MAC04222 What Counts as Information Communication Technology Integration…€¦ · · 2013-09-26Teachers and administrators have long desired classroom technology integration

MAC04222

What Counts as Information Communication Technology Integration? Toward a Better Theoretical Framework for Technology Integration

Ron MacDonald, University of South Australia Abstract Successful integration of technology is a key goal of recent large investments in technology infrastructure in Western education systems. Conditions affecting successful integration in the classroom are in need of further elucidation. An extensive study was conceived to investigate modes of professional development, teachersí perceptions of formal and informal leaders, teacher attitudes regarding ICTs and the level of technology integration. A 152-item questionnaire was developed and used to gather data from a School District in Nova Scotia, Canada where 751 out of a potential 996 grade three to twelve teachers and administrators responded. Statistical analysis from this data was then used to guide the researcher to focus upon two Elementary, two Junior and two Senior high schools. At these six schools 71 teachers and administrators were interviewed and/or observed. The top ten technology integrators in the school district also participated in observations and interviews. The data show evidence of complex relationships between the components of professional development, leadership, teacher attitudes and the level of technology integration in the classroom. The data analysis required the development of a new theoretical framework for level of technology integration. This new framework includes components student-control (student-centeredness), curriculum differentiation, teacher organisation and levels of cognitive engagement. Introduction The purpose of the following study was to investigate the ways Leadership, Professional Development and Teacher Attitude relate to ICT Integration. A 152-item questionnaire was developed and employed to gather data from a School District in Nova Scotia, Canada where 751 out of a potential 996 grade three to twelve teachers and administrators responded. Statistical analysis from this data was then used to guide the research by focusing upon two Elementary, two Junior and two Senior high schools. At these six schools 71 teachers and administrators were interviewed and/or observed. The top ten technology integrators in the school district (according to an analysis of the questionnaire data) also participated in observations and interviews. A well-established theory outlining the goals and purposes of Information Communication Technology (ICT) was used as a framework from which questionnaire items were developed (DETYA, 2002). This framework also served as a backdrop to the qualitative data collection. Throughout the data collection and subsequent analysis, it was noted that the theoretical framework required the expansion of, or addition to, existing components. Without these expansions and additions, the way classroom technology integration is framed could fall short of identifying appropriate and effective integration.

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The Questionnaire Past ICT questionnaires concentrated on asking teachers about a list of different types of software applications that they use and about skills they have with respect to these software applications. However to examine the connections between Leadership, Professional Development, Teacher Attitude and ICT Integration a deeper analysis will be needed involving both qualitative and quantitative techniques. To this end the ICTIS (Information Communication Technology Integration Snapshot) has been developed as an instrument that measures teachersí attitudes, ICT integration efforts, perception of professional development experiences and perception of leadership. It is mainly concerned with what teachers and students are doing when using ICTs and what they are thinking while using them. In order to build the questionnaire a set of recurring factors were drawn from the research literature regarding Leadership, Professional Development and Level of Technology Integration (LOTI). From these areas, representational Indicators were developed. These Indicators formed the basis from which the questionnaire items were built. For the factor of Teacher Attitude the Computer Attitude Scale (Gressard & Loyd, 1986) was adapted. The ëIndicatorí approach was not an attempt to gainsay the established literature in these areas but rather to connect current themes and understandings in that literature though to Levels of Technology Integration (LOTI). The LOTI component of the questionnaire employed a second theoretical underpinning. The four types of technology integration goals put forth in the Making Better Connections (DETYA, 2002) were mapped onto the questionnaire items. Both the literature-supported Indicators and the four types of technology integration goals formed the basis for the questionnaire items. Further information regarding the construction and implementation of this questionnaire and subsequent qualitative data will be available in later publications. Four Types of Integration Teachers and administrators have long desired classroom technology integration. In order to address the technology integration within classrooms, a framework for the characteristics of what technology integration looks like and how it functions within the classroom is needed. According to the authors of Making Better Connections (DETYA, 2002) there are four types of ICT integration which may occur at the classroom, school or system level: Type A: ICT as an object of study unto itself. The learning outcome is one of having students become proficient in the use of a particular technology application. Students are to be able to access data from a number of sources and then critically assess its reliability.

