view of … changed? 7. How would you describe the person you were then?
1. What, if anything did you know about...? 2. Tell me about your thoughts and feelings when you learned about… 3. What happened next? 4. Who, if anyone, was involved? When was that? How were they involved? 5, Tell me about how you learned to handle… 6. How, if at all, have your thoughts and feelings about … changed since? 7. What positive changes have occurred since…? 9. Tell me how you go about… What do you do? 10. Could you describe the most important lessons you learned about … through experiencing…? 11. What helps you to manage…? What problems might you encounter? Tell me the sources of these problems. 12. Who has been most helpful to you during this time? How has he/she been helpful?
1. What do you think are the most important ways to…? How did you discover (or create) them? How has your experience before affected how you handled…? 2. Tell me about how your views may have changed since you have…? 3. Tell me about your strengths that you discovered or developed through… 4. After having these experiences, what advice would you give to someone who has just discovered that he or she…? 5. Is there anything that you might not have thought about before that occurred to you during this interview? 6. Is there anything you would like to ask me?
Charmaz (2003)
265
APPENDIX E: Initial individual questionnaire
1. What is a group?
2. What do you like about working in a group?
3. What do you not like about working in a group?
4. Where did you learn to work with other people?
5. What advice would you give to someone who has just discovered that they will be working in a group?
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APPENDIX F: Final individual questionnaire
1. What did you like about the group work?
2. What did you not like about the group work?
3. What do you feel was easier to understand or learn in your group?
4. What do you feel would have been easier to understand or learn on your own?
5. What would you change about the group?
6. What advice would you give to someone who has just discovered that they will be working in a group?
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APPENDIX G: Group cohesiveness questionnaire
NAME
Strongly Agree Agree Neutral Disagree
Strongly Disagree
I'm glad I belong to this group I feel held back be this group I am an important part of this group I don't fit in with other kids in this group I feel strongly tied to this group I don't think the group is that important I think this group worked well together I don't feel comfortable with the other kids in this group
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APPENDIX H: Lesson plan
Learning outcomes
Data CD 3.2 Students design and trial a variety of data collection methods and use existing sources of data to investigate their own and others’ questions, organise data and create suitable displays, identifying and interpreting elements of the displays.
CD 4.2 Students plan and carry out data collections using their own data record templates; choose and construct appropriate displays and make comparisons about the data based on the displays and measures of location.
CD 5.2 Students plan investigations involving discrete and continuous data, produce and compare data displays involving grouping, and compare measures of location.
Investigation Last week, (5 October, 2005) the London-based Economic Intelligence Unit released their
ranking of the top cities to live. Melbourne was the top Australian city, then, Sydney, Perth –
Brisbane was rated number 11. However, the Economic Intelligence Unit didn’t include
categories that children may think are important.
Students need to decide what information is important in ranking cities in Australia according
to the liveability and how they can collect and present the information. Throughout this
activity students will be working in cooperative groups of 3 students. Using the Internet, they
will learn gather data about Australian cities. To organise the data, the students will use
EXCEL. The groups will use the Knowledge Forum database to share information as well as
discuss and revise their solution. They will also give feedback to other groups on the online
database. The final solution will be presented a word document –Newspaper format.
269
Identifying and describing
Overview of activity Students: discuss the requirements of investigation identify the data to collect determine how data will be collected design data collection template Level Three Level Four Level Five Students: know that data collection is
used to investigate questions design data collection
methods to investigate questions
create suitable data displays know the elements of data
displays interpret data displays using
elements of displays.
Students: know data collection is
planned to investigate particular situations
plan and carry out data collections
design data record templates compare data based on
displays
Students: know data collection is
planned to investigate particular situations
plan investigations compare grouped data
Understanding and applying
Students: carry out data collections using
data record templates record data construct data display using
excel
Communicating and justifying
Students:
generate, discuss the data, and compile a report
report findings to the class
Thinking, reasoning and
working mathematically
270
Lesson sequence Anticipated evidence
Introducing the investigation Students discuss the requirements of the investigation
and determine that data will need to be collected. Students form groups. Groups brainstorm the types of data they need to fill
their categories: - the climate –temperature, rainfall,
humidity - recreational activities of the students –
parks, sports, scouts, guides, holiday clubs.
- tourist attractions in the local area –Beaches, fun parks.
Students will:
decide what data they will need to collect (they may decide to collect data about recreational activities and the temperature)
determine how they will collect the data. Will it be from existing data sources, or will they need to collect the data themselves?
identify categories for data, and design data record templates.
know data collection is planned to investigate particular situations (Level 3/4/5) plan and carry out data collections design data record templates
271
Lesson sequence Anticipated evidence
Exploring data Students carry out data collections using data record
templates. Students will: enter data onto a spreadsheet and compare and analyse
data construct data displays using the data they have
gathered and the ways it has been classified.
compare data based on displays know ways of displaying data for comparison compare grouped data
Lesson sequence Anticipated evidence
Making judgments using data using the data that has been collected throughout the
course of the activity – students interpret data and compile a report.
students use data collected to inform about most liveable city.
the report to will be presented for editing, and will be presented to the class.
compare data based on displays (Level 4)
272
Contributions to the valued attributes of a lifelong learner Through engagement with activities in this module, students develop the following attributes:
Knowledgeable person with deep understanding understands the purpose for collecting data makes judgements on data collected Complex thinker analyses and organises information Active investigator uses data collection to investigate questions accesses information from a variety of sources Effective communicator presents data collections to others uses data as a means of communicating information Participant in an interdependent world works in groups and acknowledges the ideas of others Reflective and self directed learner looks for and recognises ways of “working mathematically” in everyday life
Procedure:
Day 1
Introduction Talk about research and what I do. Introduce the idea of working in groups or teams. Introduce Rainbow Book with group roles and skills. Group roles –how they will change weekly –not always on the computer-everyone should get a chance to do each role –one person today can be the recorder. Go through skills, strategies, problem-solving, and group skills from book. Discuss what other strategies/skills students have used on problems. Present problem Read Newspaper article Sun/Herald. Introduce CNN site and their ranking system Students will brainstorm –categories can use –Write up a few ideas on the board. Brainstorm in groups. Write all ideas down –on red pages in Rainbow book. Introduce Planning sheet in Rainbow Book –on orange pages in Rainbow book. In group work out who will be doing each role (remember they will be changed next week). Choose a recorder and help the recorder complete planning sheet in the rainbow book. Come up with team name and password. Write in Rainbow book. Collect books. Discuss other categories groups thought were important and why –asking the encourager/checker. Ext: Demonstrate how to set up Excel to organise data –Cities, ranking. Ext: Demonstrate Knowledge Forum.
