Is this the Answer?

1

Physics Department

Is this the Answer?

2011

This report was supported by the Department of Physics. A graduate student was employed as an

observer in the Physics 160FC lectures in 2011 Semester 1. Funding was supplied to provide

professional development to the laboratory tutors for the Team-Based Learning and the Help-

Room tutors for student guidance during problem solving.

Thanks to Pearson Education for the opportunity to trial Mastering Physics, the on-line assessment

system that provided effective feedback to lecturers about questions students found difficult and

support to students through the problem solving structures.

Graham Foster

Physics Education Research

Room 303 .612 Physics Dept

g.foster@auckland.ac.nz

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Abstract

The 2009 report by Graham Foster and Brett A Armstrong identified barriers to learning in

Physics at Stage 1 and suggested strategies that might improve students‟ view of, and confidence

about, studying Physics at Stage 1.

During 2010 several strategies were added to the mix in both Physics 120 „Physics of Energy‟ and

Physics 160 „Physics for the Biological Sciences‟. The use of clickers, together with in-lecture

problem solving, weekly bulletins, and Team Based Learning were some of the strategies

implemented.

In Semester1, 2011, these strategies were refined and applied. Additionally the opportunity was

provided by Pearson Education to trial Mastering Physics, an on-line assignment strategy that

had several advantages over the OASIS on-line system commonly used in Stage 1 Physics courses.

These strategies facilitated the transfer from „content-focused‟ teaching to the „student-focused‟

teaching based on socio-cultural theory and the work being promoted in the Carl Wieman Science

Education Initiative at the University of British Columbia, Canada.

This paper places the strategies used in the appropriate theoretical context and reports the

summative effect of implementing these strategies in the Physics 120 course. The student outcomes

in both on-course assessments and examinations is analysed to determine the relative effectiveness

of each strategy and the apparent gains that each strategy contributed to student performance.

Conclusions and recommendations are provided.

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Preliminary Contexts of this Report

The MoRST Report “Staying in Science 2” (2006) shows that Physics was the most disliked

subject of all the Sciences. While 52% studied Physics in Year 13, 40% of the sample expressed

dislike for Physics. Only 30% of students in the sample expressed a dislike for Chemistry and

19% expressed their dislike for Biology. The report showed that clear gender preferences in

science disciplines. Females were more likely to choose Biology, while males chose Physics.

The 2009 report to the Science Faculty and Physics Department:

How do we keep them? Identifying and dismantling barriers to participation, performance and

progression in Stage I Physics courses.

by Graham Foster, Physics Department, Faculty of Science, the University of Auckland and

Brett A Armstrong, Research Assistant, Sociology Dept, University of Auckland

identified barriers to learning in Physics at Stage 1 and suggested strategies that might improve students‟

view of and confidence about studying Physics at Stage 1.

In a the 2010 report to the Science Faculty and Physics Department

Student Perceptions of Studying Physics at the University of Auckland

Graham Foster (Senior Tutor), Yvette Wharton (SIT), Simon Kjellberg (PhD student)

reported on the steady decline of NCEA Level 3 entries in the Auckland Region, from 8215 in

2006 to 7527 in 2009. This report also provided information about the changes to the NCEA

awards in Level 2 and 3 through “endorsement‟ and possible effects of students coming to the

University of Auckland with a lower level of Physics appreciation since they may have attempted

fewer Achievement Standards. It detailed the hesitancy that students perceive about Physics and

the influences that caused students to study Physics at the University of Auckland.

Base Data of Enrolments 2007 to 2011

Table 1 provides data of student enrolments in Physics Stage 1 and 2 courses at the University of

Auckland Physics Department. There seems to be an increase in numbers in Stage 2 in 2010 and

2011. Some Stage 1 courses seem to be holding or slightly increasing their enrolment numbers,

other courses, such as Physics 102, seem to be showing significant, sharply reduced enrolments.