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Type B: using ICTs within the existing curriculum to enhance studentís learning experiences. There is the same general teacher-directed, pedagogical approach with new ICT tools. ICTs are used as tools within the teacher directed classroom and used within the existing curriculum to enhance studentís learning experiences. ICTs are used in a way that the pedagogical focus is still on the teacher and the curriculum. However, there may be some classrooms where pedagogy has begun to change more radically. With this type of integration, how curriculum outcomes are reached shift, but the curriculum content does not. Type C: using ICTs in a classroom where both pedagogy and curriculum is significantly changed. For example, the traditional pedagogy, where a teacher introduces an abstract concept first followed by practical examples and finally students practice this application is being transformed. The transformation may start with an authentic (real-world), community-based application and work backwards to have students find the abstract concepts (which may or may not be the intended outcome of the teacher). The later pedagogy is sometimes unpredictable and organizationally messy but essentially authentic. For type C, both curriculum and pedagogy is being reconstructed with the aide of ICTs. Type D: using ICTs as an integral component of school-wide, organizational and structural reform. There is a change in the nature of schooling itself and an integral part of this reform is the use of ICTs to facilitate the change. In the modern era, where many industry sectors have been pervasively impacted by the adoption of ICTs, progression through these types demonstrates profound changes in student learning, teacher practices and education systems. It is tempting to see these types as levels of technology integration where the movement from Type A to B involves progressively profounder and more important integration. However the nature of these types or levels and the conditions underpinning their attainability is problematic. For example if Type D exists, not only should many classrooms demonstrate Type C integration, but also the school structure should have developed in order to support this type of technology integration. Type D maintains Type C. For this fourth type, the total structure of school needs to change. How a given school reaches this profound level is an important issue. Certainly teacher and student roles need to change to reflect shift in focus toward student-centeredness. Critical to the success of type C will be ideational and attitudinal changes about the role of ICTs in education. This may necessitate a change in the building structure itself, the hours of operations, the schedule, what and how teachers teach, how they assess, the relationship teachers and students have together and the teaching profession itself. The notions of ìwho a teacher isî will be challenged in the processes that lead to profound ICTs integration. Schools that achieve the most profound levels show a history of achieving the others Types (Barnes, 2003). However, in a given context the process of reaching the profound levels of integration may be complex and uneven across the school.

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The Types of Technology Integration, as put forth in Making Better Connections, are a very good outline for how ICTs may be integrated within the classroom. However, expansion of and addition to this framework is necessary to more fully describe how technology may be integrated within classrooms. This paper will do this. Toward a Better Theoretical Framework The motivation of this research was to gain a better understanding of what is actually happening in classrooms. From the questionnaire data, interviews and observations, it was noticed that the Types A, B, C and D need more grounding in particular ways. The fairly general four levels from Making Better Connections are not enough to paint a picture of the possibilities and subtleties of ICT integration. Expansions and additions to the four types are necessary for an effective framework. This paper will address the following expansions and additions to Type C:

a) Student Control b) Curriculum Differentiation c) Teacher Organisation d) Higher Order Thinking

a) Student Control Type C states that both the curriculum and pedagogy change. According to the theoretical framework, at Type C, student may gain more control over what happens in the classroom. The implication is the dynamic in the classroom may also change. Instead of having the curriculum and the teacher at the center of the classroom, the student and his/her learning choices become the focus. Learner-centeredness (control) exists here. There may a shift from having the teacher as the person with a great deal of control over what and how learning activities proceed to permitting and encouraging students to take ownership of their education. However, this is only an implication in the existing model and this need for student control should be overtly stated in a new theoretical framework, according to the research gathered from this study. Pupil/learner/student-centeredness is an essential pedagogical approach whereby students are given more control over their own learning (Chandra-Handa, 2001; Haughey, 2002; Pisapia, Coukos, & Knutson, 2000; Smeets & Mooij, 2001). Student control facilitates student-centeredness. According to Smeets and Mooij (2001) particular teacher behaviors within the classroom will allow for student-centeredness. When a teacher in a classroom acts as a coach or facilitator instead of the disseminator of information then students tend to gather and construct their own knowledge. Who controls the curriculum and learning context decisions may be in the realm of the teacher, the student or both. Classrooms where students have been permitted to gain control over curriculum decisions demonstrate student-centeredness. Technology should be employed in ways that pedagogical strategies that are learner-centred develop in classrooms (Haughey, 2002). Teachers are responsible for this development.