273
Day 2
Distribute rainbow books and remind students to change group roles next time on computer and to record in book so that no arguments about who has next turn. Introduce Knowledge Forum -Written guidelines for using Knowledge Forum provided for the students to refer to. Demonstrate how to use Excel to organise data –Cities, ranking –need to decide what ranking you give each category eg. Out of 10 –Lots of parks 10, no parks 0 -written guidelines for using EXCEL will be provided for the students to refer to. Model how to evaluate some sites with students. Discussion will include the validity of websites and the need to find information by using appropriate websites to find data. Students will then review at least three sites – demonstrate how to gather data and complete information sheet Web Resources The students will select those websites from this list which are relevant to their project: (This will depend on students’ rankings from day 1). Groups also need to read other groups Knowledge Forum notes and write back to welcome note. Complete yellow monitoring sheet in rainbow book –how well group working together, what needs to change?
Day 3 & 4
Complete ranking system and review and model how to import Excel onto Knowledge Forum –also show how to add comments to Excel sheet in order to justify reasons why cities are ranked accordingly.
Model Feedback –Praise, comment, suggestion.
Day 5 & 6
Read Knowledge Forum note from groups and finalise overall ranking system.
What is the best city in Australia to live? Explain your system of ranking the cities, why it is a good system and how your ranking system could be used to rank other cities in the world in terms of liveability.
Follow-up
In discussion and writing, students will reflect on project in Rainbow Book -Complete group evaluation and reflection. Complete final individual questionnaires and group metacognitive questionnaire.
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APPENDIX I: City information
Adelaide Categories Indicators Information Rating
Population 1,100,000
Climate
Maximum average temperature 21.4 °c
Minimum average temperature 11.2 °c
Average rainfall per year 450 mm
Crime Murder per 100,000 persons 5.9
Economy Major industries Manufacturing, refining
Cost of living Not rated
Attractions
Natural
Kilometers of beaches, Lots of parks City is surrounded by parkland
Tourist Coastal beaches and the Mount Lofty Ranges
Stadiums
AAMI -51,515 (sc), Entertainment Centre- 11,000 (sc), Adelaide Oval- 33,597 (sc), Prospect Oval- 20,000 (sc)
Cost of living rating
Rating of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
275
Brisbane Categories Indicators Information Rating
Population 1,627,000
Climate
Maximum average temperature 25.4°c
Minimum average temperature 15.75°c
Average rainfall per year 1152
Crime murder per 100,000 persons 5.1
Economy Major industries Mining, tourism, agriculture
Cost of living 84/100
Attractions
Natural Morteon Bay, islands, parks
Tourist Southbank Gold Coast in the south and the Sunshine Coast in the north
Stadiums
Ballymore -24,000 (sc), Entertainment Centre – 13,500 (sc), Exhibition ground -25,490, Gabba -37,600, QE11 Stadium -49,000 (sc), Suncorp Stadium -52,579 (sc)
Cost of living rating
Rating of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
276
Canberra Categories Indicators Information Rating
Population 304,000
Climate
Maximum average temperature 19.5°c
Minimum average temperature 6.5°c
Average rainfall per year 630 mm
Crime murder per 100,000 persons 1.9
Economy
Major industries Federal government, public administration, manufacturing, education, tourism, IT
Cost of living 45/100 (45th out of the 100 most expensive cities to live).
Attractions
Natural No beaches, Lots of parks.
Tourist Parliament House, War Memorial, National Gallery, Old Parliament House.
Stadiums AIS -5050 seating capacity, Canberra Stadium -24,647 (sc), Manuka Oval -15,000.
Cost of living rating
Rating of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
277
Darwin Categories Indicators Information Rating
Population 80,000
Climate
Maximum average temperature 32.5 °c
Minimum average temperature 23.6 °c
Average rainfall per year 1570 mm
Crime murder per 100,000 persons 8.5
Economy Major industries Rural, hospitality, tourism
Cost of living Not rated
Attractions
Natural Harbor twice the size of Sydney 20 parks and nature reserves
Tourist
Stadiums Marrara Hockey -10,000 ( sc), Marrara Stadium - !5, 000 (sc)
Cost of living rating
Rating of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
278
Hobart Categories Indicators Information Rating
Population 193,500
Climate
Maximum average temperature 16.7 °c
Minimum average temperature 8.2 °c
Average rainfall per year 626 mm
Crime murder per 100,000 persons 3.7
Economy
Major industries
Tourism, meatpacking, food processing, and the making of textiles, chemicals, and glass
Cost of living 99/100
Attractions
Natural
Tourist
Stadiums
Bellerive Oval- 16,000 (sc), North Hobart-18,000, Queenborough Oval-8,000 (sc), TCA-8,000 (sc)
Cost of living rating
Rating of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
279
Melbourne Categories Indicators Information Rating
Population 3,200,000
Climate
Maximum average temperature 19.8 °c
Minimum average temperature 10. °c
Average rainfall per year 660 mm
Crime murder per 100,000 persons 3.1
Economy
Major industries
Tourism, mining, food processing, chemicals, steel, industrial and transport
Cost of living 68/100
Attractions
Natural
Melbourne is on the bank of the Yarra River and is five kilometres from Phillip Bay
Tourist Trams,
Stadiums
Raceway- 44,000(sc), McHale Stadium- 27,000, Melbourne Cricket Ground- 100,000, Optus Oval- 35,000, Telstra Dome- 56,347
Cost of living rating
Rating of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
280
Perth Categories Indicators Information Rating
Population 1,223,000
Climate
Maximum average temperature 23.6 °c
Minimum average temperature 13.3 °c
Average rainfall per year 869 mm
Crime murder per 100,000 persons 3.8
Economy Major industries
Tourism, agriculture, mining, horticulture
Cost of living 93/100
Attractions
Natural Fabulous beaches, National Parks
Tourist
Stadiums
East Freemantle Oval 25,00 (sc), Perry Lakes Stadium- 30,000 (sc), Freemantle Oval- 17,500(sc), Entertainment Centre- 8,200 (sc), Subiaco Oval- 42,922 (sc)
Cost of living rating
Rating of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
281
Sydney Categories Indicators Information Rating
Population Number of people 4,600,000
Climate
Maximum average temperature 21.6 °c
Minimum average temperature 13.5 °c
Average rainfall per year 1226 mm
Crime murder per 100,000 persons 3.4
Economy Major industries
Agriculture, manufacturing, mining
Cost of living 20/100
Attractions
Natural National Parks, Sydney Harbor
Tourist Botanic Gardens Harbor Bridge, Opera House.
Stadiums
Aussie Stadium- 40,792 (sc), Hensen Park- 30,000 (sc), Sydney Cricket Ground- 44,000, Entertainment Centre- 10,500, Showground -21,000, Telstra Stadium- 83,500
Cost of living rating
Rating out of 100 most expensive cities to live in the world.
Stadiums (sc)-seating capacity.
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APPENDIX J: Newspaper article
Melbourne rated only the second best Jane Metlikovec 05oct05
MELBOURNE is still the best city in Australia, but has lost its world title after two years at the top. Vancouver has pipped Melbourne as the world's most liveable city by only 1 per cent, according to an annual survey of 127 cities. The London-based Economic Intelligence Unit based its rankings on stability, health care, culture and environment, education and infrastructure.