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Strategies and Objective for 2011

Since the end of 2009 the endeavour has been to change the teaching and learning processes in

Physics 120FC by implementing several strategies to encourage students to know that their

personal learning needs are being met more effectively through the strategies being used in

Physics. The strategies were intended to provide a greater sense of „belonging‟ and recognition,

while reducing cognitive load and student stress and increasing student confidence about their

ability to learn and achieve in Physics.

During 2010 several strategies were added to the mix in both Physics 120 „Physics of Energy‟ and

Physics 160 „Physics for the Biological Sciences‟. In Semester 1 2011 these strategies were

refined and implemented.

This paper reports on the strategies used to improve the students‟ view of Physics in the course

Physics 120. The outcomes from the previous research and reports, together with on-going

research readings, gave reasonably good definition to some of the strategies that should be used in

Physics 120 for 2011.

The objectives were:

1) To continue developing stronger relationships between students and the Physics Department

so that the Physics 120 FC course changes from „content-focused‟ to „student-focused‟.

2) To find ways to reduce the effects of any subject dislikes and lack of student confidence in

order to encourage students entering Physics 120FC to perform effectively, gain success

and to continue to Stage 2 Physics courses.

3) To determine if we have developed strategies to keep them!

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Physics Courses and Enrolments Course 2007 2007 2007 2008 2008 2008 2009 2009 2009 2010 2010 2010 2011

Local Int'l Total Local Int'l Total Local Int'l Total Local Int'l Total Total

102 323 42 365 278 42 320 272 35 307 240 21 261 300

107 136 22 158 126 8 134 182 20 202 164 17 181 344

107G 92 11 103 134 15 149 135 9 144 147 23 170

108

38 8 46 50 8 58 62 4 66 108

108G

24 7 31 27 6 33 28 6 34

111 21 1 22 27 1 28 30 3 33

120 296 35 331 280 35 315 293 23 316 279 28 307 308

130 57 16 73 46 10 56 120 5 125 63 5 68 109

140

88 9 97 107 12 119 77 14 91 135

150 189 26 215 169 23 192 192 23 215 201 27 228 227

160 623 65 688 654 49 703 652 58 710 689 53 742 730

210 18 1 19 16

16

211 18 2 20 27 1 28 14 1 15 33 3 36 39

213 25 6 31 21 7 28 22 11 33 22 4 26 37

220 44 1 45 35 10 45 42 4 46 69 15 84

230 35 4 39 35 13 48 41 6 47 58 6 64

231

76

240 48 4 52 47 9 56 34 7 41 48 9 57 61

243 17 1 18

250 44 3 47 43 8 51 33 1 34 50 2 52

251

69

260 29 3 32 24 4 28 15

15 36 6 42

261

68

270 20 3 23 29 3 32 16 1 17 23 4 27

280 17 2 19 11

11 12 1 13 9 1 10 16

Total Stage 1 1955

2071

2262

2148 2261

Total Stage 2 345

343

261

398 366

Table 1: Base Data from Faculty of Science providing detail of Stage 1 and Stage 2 enrolments 2007-11

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Introduction and Theory

Part 1: Retaining Information

Three separate surveys by Redish, Hrepic and Perkins have shown that students retain very little from a

lecture even if it only occurred 30 minutes previously. Students‟ short-term working memory is very

limited in its both its capacity and retention. Studies such as those using the Force Concepts Inventory

by Richard Hake showed that “in the traditional lecture course students master no more than 30 per cent

of the key concepts that they didn‟t already know at the start of the course.

Carl Weiman explains that research has several things to say about pedagogical strategies related to

learning. Retention of information, understanding of basic concepts, and beliefs about science and

scientific problem solving are included.

Weiman concludes that, since people learn by creating their own understanding, with assistance from

teachers, then effective teaching facilitates that creation by getting students „engaged‟ in thinking deeply

about the subject at an appropriate level and then monitoring that thinking and guiding it to be more

expert-like. These strategies include reducing cognitive load to reduce the load on the short-term

memory by slowing down, using clear explanations and connections between ideas, and using pictorial

representations as well as verbal and mathematical representations. Teachers must know where their

students are starting from in their thinking, so they can build on that foundation; they must “engage”

students and guide their thinking using technologies, and to use Novack et al‟s „just-in-time-thinking‟

through questions to be covered before class.