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The questionnaire included three self-reported items on the level of technology integration (see below). How do you see your current level of ICT integration? (please circle) No Integration Low Level Medium Level High Level Very High Level How do you see your current level of Software integration? (please circle)

No Integration Low Level Medium Level High Level Very High Level How do you see your current level of Web integration? (please circle) No Integration Low Level Medium Level High Level Very High Level A number of teachers do not use technology either because they do not have access or they do not see the necessity. Those teachers, as well as physical education teachers and computer room teachers, were excluded from this statistical analysis of classroom ICT use. This reduces the value of the correlation coefficient but, importantly, provides a clearer picture of bivariate correlations regarding ICT use among those teachers who use technology. In order to measure the respondentsí level of technology integration, the three self-reported items were combined into a composite index by factor analysis. This composite index is called Level Of Technology Integration (LOTI). The factor analysis procedure will be elucidated in future publications. This LOTI Index was found to correspond with the researcherís field observations. Teachers who demonstrated high levels of Type B and Type C integration also scored themselves at high levels for the LOTI Index. This will be elucidated in further publications. Three questionnaire items represented the construct of student control: My students are given some input into how curriculum outcomes will be

attained. N O M W OD D My students are given some input into when to use ICTs. N O M W OD D My students help us decide which sites we should access. N O M W OD D (Note: N=never O=once a term M=monthly W=weekly OD=every other day D=daily) The three student control questionnaire items were combined into a composite index by factor analysis. This composite index is called Student Control Index. The factor analysis procedure will be elucidated in future publications. The bivariate correlations that follow suggest that when teachers view their integration as high, they also conduct their classrooms with high levels of student control.

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LOTI, Student Control and Student Control Index

Input into How

Outcomes Reached

Input into When to use ICTs

Student Input for

Web Sites

Student Control Index

LOTI Pearson Correlation .332(**) .425(**) .364(**) .472(**) Sig. (2-tailed) .000 .000 .000 .000 N 504 494 476 441

** Correlation is significant at the 0.01 level (2-tailed). The data implies a shift in control within the classroom. Students, who have input into how outcomes are to be reached, input into when to use ICTs and who have input into which web sites to use are also permitted control over their own learning. When they are permitted this control teachers are also integrating at higher levels. Students gain a sense of ownership over their curriculum; they gain knowledge construction control. This knowledge construction control, the ability for students to gain control over their learning, is a necessary shift in the classroom surrounding effective ICT integration (Chandra-Handa, 2001). This empirical finding of a relationship between integration and student control is supported by direct observations of teachers and students who negotiated topics for projects. A continuum of student control can be discerned from these observations. An example of this continuum follows:

i) Students are given a list of topics to choose from. ii) Students are given a list of topics to choose from but then can add to the

list with teacher approval. iii) Students come up with their own topic and go to the teacher if they canít

develop their own iv) Students must come up with their own topic. The most student control (and student-centeredness) exists in the fourth situation. When students are granted a great deal of control over the project topic, they may gain a sense of ownership over their work. In order for students to gain this much control, the teacher must trust the studentsí choices. This is not to suggest that whatever the student says goes. But, to a large extent the students may be permitted to make real choices and then be able to defend them. The foregoing suggests that in a framework that describes the goals of technology integration in classrooms, the shift of control to the student is an essential component. Without this shift represented, varying presentation methods (as controlled by the teacher) will result in an enhanced Type B situation. The difference between Type B and C lies in the level of control granted to students. Therefore, Type C integration should contain elements of student control.