A low threat of terrorism and good health and education systems saw Melbourne rank
second to Vancouver, beating rival Sydney, which polled equal fifth with Adelaide and Perth.
Brisbane was the only major Australian city to miss out on the Top 10, coming eleventh.
Editor of the survey Jon Copestake said it was not surprising Western cities dominated the top rankings.
"In the current global political climate, it is no surprise that the most desirable destinations are those with a lower perceived threat of terrorism," Mr Copestake said.
Port Moresby, the crime-ridden capital of Papua New Guinea, ranked as the worst city in the world for its high level of corruption, crime rates and low availability of entertainment.
Metlikovec, Jane, Melbourne rated only the second best. Herald and Weekly Times, http://www.heraldsun.news.com.au/common/story_page/0,5478,16817534%255E2862,00.html Accessed: 7/10/05.
283
APPENDIX K: Group roles, skills, and problem-solving strategies
Group skills Task (What) Team (How)
Check group
understanding. Give ideas. Share information. Talk about the work. Get group back to work. Repeat what has been
said. Ask questions.
Encourage. Check for agreement. Encourage others to talk Respond to ideas. Use eye contact. Say ‘Thank you’. Share feelings. Disagree in a nice way. Keep things calm.
Group roles
Task roles Team roles
Keyboarder/Checker - seek opinions and information, summarise ideas.
Coordinator/Recorder - organise, give information and opinions, elaborate on ideas, follow group plan.
Encourager/Moderator - encourage participation, manage conflict, encourage harmonious discussion, support decisions, spokesperson for group.
Problem-solving strategies
Strategy How
Draw Solve by drawing model/diagram.
Small Simplify the problem using small numbers.
Parts Solve part(s) of the problem first.
Before List information given before and after the action; compare the information to the unknown.
Backwards Solve by working backwards.
284
APPENDIX L: Group diary checklists
PLANNING What do we know about the problem?
(What information is needed?)
What is the goal?
What is our plan to solve the problem and reach the goal? (What strategies can be used?)
What group roles will we use? Name: Group role: Name: Group role: Name: Group role:
What group skills will we use?
Task (What) Team (How)
285
MONITORING
Are we following the group plan?
Do we need to make changes?
What group roles will we use? Name: Group role: Name: Group role: Name: Group role:
What group skills will we use? Task (What) Team (How)
Looks Like Sounds Like Looks Like
Sounds Like
What are 2 things your group is doing well and 1 thing that needs
to improve? (Eg. contributing ideas, encouraging participation, checking for understanding, and keeping things calm) The group is doing well …
The group is doing well …
The group is doing well …
The group needs to improve …
286
MONITORING 2 Group Roles
Group Role Name
Keyboarder/Checker
Coordinator/Recorder
Encourager/Moderator
Group Skills
Task Team
Best City
What group skills will we use on Knowledge Forum? (Eg. give ideas, share information, encourage participation, check for agreement, and respond to ideas.)
Category:
City Ranking
Adelaide
Brisbane
Canberra
Darwin
Hobart
Melbourne
Perth
Sydney
We ranked this city as number 1 because:
287
EVALUATING
Have we reached our goal?
What worked?
What didn't work?
What would we do differently next time?
How can we improve: o The Rainbow book?
o Knowledge Forum?
288
APPENDIX M: Final overall ranking system: Cycle 1
289
290
APPENDIX N: T-chart
Group skill
Looks Like
Sounds Like
291
APPENDIX O: Knowledge Forum guide
Sign on to Knowledge Forum
-Select the PAKSTEM database.
-Enter team User Name
-Enter team Password
-Click Sign On
Build-on notes
-Click on the note you want to build on.
-Click the button.
-A new note will open.
-Type your new note.
-Click on Close and Contribute.
(If you just click Close the note will not be added).
292
Create a new note -Click the new note button. -Maximise note window. Title the note
-Type a heading for your note. Adding a scaffold
-Select a scaffold. -Click on the Add button. Adding ideas
-Place the cursor in between the > < signs. -Type your note. Contribute ideas -Click the Close and Contribute button.
293
APPENDIX P: Group categories
Group Group diaries Knowledge Forum A clean ivienment (environment) nice
parks good egecashon (education) Clean environment, nice parks, and food education, health.
B skateboarding and chilling out, laser skirmish
Skate boarding and chilling out laser skirmish
C draw a chart part Education, environment and pollution. D Theme parks, sports, public health
system, infastructure. Sport, public health system and education, Facilities
E Get information -Use to find top 8 -Which is best
Shopping, showgrounds, food, transport, main attractions, theme parks, education, sports, health, facilities
F health, neighbours, pets, egication (education), comunity, shopping, beauty, weather, parks, goverment, food, water.
Shopping beauty neighbours food water parks school community pets health weather and government
G Shopping, movies, theme parks, foodcourt, park, sports
Shopping movies theme parks food court park sports and computers
H The population, environment, wild life, food, theame parks, buildings, edgucation.
Population, environment, wild life, food and drinks, theme parks, buildings and education.
I Sports, education, health, wildlife, foods and drinks
J Adresher (Adventure) parks, shops. Adventure parks, shops to rank K Sport, trees, shop, rivers, school,
buildings, food, culture, money, weather
Sports, population, pollution, schools, culture, buildings and shops
L 8 citys sports Sport’s M Use computer Sports, main attractions, health,
environment, energy saving cities, wildlife
N Theme parks, transport, safety, lifestyle, shopping, real estate, education, population, hospitals
Theme Parks, Transport, Safety, Lifestyle, Shopping, Real Estate, Education and Population.
O Wild life, buildings, food and drink, and population
Wildlife, buildings, food and water ,parks and population
P sport Art Showers gardens, trees, water, food.
Sports, art, gardens, food and water
294
APPENDIX Q: List of categories
Adventure parks Art Beauty Community Culture Education Environment Facilities Food Food courts Gardens Government Health Hospitals Infrastructure Lifestyle Main attractions Money Movies Neighbours Parks Pets Pollution Population Public health system Rain Real estate Rivers Safety Shopping Show grounds Sports Theme parks Transport Weather Wildlife
295
APPENDIX R: CD: Australia’s best city
Australia's best city Adelaide Brisbane Canberra Darwin Hobart Melbourne Perth Sydney
Our Categories
Adventure Movies
Art Pollution
Attractions Population
Beauty and Health Rain
Culture Real estate
Economy Safety
Food Shopping
Gardens and Parks Sports
Government Theme parks
Health System Transport
Hospitals Weather
296
APPENDIX S: Excel guide
Entering Data Click on a cell to make it active. Type in your data and press Enter.
Selecting Data Click on a cell and drag the pointer so all data is selected.
Sorting Data
Select the columns to be sorted. Click on Data on the menu bar, and select Sort.