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Part 2: Active Involvement versus Engagement

It should be noted that the word „engaged‟ must be used with caution and there is a developing

background of theory that distinguishes „active learning‟ from „engagement‟ which has specific

implications. The Derek Bok Centre for Teaching and Learning (Harvard University) indicates that

• active learning includes in-classroom methods that involve students in the learning process requiring

meaningful learning activities that cause them to think about what they are doing.

• collaborative learning is any instructional method in which students work together in small groups

toward a common goal.

• cooperative learning is a structured form of group work when students pursue common goals whie

being assessed individually.

• problem-based learning uses relevant problems introduced at the beginning of an instructional cycle

and used to provide context and motivation for learning that follows

The definition of engagement is much more debated and is developing more specific definition with

time. Russell, Ainley and Frydenberg, 2005, (P1) define engagement as “energy in action, the

connection between person and activity”. Ball and Perry (2010) define engagement as “students‟

involvement with activities and conditions likely to generate high quality learning”

While engagement was viewed as reflecting a person‟s active involvement in a task or activity (Reeve,

Jang, Carrel, Jeon & Barch, 2004) it has now developed to include specific sub-divisions of cognitive

engagement, emotional engagement, and psychological engagement. In Finn‟s (1989) model,

engagement is comprised of behavioural (participation in class and school) and affective components

(identification, belonging, valuing learning). Similar definitions have been offered by Newmann,

Wehlage, and Lamborn (1992) and Marks (2000). More recently, engagement has been defined as

having three subtypes: behavioural (positive conduct, effort, participation), cognitive (e.g. self-

regulation, learning goals, investment in learning) and emotional or affective (e.g. interest, belonging,

and positive attitude about learning (Fredericks et al, 2004; Jimerson, Campos, & Greif, 2003).

Measuring student engagement

Kuh (2001) reports that student engagement represents the amount of time and effort that students put

into their study and learning. Pintrich and De Groot (1990) indicate that the extent to which students are

involved in active learning is thought to be facilitated by experiences that involve constructing new

knowledge and understanding. A series of five benchmarks have been established for student

engagement. These are: active and collaborative learning, academic challenge, student interactions with

faculty, enriching educational experiences, and supportive campus environment.

Bell and Perry (2010) identify the Cognitive Processes and attempt to Explain the Dominant Cognitive

Processes. They use Felder and Brent‟s argument that “students have different levels of motivation,

different attitudes about teaching and learning, and different responses to specific classroom

environments and instructional practices. The more thoroughly instructors understand the differences,

the better the chance they have of meeting the diverse learning needs of all their students.”

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Bell and Perry indicate that each cognitive type has a distinctive pattern of processes:

• for what energizes:

- Interaction with others – Extraversion

- More solitary activities – Introversion

• for what is accessed in information gathering

- Tangible, experiential awareness - Sensing

- Conceptual, symbolic awareness – Intuiting

• the process of organizing, evaluating and deciding on information

- Based on criteria or principles – Thinking

- Based on appropriateness of worth – Feeling

They indicate that each of the possible combinations of these dichotomies leads to differences in

cognitive processes.

Sharan and Goek Chin Tan describe cognitive engagement as “understanding engagement through active

or self-regulated involvement in learning”. Since this requires an understanding of the cognitive

processes involved in active learning it is important at this stage to describe Jung‟s Eight-Functions

Model.

Jung first defines the Perception Processes, recognizing the four types of perceived data (the way things

are, the way they used to be, the way they could be now, and the way they will ultimately be).