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b) Curriculum Differentiation Type C integration, as stated above, exists when both pedagogy and curriculum is changed. Learner-centeredness is an essential element in discussing Type C integration. A shift from having the teacher as the person with a great deal of control over what and how learning activities proceed to permitting and encouraging students to take ownership of their education occur when teachers integrate at high levels. A number of teaching/learning situations may lead to a classroom to student-centeredness. Curriculum differentiation is essential in developing student-centeredness (HRDC, 1999; Smeets & Mooij, 2001). All learners have their own particular curricular needs and intelligences (Gardner, 1993). One method of addressing these varying needs is to differentiate the curriculum. Learning contexts, which are facilitated to address studentsí learning styles result in having students reach outcomes more effectively. Most classrooms have a number of ability levels and ability types represented by students. Differentiating the curriculum allows for these various ability levels to be addressed (Smeets & Mooij, 2001). The following questionnaire items represent curriculum differentiation: I implement learning experiences that use ICTs to meet the needs of: students in general N O M W OD D N/A students with special needs N O M W OD D N/A gifted students N O M W OD D N/A students with learning disabilities N O M W OD D N/A (Note: N=never O=once a term M=monthly W=weekly OD=every other day D=daily) When curriculum differentiation occurs in the classroom, student-control also exists. The four curriculum differentiation questionnaire items were combined into a composite index by factor analysis. This composite index is called Curriculum Differentiation Index. The factor analysis procedure will elucidated in future publications.

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Curriculum Differentiation and Student Control

** Correlation is significant at the 0.01 level (2-tailed).

All of the items above show strong correlations between teacher-facilitated, curriculum differentiation and student-control. It is interesting to note that with curriculum differentiation, there is a higher correlation with teachers allowing students to control ëWhen to use ICTsí. When employing the Student Control Index and the Curriculum Differentiation Index, the correlations are as follows:

Curriculum Differentiation Index and Student Control Index

Student Control

Index Curriculum Differentiation Index

Pearson Correlation .620(**) Sig. (2-tailed) .000 N 311


When the representations of curriculum differentiation occur, teachers also report ICT integration at high levels:

Input into How

Outcomes Reached


Student Input for

Web Sites

Regular Student ICT use

Pearson Correlation .393(**) .479(**) .335(**) Sig. (2-tailed) .000 .000 .000 N 469 459 440 Special Needs ICT use

Pearson Correlation .332(**) .479(**) .351(**) Sig. (2-tailed) .000 .000 .000 N 412 401 385 Gifted Students ICT use

Pearson Correlation .370(**) .431(**) .316(**) Sig. (2-tailed) .000 .000 .000 N 381 375 361 Learning Disabilities ICT use

Pearson Correlation .353(**) .485(**) .360(**) Sig. (2-tailed) .000 .000 .000 N 414 404 391

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Curriculum Differentiation and LOTI

LOTI Regular Student ICT use

Pearson Correlation .420(**) Sig. (2-tailed) .000 N 486 Special Needs ICT use Pearson Correlation .357(**) Sig. (2-tailed) .000 N 425 Gifted Students ICT use Pearson Correlation .301(**) Sig. (2-tailed) .000 N 393 Learning Disabilities ICT use



All of the above show strong correlations between teachers using technology at high levels and differentiating their curriculum. The consolidated indices for Curriculum Differentiation and LOTI result in these correlations:

Curriculum Differentiation and LOTI

LOTI Curriculum Differentiation Index


** Correlation is significant at the 0.01 level (2-tailed). Curriculum differentiation is strongly correlated with student control. Student control is strongly correlated with high levels of ICT integration (as stated in Section a). Therefore, curriculum differentiation is important for high levels of ICT integration and should therefore be included in a framework for thinking about the ICT integration purposes. Curriculum differentiation comes with student options (sometimes ICT options) that are tuned to the particular student. A teacher directing particular differentiations may not lead to increased student-control (student-centeredness). For students to take ownership over their own learning, curriculum differentiation should be directed by students. Therefore, the notion of student controlled, curriculum differentiation should be stressed in a framework for Type C.