Sort by
Sort by column to be ranked (e.g. population) Click OK.
Writing Formulas
Click on a cell and type = + Addition -B2+C2+D2 - Subtraction; e.g. A5–B5 * Multiplication; e.g. D1*D2 / Division; e.g. B2/A3
Clicking in cell B2 displays B2 in the equation.
Using the Fill Handle
Position the pointer in lower-right corner of cell until it changes into a small +
Drag + to select cells
The formula is copied to the cells selected.
297
APPENDIX T: Final CD: Cycle 1
Brisbane is Australia's best city Adelaide Brisbane Canberra Darwin Hobart Melbourne Perth Sydney
We found out the best city was........... Brisbane!!!!!!!!!!!!!!!!!!!!!!
Our best city is Brisbane because we have found that Brisbane has the best stuff and because it has more places than other cities. We think Brisbane is the cleanest, it has a nice mix of culture, beautiful attractions, and the best theme parks!
Our Categories
Adventure Movies
Art Pollution
Attractions Population
Beauty and Health Rain
Culture Real estate
Economy Safety
Food Shopping
Gardens and Parks Sports
Government Theme parks
Health System Transport
Hospitals Weather
Our Ranking system
Links
298
APPENDIX U: Bales’ Interaction Process Analysis
(IPA) Behaviours Row Total 1. Seems friendly, raises other’s status, gives help, reward
2. Dramatises, jokes, laughs, shows satisfaction
3. Agrees, shows passive acceptance, understands, concurs, complies
4. Gives suggestion, direction, implying autonomy for other
5. Gives opinion, evaluation, analysis, expresses feeling, wish
6. Gives information, repeats, clarifies, confirms
7. Asks for information, repetition, confirmation
8. Asks for opinion, evaluation, analysis, expresses feeling
9. Asks for suggestion, direction, possible ways of action
10. Disagrees, shows passive rejection, formality, withholds help
11. Shows tension, asks for help, withdraws
12. Seems unfriendly, deflates other’s status, defends or asserts self
Column Total
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APPENDIX V: Group metacognition coding
Coded Checklist Text
Planning 1
Planning 2
Planning 3
What is the nature of the task?
What is the goal?
What kinds of strategies are
needed?
Coded Checklist Text
Monitoring 1
Monitoring 2
Monitoring 3
Clear understanding of what we
are dong
Does the task make sense?
Are we reaching our goals?
Coded Checklist Text
Evaluation 1
Evaluation 2
Evaluation 3
Evaluation 4
Have we reached our goal?
What worked?
What didn’t work?
Would we do things differently
next time?
300
APPENDIX W: Mathematical model for Team One
Team One (Group A, B, C).
Group A (Team One)
301
Group B (Team One)
Group C (Team One)
302
APPENDIX X: Posters
TEAM SKILLS POSTER
The team The work Encourage encourage
others to talk encourage
others to listen
Ideas give ideas repeat ideas respond to
ideas
Be positive say ‘thank you’ use eye contact say positive
things
Share information seek ideas search for new
information
Check for agreement manage conflict keep things
calm
Check understanding ask questions talk about the
work
303
GROUP ROLES POSTER
Team roles Work roles Encourager encourage some
to talk encourage
others to listen
Keyboarder give ideas repeat ideas respond to
ideas
Manager be positive manage conflict share positive
feelings
Coordinator seek ideas search for new
information
Checker check for
agreement manage conflict keep things
calm
Recorder check for
understanding ask questions talk about the
work
304
PROBLEM-SOLVING POSTER
Make a list Draw a picture
Guess and check Work backward
Make a table Choose an
operation
Find a pattern Check solution
305
CONFLICT MANAGEMENT POSTER
Listen to each other
Try to understand
everyone’s point of view
Give everyone a
chance to speak
Discuss solution paths
Get help if needed
306
APPENDIX Y: IPA Coding for each group
Group A
Figure Y1 shows that Group A has a higher number of task-related
communication (74.7%) than team-related communication (25.3%). The task-related
communication domain includes the categories, gives suggestion, gives opinion, gives
information, asks for information, asks for opinion, and asks for suggestion. While the
team-related domain includes the categories, seems friendly, dramatises, agrees,
disagrees, shows tension, and seems unfriendly.
24.9
57.8
16.9
0.40
10
20
30
40
50
60
70
1.- 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
quen
cy (%
)
Figure Y1. IPA domain frequencies for Group A.
The IPA category frequencies for Group A are shown in Table Y1. As can be
seen in this table the categories with the highest total frequency counts are gives
information (38.8%), agrees (21.1%), and gives suggestion (11.8%). The category
gives suggestions is coded for behaviour or acts that include giving suggestions,
giving direction or implying autonomy for other students. The category gives
information is coded for behaviours or acts that include giving information, repeating
what has been said, and clarifying or confirming what has been said. The categories
307
with the lowest frequency counts, with no behaviours observed or coded, are
dramatises, disagrees, and seems unfriendly.
Gives suggestions is the highest category in session 4 while the category gives
information is the highest in all the other sessions. An example of gives information
from session 1 was when groups were selecting a category to rank the major cities:
That's when you, when people are healthy and be healthy (Student 3).
The category agrees is higher in sessions 2 and 3 than the gives suggestions
category. The category agrees is coded for behaviours or acts that show agreement,
passive acceptance, understanding, concurring or compliment. An example of agrees
from session 2 was when groups were asked to place the categories they were going
to rank their cities on to the Knowledge Forum ® database:
OK (Student 1)
The behaviour of shows tension (0.4%) was coded in session 3. Behaviours in
this category include asking for help or withdrawing from the group. An example of
shows tension from session 3 was when groups were writing in their diary:
I need your help (Student 2).
308
Table Y1 IPA Frequency Count for Each Category for Group A
Categories Session
1
Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 2 5 0 0 7 3
2. Dramatises 0 2 0 0 2 0.8
3. Agrees 6 10 31 3 50 21.1
4. Gives suggestion 7 8 6 7 28 11.8
5. Gives opinion 2 7 8 0 17 7.2
6. Gives information 14 38 36 4 92 38.8
7. Asks for information 5 6 4 1 16 6.8
8. Asks for opinion 5 3 5 0 13 5.5
9. Asks for suggestion 5 5 1 0 11 4.6
10. Disagrees 0 0 0 0 0 0
11. Shows tension 0 0 1 0 1 0.4
12. Seems unfriendly 0 0 0 0 0 0
Total 46 84 92 15 237 100
309
Group B Figure Y2 shows that Group B has a higher number of task-related
communication (77.1%) than team-related communication (22.9%).
16.3
55.4
21.7
6.6
0
10
20
30
40
50
60
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y2. IPA domain frequencies for Group B.
The IPA category frequencies for Group B are shown in Table Y2. As can be
seen in this table the categories with the highest total frequency counts are gives
suggestion (27.1%), gives information (17.4%), and asks for suggestion (12.8%). The
categories with the lowest frequency counts, with no behaviours observed or coded, is
seems friendly.