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c) Teacher Organisation If a teacher allows a shift toward more student control, which may lead to curriculum differentiation then a classroom may become student-centred. However, if this student-centeredness does not allow for a certain level of teacher-directed organisational requirements then chaos may ensue (Smeets & Mooij, 2001). Students let loose, without an understanding of expectations, may result in disorganization. A classroom that has clearly outlined student outcomes, clearly outlined methods of demonstrating these outcomes have been reached and clearly outlined time-lines will be effective in creating student-centeredness (OTA, 1995; Pisapia et al., 2000). Teachers not only need to be able to manage a classroom when ICTs are being used but they also need to guide students to manage their own curriculum (Pisapia et al., 2000). The questionnaire items that represented teacher-directed organization were: As I plan for the subject matter to be presented in a lesson, I also plan how ICTs can be embedded to help students reach curriculum outcomes. N O M W OD D I use criteria (rubrics) for evaluation of technology-based student projects and the processes used to create those projects. N O M W OD D When teachers set up classrooms where student-control exists, they also organize their curriculum:

Teacher Organization and Student Control ** Correlation is significant at the 0.01 level (2-tailed). The Teacher Organization questionnaire items were combined into a composite index by factor analysis. This composite index is called Teacher Organization Index. The factor analysis procedure will be elucidated in future publications. Using the Teacher Organization Index and the Student Control Index, the correlations are as follows:

Input into How

Outcomes Reached


Student Input for

Web Sites ICT Lesson Planning Pearson Correlation .371(**) .512(**) .337(**) Sig. (2-tailed) .000 .000 .000 N 499 488 469 ICT Rubrics Pearson Correlation .355(**) .265(**) .249(**) Sig. (2-tailed) .000 .000 .000 N 491 480 460

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Teacher Organization Index and Student Control Index

Student Control

Index Teacher Organization Index


** Correlation is significant at the 0.01 level (2-tailed). When teachers are organized, they also demonstrate curriculum differentiation, as represented below:

Teacher Organization and Curriculum Differentiation


Special Needs

ICT use

Gifted Students ICT use

Learning Disabilities

ICT use ICT Lesson Planning Pearson Correlation .708(**) .558(**) .544(**) .545(**) Sig. (2-tailed) .000 .000 .000 .000 N 483 422 390 424 ICT Rubrics Pearson Correlation .409(**) .337(**) .313(**) .331(**) Sig. (2-tailed) .000 .000 .000 .000 N 474 417 387 418

** Correlation is significant at the 0.01 level (2-tailed). Using the Teacher Organization Index and the Curriculum Differentiation Index, the correlations are as follows:

Teacher Organization Index and Curriculum Differentiation Index

Curriculum Differentiation

Index Teacher Organization Index


** Correlation is significant at the 0.01 level (2-tailed). When teachers are organised, they also report high levels of technology integration. The table below demonstrates this (note: Teacher Organization Index is also included):

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LOTI and Teacher Organization (including Index)

** Correlation is significant at the 0.01 level (2-tailed). There may be a fuzzy line between teacher direction and organised teacher facilitation. The difference, essentially, exists when there is a teacher-organised high level of student control, which allows for curriculum differentiation and thus student-centeredness. When the teacher only directs the curriculum differentiation or when there is a lack of student choices over curriculum then Type B results. This is not to say that there is a distinct division between Type B and C. Rather, there exists a range of types across classrooms, schools and school systems (DEST, 2003). Not only is there variability across classrooms, schools and school systems, but there may also be a range of Types between students in the same classroom. Studentsí actual experience of ICT integration may vary. This will be investigated in future publications. Teacher-directed classroom organization is strongly correlated with student-control. Student-control is strongly correlated with high levels of ICT integration (as stated in Section a). Therefore, teacher-directed, classroom organization is important for high levels of ICT integration and should be included in Type C of the framework for thinking about ICT integration. d) Cognitive Engagement Higher order thinking that involves problem solving, creativity and critical thinking have long been desired as student outcomes. Type C integration goals may lead to higher levels of student cognition. There is an untested association between cognitive learning outcomes and classroom ICT use (DEST, 2003). If a strong association between Type C integration and higher levels of student cognitive engagement could be demonstrated then the importance of Type C integration would be elevated. According to the questionnaire data, this may be true. Three questionnaire items represent Higher Order Thinking: ICTs are used in my classroom to have students engage in higher order thinking like problem solving, critical thinking or creativity. N O M W OD D I am able to have my students engage in higher order thinking when using this software (creativity, problem solving or critical thinking). N O M W OD D I am able to have my students engage in higher order thinking when using the Web (creativity, problem solving or critical thinking). N O M W OD D

ICT Lesson

Planning ICT Rubrics

Teacher Organization

Index LOTI Pearson Correlation .473(**) .352(**) .480(**) Sig. (2-tailed) .000 .000 .000 N 520 509 505

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There is a strong correlation between high levels of ICT integration and higher order thinking. When teachers integrate technology at high levels they also say that higher order thinking occurs:

LOTI and Higher Order Thinking

** Correlation is significant at the 0.01 level (2-tailed). The questionnaire items representing higher order thinking were also consolidating using factor analysis. The composite index is called Higher Order Index. The correlations between the Higher Order Index and LOTI are:

Higher Order Thinking Index and LOTI

LOTI Higher Order Thinking Index

Pearson Correlation .514(**)

Sig. (2-tailed) .000 N 322


Five other pieces of evidence may also reveal that students engaging in higher levels of integration (Type C) reach higher levels of cognition. The five areas that may point to higher levels of cognition are i) student collaboration, ii) project/problem-based activities, iii) student control, iv) curriculum differentiation and v) teacher-directed organization. i) Student Collaboration Collaboration is the highest level of meaningful interaction: ëit implies working together, yet challenging each other through continual interaction to create meaning, explore topics, construct shared understanding and knowledge, accept group accountability and through a combination of efforts achieve the group goalí (Geer & Barnes, 2001). Cooperative learning environments where students learn in an interdependent context enhances studentsí problem solving skills (Johnson & Johnson, 1996). Higher knowledge and skill levels are demonstrated when students work collaboratively (Means et al., 1997). This assertion, that student collaboration and higher order thinking correlate, has been confirmed by this studyís data. One questionnaire items asks if professional development has helped the teacher create a classroom where student collaboration has increased: Over the past two years, professional development involving ICTs has helped me create a classroom where student collaboration has increased. Yes No

Higher Order Thinking with

ICTs


Software


Web LOTI Pearson Correlation .496(**) .304(**) .455(**) Sig. (2-tailed) .000 .000 .000 N 497 358 498

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The correlations (including the Higher Order Thinking Index) are as follows:

Student Collaboration and Higher Order Thinking (including Index)

Higher Order

Thinking with ICTs

Higher Order

Thinking with

Software

Higher Order

Thinking with Web

Higher Order

Thinking Index

Student Collaboration Pearson Correlation .260(**) .343(**) .351(**) .417(**) Sig. (2-tailed) .000 .000 .000 .000 N 423 324 427 289

** Correlation is significant at the 0.01 level (2-tailed). Student collaboration, as demonstrated above, occurs at the same time teachers believe their students are attaining higher order thinking. ii) Problem/Project Based Activities When students engage in activities where the curriculum has been problematized or project-based, typically a Type C activity (DETYA, 2002), then higher order cognition may result. The questionnaire contained the following question as a representation of project/problem based activities: My students do project/problem-based learning using ICTs. N O M W OD D According to the data gathered in this study, there are strong correlations between higher order thinking and project/problem based activities.

Project/Problem Based with ICTs and Higher Order Thinking (including Index)

Higher Order

Thinking with ICTs

Higher Order

Thinking with

Software

Higher Order

Thinking with Web

Higher Order

Thinking Index

Project/Problem Based with ICTs

Pearson Correlation .558(**) .297(**) .323(**) .512(**) Sig. (2-tailed) .000 .000 .000 .000 N 487 350 484 319 ** Correlation is significant at the 0.01 level (2-tailed). Higher order thinking is evident in Type C integration.

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iii) Student Control If one was to agree that student control was also important (as suggested above) for Type C integration, then student control should correlate with high levels of cognitive involvement:

Higher Order Thinking and Student Control

Input into How

Outcomes Reached

Input into

When to use ICTs

Student Input for

Web Sites

Higher Order Thinking with ICTs

Pearson Correlation .426(**) .606(**) .311(**) Sig. (2-tailed) .000 .000 .000 N 482 473 452 Higher Order Thinking with Software

Pearson Correlation .284(**) .304(**) .205(**) Sig. (2-tailed) .000 .000 .000 N 343 336 324 Higher Order Thinking with Web

Pearson Correlation .244(**) .294(**) .368(**) Sig. (2-tailed) .000 .000 .000 N 477 467 452

** Correlation is significant at the 0.01 level (2-tailed). The Indices for Higher Order Thinking and Student Control show the following correlations:

Higher Order Thinking Index and Student Control Index

Student Control

Index Higher Order Thinking Index


** Correlation is significant at the 0.01 level (2-tailed). The above tables demonstrate strong correlations between higher order thinking and student control. An element of Student Control an as inclusion in Type C of the framework will reflect the possibility of students reaching higher cognitive levels. iv) Curriculum Differentiation If one was to agree that curriculum differentiation was also important (as suggested above) for Type C integration, then curriculum differentiation should correlate with high levels of cognitive involvement:

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Curriculum Differentiation and Higher Order Thinking with ICTs

Higher Order

Thinking with ICTs


Pearson Correlation .560(**) Sig. (2-tailed) .000 N 463 Special Needs ICT use Pearson Correlation .514(**) Sig. (2-tailed) .000 N 410 Gifted Students ICT use Pearson Correlation .470(**) Sig. (2-tailed) .000 N 379 Learning Disabilities ICT use


** Correlation is significant at the 0.01 level (2-tailed). The Indices for Curriculum Differentiation and Higher Order Thinking yield the following:

Higher Order Thinking Index and Curriculum Differentiation Index

Curriculum Differentiation

Index Higher Order Thinking Index


** Correlation is significant at the 0.01 level (2-tailed). iv) Teacher-Directed Organization If one was to agree that Teacher-Directed Organization was also important (as suggested above) for Type C integration, then Teacher-Directed Organization may correlate with high levels of cognitive involvement. This is demonstrated below:

Teacher Organization and Higher Order Thinking


ICTs ICT Lesson Planning Pearson Correlation .621(**) Sig. (2-tailed) .000 N 492 ICT Rubrics Pearson Correlation .333(**) Sig. (2-tailed) .000 N 483

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The Teacher Organization and Higher Order Thinking Indices result in the following correlations:

Teacher Organization Index and Higher Order Thinking Index

Higher Order

Thinking Index Teacher Organization Index


** Correlation is significant at the 0.01 level (2-tailed). Summary of Correlations As stated above, factor analysis resulted in the creation of a number of relevant Indices:

• Level of Technology Integration Index (LOTI) • Curriculum Differentiation Index • Student Control Index • Teacher Organization Index • Higher Order Thinking Index

The following is a summary of the Indicesí correlations:

Index Correlations

Teacher Organ. Index

Student Control Index

Curr. Diff. Index

Higher Order

Thinking Index

LOTI Pearson Correlation .480(**) .472(**) .408(**) .514(**) Sig. (2-tailed) .000 .000 .000 .000 N 505 441 357 322 Teacher Organization Index

Pearson Correlation 1 .537(**) .616(**) .513(**) Sig. (2-tailed) . .000 .000 .000 N 505 426 349 311 Student Control Index Pearson Correlation .537(**) 1 .620(**) .577(**) Sig. (2-tailed) .000 . .000 .000 N 426 441 311 273 Curriculum Differentiation Index

Pearson Correlation .616(**) .620(**) 1 .465(**) Sig. (2-tailed) .000 .000 . .000 N 349 311 357 228


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Using the Index correlation values, the following preliminary diagram was produced:

(Please note: the dashed arrows represent correlations between Higher Order Thinking Index and Student Control Index (vertically) and Teacher Organization Index and Curriculum Differentiation Index (horizontally).)

Future Analyses Multivariate and path analyses will be carried out to determine the possible causal relationships among the Indices. The results of this analyses will be revealed in upcoming publications. Conclusion In Making Better Connections (2001), the crux of the difference between Type B and Type C lies in the curriculum (the what) and the pedagogy (the how). In Type B the pedagogy changes in the methods student use in order to address particular curriculum outcomes. Information, communication technologies are employed in the classroom to help students reach these outcomes in ways that were not available without them. How curriculum outcomes are reached change with this type of integration. However, the curriculum (the What) in this Type B remains unchanged.