Gives suggestion is the highest category in session 2 and 4, while gives
information is the highest category in session 3. An example of gives suggestion from
session 2 was when groups were introducing themselves to other groups on
Knowledge Forum ®:
Yeah I want to say something like I heard something about your school
I heard it is pretty good, I have (Student 1)
310
An example of gives information from session 4 was when groups were
selecting a category to rank the major cities:
You can only choose one (Student 2).
The behaviour of seems unfriendly (2.7%) was coded in sessions 2 and 3.
Behaviours in this category include seeming unfriendly, deflating other’s status, and
defending or asserting oneself. An example of seems unfriendly was when groups
were developing their ranking models:
Are you doing any of the work? (Student 2).
311
Table Y2
IPA Frequency Count for Each Category for Group B
Categories Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 0 0 0 0
2. Dramatises 2 6 2 10 3.9
3. Agrees 10 11 11 32 12.4
4. Gives suggestion 22 16 31 70 27.1
5. Gives opinion 5 16 7 28 10.9
6. Gives information 12 22 11 45 17.4
7. Asks for information 5 4 4 13 5.0
8. Asks for opinion 3 5 2 10 3.9
9. Asks for suggestion 6 7 20 33 12.8
10. Disagrees 5 3 2 10 3.9
11. Shows tension 1 0 0 0 0
12. Seems unfriendly 4 3 0 5 2.7
Total 75 93 90 258 100
312
Group C Figure Y3 shows that Group C has a higher number of task-related
communication (78.8%) than team-related communication (21.2%).
19.5
59.8
19.0
1.7
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y3. IPA domain frequencies for Group C.
The IPA category frequencies for Group C are shown in Table Y3. As can be
seen in this table the categories with the highest total frequency counts are gives
opinion (25.9%), gives information (19%), and gives suggestion (14.9%). Gives
opinion was coded for behaviours that include evaluation, analysis, or an expression
of feeling or a wish. The categories with the lowest frequency counts, with no
behaviours observed or coded, are seems friendly and seems unfriendly.
Gives opinion is the highest category in session 3 and 4, while gives
suggestion is the highest category in session 1 and 2. An example of gives opinion
from session 3 was when groups were developing their ranking models of the top
cities in Australia:
313
I think a good city would have lots of good schools and parks, good
committees and groups, good theatres umm beautiful parks that's what
I think would make a good city (Student 2).
The behaviour of shows tension (0.6%) was coded in session 1. An example of
shows tension was when groups were sending their welcome notes to Knowledge
Forum:
Do you have anything to say? Gave no answer [this was said aloud]
(Student 1)
314
Table Y3 IPA Frequency Count for Each Category for Group C
Categories Session
1
Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 0 0 0 0 0
2. Dramatises 0 0 11 4 15 8.6
3. Agrees 1 1 15 2 19 10.9
4. Gives suggestion 9 4 6 7 26 14.9
5. Gives opinion 4 0 33 8 45 25.9
6. Gives information 6 1 18 8 33 19.0
7. Asks for information 3 2 6 1 12 6.9
8. Asks for opinion 1 1 10 3 15 8.6
9. Asks for suggestion 2 1 3 0 6 3.4
10. Disagrees 1 0 1 0 2 1.1
11. Shows tension 1 0 0 0 1 0.6
12. Seems unfriendly 0 0 0 0 0 0
Total 28 10 103 33 174 100
315
Group D Figure Y4 shows that Group D has a higher number of task-related
communication (77.2%) than team-related communication (22.8%).
21.6
51.5
25.7
1.20
10
20
30
40
50
60
1.- 3. 4. - 6. 7. - 9. 10. -12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y4. IPA domain frequencies for Group D.
The IPA category frequencies for Group D are shown in Table Y4. As can be
seen in this table the categories with the highest total frequency counts are gives
information (21.6%), gives opinion (19.9%), and agrees (14%). The category with the
lowest frequency count, with no behaviours observed or coded, is shows tension.
Gives information is the highest category in session 3 and 4, while gives
opinion is the highest category in session 2. An example of gives information
suggestion from session 4 was when groups were working on their ranking models:
Adelaide got first in the food (Student 2).
The behaviours of seems unfriendly (0.6%) and disagrees (0.6%) were coded
in sessions 2 and 3. The category disagrees was coded for behaviours or acts that
show disagreement, passive rejection, formality or withholding help. An example of
316
disagrees from session 3 was when groups were working on their ranking system for
the top cities in Australia:
Hobart's third (Student 1) (Gives opinion)
I just said Adelaide was third (Student 2) (Disagrees).
Table Y4 IPA Frequency Count for Each Category for Group D
Categories Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 3 0 3 1.8
2. Dramatises 0 2 8 10 5.8
3. Agrees 1 18 5 24 14.0
4. Gives suggestion 4 13 0 17 9.9
5. Gives opinion 10 15 9 34 19.9
6. Gives information 3 19 15 37 21.6
7. Asks for information 1 13 6 20 11.7
8. Asks for opinion 1 3 7 11 6.4
9. Asks for suggestion 5 4 4 13 7.6
10. Disagrees 0 1 0 1 0.6
11. Shows tension 0 0 0 0 0
12. Seems unfriendly 1 0 0 1 0.6
Total 26 91 54 171 100
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Group E
Figure Y5 shows that Group E has a higher number of task-related
communication (78.3%) than team-related communication (21.7%).
18.4
56.6
21.7
3.3
0
10
20
30
40
50
60
1.- 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y5. IPA domain frequencies for Group E.
The IPA category frequencies for Group E are shown in Table Y5. As can be
seen in this table the categories with the highest total frequency counts are gives
information (23.2%), gives suggestion (17.4%), gives opinion (15.9%), and agrees
(15.7%). The category with the lowest frequency count, with no behaviours observed
or coded, is seems unfriendly.
Gives information is the highest category in session 2 and 4, while agrees is
the highest category in session 3. An example of gives information from session 2 was
when groups were working on their ranking models:
Our plan is to get information to use to find the top eight which is the
best (Student 1)
318
An example of agrees from session 4 was when groups were placing the
categories they had ranked on to the Knowledge Forum ® database:
Yeah, that definitely needs a hospital (Student 2).
The behaviour of shows tension (1%) was coded in sessions 2 and 4. An
example of shows tension from session 4 was when groups were allocating group
roles to each member of the group:
We're trying to tell you but you weren't listening to us (Student 2).
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Table Y5 IPA Frequency Count for Each Category for Group E
Categories Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 2 4 0 6 1.5
2. Dramatises 3 0 2 5 1.3
3. Agrees 15 12 35 62 15.7
4. Gives suggestion 31 11 27 69 17.4
5. Gives opinion 13 11 39 63 15.9
6. Gives information 38 11 43 92 23.2
7. Asks for information 18 8 7 33 8.3
8. Asks for opinion 11 1 16 28 7.1
9. Asks for suggestion 12 6 7 25 6.3
10. Disagrees 1 2 6 9 2.3
11. Shows tension 2 0 2 4 1.0
12. Seems unfriendly 0 0 0 0 0
Total 146 66 184 396 100
320
Group F
Figure Y6 shows that Group F has a higher number of task-related
communication (74.9%) than team-related communication (25.2%).
20.4
61.1
13.8
4.8
0
10
20
30
40
50
60
70
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y6. IPA domain frequencies for Group F.
The IPA category frequencies for Group F are shown in Table Y6. As can be
seen in this table the categories with the highest total frequency counts are gives
information (32%), gives opinion (18.6%), and agrees (18.6%). The category with the
lowest frequency count, with no behaviours observed or coded, is seems unfriendly.
Gives information was the highest category in session 1, 3, and 5, while gives
opinion was the highest category in session 4. The categories with the highest number
in session 2 includes agrees, give suggestion, and asks for suggestion. An example of
gives information from session 5 was when groups were finishing placing their
ranking system on to the Knowledge Forum ® database:
We don't need the web site (Student 2).
321
The behaviours of seems friendly (0.9%), dramatises (0.9%), and shows
tension (0.6%), were coded in sessions 2 and 3. The category seems friendly was
coded for behaviours or acts that seemed friendly, raised other’s status, gave help or
reward. The category dramatises was coded for behaviours or acts that showed
dramatising, joking, laughing, or showing satisfaction. An example of dramatises
from session 2 was when groups were working on their ranking system for the top
cities in Australia:
This is cool. This is cool (Student 1)
322
Table Y6 IPA Frequency Count for Each Category for Group F
Categories Session
1
Session
2
Session
3
Session
4
Session
5
Total %
of total
1. Seems friendly 1 0 1 0 1 3 0.9
2. Dramatises 0 2 1 0 0 3 0.9
3. Agrees 9 4 18 22 9 62 18.6
4. Gives suggestion 6 4 10 7 8 35 10.5
5. Gives opinion 7 1 10 32 12 62 18.6
6. Gives information 14 3 21 20 49 107 32.0
7. Asks for information 2 0 2 2 23 29 8.7
8. Asks for opinion 0 2 3 1 0 6 1.8
9. Asks for suggestion 0 4 1 3 3 11 3.3
10. Disagrees 1 0 5 6 1 13 3.9
11. Shows tension 0 0 0 2 1 3 0.9
12. Seems unfriendly 0 0 0 0 0 0 0
Total 40 20 72 95 107 334 100
323
Group G
Figure Y7 shows that Group G has a higher number of task-related
communication (79%) than team-related communication (21%).
16.4
50.7
28.3
4.6
0
10
20
30
40
50
60
1. - 3. 4. - 6. 7. - 9. 10. -12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y7. IPA domain frequencies for Group G.
The IPA category frequencies for Group G are shown in Table Y7. As can be
seen in this table the categories with the highest total frequency counts are gives
information (23%) and gives opinion (17.8%). The categories with the lowest
frequency counts, with no behaviours observed or coded, are seems friendly, shows
tension, and seems unfriendly.
Gives information was the highest category in session 2 and 3, while asks for
opinion was the highest category in session 4, followed by gives opinion. The
category asks for opinion is coded for behaviours or acts that ask for opinion,
evaluation, analysis, or an expression of feelings. An example of asks for opinion
from session 4 was when groups were writing in their group diary:
324
You reckon that's neat writing (Student 1)
The behaviour of dramatises (2%) was coded in sessions 2 and 3. An example
of dramatises was when groups were developing their ranking models:
Rock on (Student 1)
Table Y7 IPA Frequency Count for Each Category for Group G
Categories Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 0 0 0 0
2. Dramatises 1 2 0 3 2.0
3. Agrees 11 10 1 22 14.5
4. Gives suggestion 10 3 2 15 9.9
5. Gives opinion 13 8 6 27 17.8
6. Gives information 13 19 3 35 23.0
7. Asks for information 4 8 0 12 7.9
8. Asks for opinion 3 8 7 18 11.8
9. Asks for suggestion 3 8 2 13 8.6
10. Disagrees 0 6 1 7 4.6
11. Shows tension 0 0 0 0 0
12. Seems unfriendly 0 0 0 0 0
Total 58 72 22 152 100
325
Group H
Figure Y8 shows that Group H has a higher number of task-related
communication (76.3%) than team-related communication (23.7%).
23.7
60.2
16.1
00
10
20
30
40
50
60
70
1. - 3. 4. - 6. 7. - 9. 10. - 12
IPA Categories
Fre
qu
ency
(%
)
Figure Y8. IPA domain frequencies for Group H.
The IPA category frequencies for Group H are shown in Table Y8. As can be
seen in this table the categories with the highest total frequency counts are agrees
(23.7%), and gives information (21.5%). The categories with the lowest frequency
counts, with no behaviours observed or coded, are seems friendly, dramatises,
disagrees, shows tension, and seems unfriendly.
Agrees was the highest category in session 4, and was the highest in session 2
along with the categories of gives suggestion and gives information. An example of
agrees from session 3 was when groups were ranking the top cities in Australia:
Student 1: Then we'll do pollution (Student 2) (Gives suggestion)
Student 2: OK (Student 3) (Agrees)
326
The behaviour of asks for suggestion (3.2%) was coded in sessions 3 and 4.
Behaviours in this category include behaviours, or acts, that ask for suggestions,
direction, or possible ways of action. An example of asks for suggestion from session
3 was when groups were developing their ranking models:
Ok, so which city should go first? (Student 2).
Table Y8
IPA Frequency Count for Each Category for Group H
Categories Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 0 0 0 0
2. Dramatises 0 0 0 0 0
3. Agrees 4 8 10 22 23.7
4. Gives suggestion 4 9 5 18 19.4
5. Gives opinion 3 8 7 18 19.4
6. Gives information 4 8 8 20 21.5
7. Asks for information 0 4 2 6 6.5
8. Asks for opinion 0 1 5 6 6.5
9. Asks for suggestion 0 2 1 3 3.2
10. Disagrees 0 0 0 0 0
11. Shows tension 0 0 0 0 0
12. Seems unfriendly 0 0 0 0 0
Total 15 40 38 93 100
327
Group I
Figure Y9 shows that Group I has a higher number of task-related
communication (23.1%) than team-related communication (76.8%).
20.5
60.0
16.8
2.6
0
10
20
30
40
50
60
70
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y9. IPA domain frequencies for Group I.
The IPA category frequencies for Group I are shown in Table Y9. As can be
seen in this table the categories with the highest total frequency counts are gives
information (32.6%), agrees (15.8%), and gives opinion (14.2%). The categories with
the lowest frequency counts, with no behaviours observed or coded are seems
friendly, shows tension, and seems unfriendly.