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Type C integration not only uses technology to address how curriculum outcomes are reached, but the curriculum content itself changes. A teacher using technology within Type C allows authentically driven (student-driven) activities to augment and enhance the curriculum. A certain level of student control molds the curriculum. Both how curriculum outcomes and what curriculum outcomes (with respect to content especially) are changed. The four Types of ICT goals from Making Better Connections (DETYA, 2002) may readily demonstrate immediately visible, outward representations of the How and the What regarding pedagogy and curriculum. However, the data from this study reveals other less apparent, underlying features that could be included in the framework. Throughout this study, student-control (student-centeredness), curriculum differentiation and teacher-directed classroom organization all strongly correlate with high levels of technology integration (LOTI). All of these factors could be included in Type C integration. From this study, data reveals that high levels of cognitive engagement (as represented by creativity, problem-solving and critical thinking) are strongly correlated with high levels of technology integration. Therefore, Type C integration could also include reference to cognitive engagement. The four Types from Making Better Connections (DETYA, 2002) outline an important perspective for practicing teachers. However, the more subtle factors of curriculum differentiation, student control, teacher organization and higher order thinking may reveal a Type C integration in a more pragmatic and substantial manner. These factors could be included in the continued development toward a better framework for technology integration in the classroom. Without the inclusion of these factors, valuable and important issues may be left undiscovered.

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References Barnes, A. (2003). Voyage of Discovery: Teaching and Learning, Whole School Change

and ICTS at Le Fevre High School 1998-2002. South Australia: Department of Education and Children's Services.

Chandra-Handa, M. (2001). Leading academic change - through connective leadership and learning. Paper presented at the Society for Information Technology and Teacher Education (SITE, 2001), Orlando, Florida.

DEST. (2003). Effective Use of Information and Communication Technology (ICT) to Enhance Learning for Disadvantaged School Students. Commonwealth Department of Education, Science and Training. Retrieved, 2004, from the World Wide Web: http://www.detya.gov.au/schools/publications/2003/ICT/ICTreport.pdf

DETYA. (2002). Making Better Connections: The Models of Teacher Professional Development for the Integration of ICT into Classroom Practice. Commonwealth

Department of Education Science and Training. Retrieved November, 2002, from the World Wide Web: http://www.detya.gov.au/schools/publications/2002/professional.htm

Gardner, H. (1993). The Unschooled Mind: How Children Think and How Schools Should Teach. New York: Perseus Books, L.L.C.

Geer, R., & Barnes, A. (2001). Towards a Framework of Teaching and Learning through Technology-Mediated Interaction. Paper presented at the Seventh IFIP World Conference on Computers in Education.

Gressard, C. P., & Loyd, B. H. (1986). Validations studies of a new computer attitude scale. Association for Educational Data Systems Journal, 18(4), 295-310.

Haughey, M. (2002). Canadian Research on Information and Communications Technologies: A State of the Field. Canadian Educational Statistics Council and PCERA (Pan-Canadian Educational Research Agenda). Retrieved November 15, 2002, from the World Wide Web: http://www.cesc.ca/pceradocs/2002/papers/MHaughey_OEN.pdf

HRDC. (1999). Professional Development and Learning Technologies: Needs, Issues, Trends and Activities (ED431900). Hull, Quebec: Human Resources Development Canada.

Johnson, D. W., & Johnson, R. T. (1996). Cooperation and the use of technology, Handbook of Research for Educational Communication and Technology (pp. pp.1017-1044). New York: Macmillan Library Reference.

Means, B., Coleman, E., Klewis, A., Quellamlz, E., Marder, C., & Valdes, K. (1997). GLOBE Year 2 Evaluation. Menlo Park, CA: SRI International. Retrieved, 2004, from the World Wide Web: http://www.sri.com/policy/ctl/assets/images/y2_full.pdf.

OTA. (1995). Teachers and technology: making the conection. Washington, D.C.: Office of Technology Assessment, Congress of the United States Government Printing Office.

Pisapia, J. R., Coukos, E. D., & Knutson, K. (2000). The impact of computers on teacher capacity, attitudes and behaviors in elementary schools. Paper presented at the American Educational Research Association, New Orleans, L.A.

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Smeets, E., & Mooij, T. (2001). Pupil-centred learning, ICT, and teacher behaviour: observations in educational practice. British Journal of Educational Technology, 32(4), 403-417.

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MAC04222 What Counts as Information Communication Technology Integration…€¦ · · 2013-09-26Teachers and administrators have long desired classroom technology integration