Gives information was the highest category in session 1, 2, and 4, while gives
opinion was the highest category in session 3. An example of gives information from
session 2 was when groups were allocating group roles to their group members:
I'm going to have to be recorder for first half (Student 2).
328
The behaviour of disagrees (2.6%) was coded in sessions 1, 3, and 4. An
example of disagrees from was when groups were placing their ranking models on to
the Knowledge Forum ® database:
No, you're going to put equals (Student 1)
Table Y9 IPA Frequency Count for Each Category for Group I
Categories Session
1
Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 0 0 0 0 0
2. Dramatises 6 0 2 1 9 4.7
3. Agrees 12 0 17 1 30 15.8
4. Gives suggestion 16 2 5 2 25 13.2
5. Gives opinion 5 0 21 1 27 14.2
6. Gives information 31 2 13 16 62 32.6
7. Asks for information 6 0 3 8 17 8.9
8. Asks for opinion 3 0 1 3 7 3.7
9. Asks for suggestion 3 1 3 1 8 4.2
10. Disagrees 3 0 1 1 5 2.6
11. Shows tension 0 0 0 0 0 0
12. Seems unfriendly 0 0 0 0 0 0
Total 85 5 66 34 190 100
329
Group J Figure Y10 shows that Group J has a higher number of task-related
communication (78.8%) than team-related communication (21.2%).
15.7
66.8
12.05.5
0
10
20
30
40
50
60
70
80
1. - 3. 4. - 6. 7. - 8. 9. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y10. IPA domain frequencies for Group J.
The IPA category frequencies for Group J are shown in Table Y10. As can be
seen in this table the categories with the highest total frequency counts are gives
information (43.3%), gives suggestions (15.7%), and agrees (14.3%). The categories
with the lowest frequency counts, with no behaviours observed or coded, are shows
tension and seems unfriendly.
Gives information was the highest category in all sessions. An example of
gives information from session 3 was when groups were placing their ranking models
on to the Knowledge Forum ® database:
It's double click down there (Student 3).
330
The behaviour of seems friendly (0.5%) was coded in session 3. An example
of seems friendly was when groups were writing their group and task skills in their
group diary:
You got nicer handwriting than me (Student 1)
Table Y10 IPA Frequency Count for Each Category for Group J
Categories Session 2
Session 3
Total % of total
1. Seems friendly 0 1 1 0.5
2. Dramatises 0 2 2 0.9
3. Agrees 0 31 31 14.3
4. Gives suggestion 0 34 34 15.7
5. Gives opinion 2 15 17 7.8
6. Gives information 3 91 94 43.3
7. Asks for information 3 12 15 6.9
8. Asks for opinion 0 5 5 2.3
9. Asks for suggestion 0 6 6 2.8
10. Disagrees 0 12 12 5.5
11. Shows tension 0 0 0 0
12. Seems unfriendly 0 0 0 0
Total 8 209 217 100
331
Group K Figure Y11 shows that Group K has a higher number of task-related
communication (70%) than team-related communication (30%).
20.0
51.1
18.9
10.0
0
10
20
30
40
50
60
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y11. IPA domain frequencies for Group K.
The IPA category frequencies for Group K are shown in Table Y11. As can be
seen in this table the categories with the highest total frequency counts are gives
information (27.9%), and agrees (16.8%). The category with the lowest frequency
count, with no behaviours observed or coded is seems unfriendly.
Gives information was the highest category in session 2, 3, 4, and 5, while
gives suggestion was the highest category in session 1. An example of gives
information from session 4 was when groups were combining their ranking to find the
best city:
Why did we rank Melbourne number one? (Student 1) (Asks for information)
Because that had the most facilities, it had the most stadiums (Student 2)
(Gives information)
332
The behaviours of seems friendly (1.1%) and shows tension (1.1%) were
coded. An example of seems friendly was when groups were working out their group
roles:
Yeah and I'll help too (Student 1)
Table Y11
IPA Frequency Count for Each Category for Group K
Categories Session
1
Session
2
Session
3
Session
4
Session
5
Total % of
total
1. Seems friendly 0 1 0 1 0 2 1.1
2. Dramatises 0 3 0 0 1 4 2.1
3. Agrees 2 6 1 22 1 32 16.8
4. Gives suggestion 3 6 0 14 3 26 13.7
5. Gives opinion 1 3 4 9 1 18 9.5
6. Gives information 2 12 6 30 3 53 27.9
7. Asks for
information
2 9 1 13 1 26 13.7
8. Asks for opinion 0 0 0 5 0 5 2.6
9. Asks for suggestion 1 0 1 3 0 5 2.6
10. Disagrees 1 1 0 15 0 17 8.9
11. Shows tension 2 0 0 0 0 2 1.1
12. Seems unfriendly 0 0 0 0 0 0 0
Total 14 41 13 112 10 190 100
333
Group L
Figure Y12 shows that Group L has a higher number of task-related
communication (82.2%) than team-related communication (17.8%).
13.5
64.8
17.4
4.3
0
10
20
30
40
50
60
70
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y12. IPA domain frequencies for Group L.
The IPA category frequencies for Group L are shown in Table Y12. As can be
seen in this table the categories with the highest total frequency counts are gives
information (41.3%), gives suggestion (14.8%), and asks for information (13%). The
category with the lowest frequency count, with no behaviours observed or coded are
asks for opinion.
Gives information was the highest category in all sessions. An example of
gives information from session 1 was when groups were filling in the monitoring
checklist in their group diary:
Our goal is to rank cities (Student 1)
334
The behaviour of seems friendly (0.9%) was coded in session 1 and 2. An
example of seems friendly was when groups were placing a note on to the Knowledge
Forum ® database:
Yeah, I want to say something like I heard of your school, I heard it's
pretty good (Student 1)
Table Y12 IPA Frequency Count for Each Category for Group L
Categories Session
1
Session
2
Session
3
Total %
of total
1. Seems friendly 1 1 0 2 0.9
2. Dramatises 1 2 2 5 2.2
3. Agrees 2 6 16 24 10.4
4. Gives suggestion 17 11 6 34 14.8
5. Gives opinion 8 3 9 20 8.7
6. Gives information 19 20 56 95 41.3
7. Asks for information 4 6 20 30 13.0
8. Asks for opinion 0 0 0 0 0
9. Asks for suggestion 6 3 1 10 4.3
10. Disagrees 0 3 0 3 1.3
11. Shows tension 0 4 0 4 1.7
12. Seems unfriendly 1 2 0 3 1.3
Total 59 61 110 230 100
335
Group M
Figure Y13 shows that Group M has a higher number of task-related
communication (86%) than team-related communication (14%).
8.6
71.8
14.1
5.5
0
10
20
30
40
50
60
70
80
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y13. IPA domain frequencies for Group M.
The IPA category frequencies for Group M are shown in Table Y13. As can
be seen in this table the categories with the highest total frequency counts are gives
information (40.3%) and gives suggestion (20.1%). The categories with the lowest
frequency counts, with no behaviours observed or coded are seems friendly,
dramatises, and seems unfriendly.
Gives information was the highest category in all sessions. An example of
gives information was when groups were reading the notes that were placed on to the
Knowledge Forum database®:
We got a note, they said great idea (Student 1)
336
The behaviour of shows tension (0.6%) was coded in session 5. An example of
shows tension was when groups were typing a reply into the Knowledge Forum®
database:
I, I know how to spell it (Student 2).
Table Y13 IPA Frequency Count for Each Category for Group M
Categories Session
1
Session
2
Session
3
Session
4
Session
5
Total %
of
total
1. Seems friendly 0 0 0 0 0 0 0
2. Dramatises 0 0 0 0 0 0 0
3. Agrees 3 3 7 1 0 14 8.6
4. Gives suggestion 4 4 20 0 4 32 19.6
5. Gives opinion 8 5 3 0 2 18 11.0
6. Gives information 8 20 24 3 12 67 41.1
7. Asks for
information
1 5 5 0 1 12 7.4
8. Asks for opinion 0 2 2 0 0 4 2.5
9. Asks for suggestion 1 4 2 0 0 7 4.3
10. Disagrees 3 0 0 0 5 8 4.9
11. Shows tension 0 0 0 0 1 1 0.6
12. Seems unfriendly 0 0 0 0 0 0 0
Total 28 43 63 4 25 163 100
337
Group N Figure Y14 shows that Group N has a higher number of task-related
communication (81.6%) than team-related communication (18.4%).
17.0
61.0
20.6
1.40
10
20
30
40
50
60
70
1. - 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y14. IPA domain frequencies for Group N.
The IPA category frequencies for Group N are shown in Table Y14. As can be
seen in this table the categories with the highest total frequency counts are gives
information (30.5%), gives opinion (19.1%), and agrees (16.3%). The categories
with the lowest frequency counts, with no behaviours observed or coded are seems
friendly, shows tension, and seems unfriendly
Gives information was the highest category in all sessions. An example of
gives information from session 3 was when groups were placing their ranking models
on to the Knowledge Forum ® database:
Brisbane's the best cause (sic) it had the most hospitals (Student 2).
338
The behaviour of dramatises (0.7%) was coded in session 2. An example of
dramatises was when groups were developing their ranking models:
Oh cool (Student 1)
Table Y14 IPA Frequency Count for Each Category for Group N
Categories Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 0 0 0 0
2. Dramatises 1 0 0 1 0.7
3. Agrees 8 14 1 23 16.3
4. Gives suggestion 7 5 4 16 11.3
5. Gives opinion 7 17 3 27 19.1
6. Gives information 16 17 10 43 30.5
7. Asks for information 2 3 8 13 9.2
8. Asks for opinion 2 11 1 14 9.9
9. Asks for suggestion 0 1 1 2 1.4
10. Disagrees 0 2 0 2 1.4
11. Shows tension 0 0 0 0 0
12. Seems unfriendly 0 0 0 0 0
Total 43 70 28 141 100
339
Group O
Figure Y15 shows that Group O has a higher number of task-related
communication (78.2%) than team-related communication (21.8%).
16.2
62.0
16.2
5.6
0
10
20
30
40
50
60
70
1. - 3. 4. - 6. 7. - 9. 10. -12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y15. IPA domain frequencies for Group O.
The IPA category frequencies for Group O are shown in Table Y15. As can be
seen in this table the categories with the highest total frequency counts are gives
information (35.9%), agrees (15.5%), and gives opinion (14.8%). The categories with
the lowest frequency counts, with no behaviours observed or coded are seems
friendly, shows tension, and seems unfriendly.
Gives information was the highest category in session 1, 3, and 5, while asks
for suggestion was the highest category in session 2, and asks for opinion was the
highest category in session 4. An example of gives information from session 1 was
when groups were deciding how to rank the capital cities in Australia:
We are ranking cities with sports and environment (Student 1)
340
The behaviour of dramatises (0.7%) was coded in session 1. An example of
dramatises was when groups were writing welcome notes and placing them on the
Knowledge Forum® database:
I don't know [laughs] (Student 2).
Table Y15 IPA Frequency Count for Each Category for Group O
Categories Session 1 Session 2 Session
3
Session
4
Session
5
Total % of
total
1. Seems friendly 0 0 0 0 0 0 0
2. Dramatises 1 0 0 0 0 1 0.7
3. Agrees 9 1 7 2 3 22 15.5
4. Gives suggestion 3 2 5 1 5 16 11.3
5. Gives opinion 6 3 5 2 5 21 14.8
6. Gives
information
29 0 13 0 9 51 35.9
7. Asks for
information
2 0 3 1 1 7 4.9
8. Asks for opinion 2 0 1 3 1 7 4.9
9. Asks for
suggestion
0 4 3 2 0 9 6.3
10. Disagrees 1 0 2 0 5 8 5.6
11. Shows tension 0 0 0 0 0 0 0
12. Seems
unfriendly
0 0 0 0 0 0 0
Total 53 10 9 11 29 142 100
341
Group P Figure Y16 shows that Group P has a higher number of task-related
communication (77%) than team-related communication (23%).
22.3
65.0
12.1
0.50
10
20
30
40
50
60
70
1.- 3. 4. - 6. 7. - 9. 10. - 12.
IPA Categories
Fre
qu
ency
(%
)
Figure Y16. IPA domain frequencies for Group P.
The IPA category frequencies for Group P are shown in Table Y16. As can be
seen in this table the categories with the highest total frequency counts are gives
information (25.7%), gives opinion (25.2%), and agrees (18.9%). The categories with
the lowest frequency counts, with no behaviours observed or coded are seems
friendly, shows tension, and seems unfriendly.
Gives information was the highest category in all sessions. An example of
gives information from session 4 was when groups were working on their ranking
models to find the ‘best’ city in Australia
And the top city is Brisbane again (Student 1)
The behaviour of disagrees (0.5%) was coded in session 3. An example of
disagrees was when the group was discussing a new name for their group:
342
The jungle girls (Student 2) (Gives suggestion)
No (Student 1) (Disagrees)
Table Y16 IPA Frequency Count for Each Category for Group P
Categories Session
2
Session
3
Session
4
Total %
of total
1. Seems friendly 0 0 0 0 0
2. Dramatises 1 2 4 7 3.4
3. Agrees 3 10 26 39 18.9
4. Gives suggestion 7 12 10 29 14.1
5. Gives opinion 8 12 32 52 25.2
6. Gives information 12 13 28 53 25.7
7. Asks for information 4 7 7 18 8.7
8. Asks for opinion 0 1 2 3 1.5
9. Asks for suggestion 0 0 4 4 1.9
10. Disagrees 0 1 0 1 0.5
11. Shows tension 0 0 0 0 0
12. Seems unfriendly 0 0 0 0 0
Total 35 58 113 206 100
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