Then he defines the ways we organize experiences and make decision about the data as the Judgment

Functions

The Four Perception Processes

we use these to focus attention and gather

information

The Four Judgment Processes

We use these to organize experiences and make

decisions

Extraverted Sensing (Se) Extraverted Thinking (Te)

Introverted Sensing (Si) Introverted Thinking (Ti)

Extraverted Intuiting (Ne) Extraverted Feeling (Fe)

Introverted Intuiting (Ni) Introverted Feeling (Fi)

While all eight of these processes are available, we develop some more than others. Jung‟s theory

indicates that the dominant process is the one we most commonly use and trust. In Jung‟s theory, the

relationship between the dominant and auxiliary is the combination of how we prefer to take in

information and our preferred processing and decision making. Ball and Perry detail the Dominant and

Perception Processes and outline the possible linkages between the Eight Cognitive Processes and

Measures of Active Learning. To do this they first established if the eight cognitive processes could be

linked to the seven areas of active learning investigated by the Australian Survey of Student Engagement

(AUSSE) instrument. They needed to determine if some processes were more aligned to engagement

than others.

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Ball and Perry used a panel of three educators to determine what linkages exist between Jung‟s

Eight Functions Model and the AUSSE instrument. They determined that:

• The Introverted Intuiting (Ni) process is only highly cognitively engaged if there is the opportunity

to ask questions in-class or on-line. They have medium cognitive engagement if they are involved

in discussions and community-based projects.

• The Extroverted Intuiting (Ne) is highly cognitively engaged in many more types of activities including

working with other students both inside and outside class, making presentations, and in in-class

discussions.

Hence Ball and Perry conclude that students with a preference for a cognitive process that is Ni would

have some difficulty in achieving well in most of the active learning occasions.

Similarly, Ball and Perry determined that those students whose cognitive processes indicate a preference

for Extraverted Feeling (Fe) would be more actively involved than students with a preference for the

Introverted Feeling (Fi) processes. They tentatively concluded that it seems likely that students

preferring different dominant cognitive processes will differ in their approach to a number of the active

learning activities.

While Ball and Perry were trying to determine if students in different disciplines displayed differences in

their use of dominant cognitive processes and hence differ in their levels of engagement, in this study for

Physics 120FC at the University of Auckland, the focus will be to what extent is the choice of dominant

processes common to all students? These ideas will be developed later in the report

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Part 3 : Socio-cultural Approach and Team Based Learning

One of the major studies discussed in the 2009 report by Foster and Armstrong was the Teaching and

Learning Research Initiative (TLRI) through the New Zealand Council for Educational Research

(NZCER) :

„Understanding and Enhancing learning communities in tertiary education in science and

engineering‟

Chris Eames and Mike Forret (CSTER, University of Waikato)

The theoretical perspective was that of using a socio-cultural approach to examine a number of factors

that may impact on the tertiary science and engineering learning community. Dawes (2004),

Aufschnaiter (2003) and Welzel et al. (1999) have all discussed the nature and role of teacher-student

and student-student relationships in tertiary learning situations. They reported that students were often

influenced by only one or two significant teachers; and that teachers were conscious of te language they

used in shaping interactions. Dalgety (2002) showed that social relationships were important in tertiary

environments, with positive relationships between students influencing the choice to continue taking

science subjects. Aldridge, Fraser and Murray et al (2002) found that tertiary students‟ perceptions of

their lessons are linked to their perceptions of teaching staff.

Forret, Eames and Coll (2007) report that:

“One of the strongest themes to emerge from the case studies was the centrally important role played by relationships

in shaping the quality of teaching and learning experiences. Students and teachers in all institutions commented that

developing positive working relationships within the tertiary science and engineering community was important.

This applied to both teacher–student and student–student relationships. ...... Students and teachers saw value in students

developing relationships with each other. These relationships were seen to provide both moral and academic support in

areas such as sharing ideas and concerns about their learning, sharing notes, and collaborating in studying. Where

students were not able to develop these relationships early on in their course, they were seen to be at a disadvantage

and, therefore, both teachers and students felt it was important for opportunities to be provided for these relationships

to be developed early” (pages 17-18).

The development of positive working relationships within tertiary science was shown to be important

and applied to both teacher-student and student-student relationships. Students at all institutions

acknowledged the fundamental role that their working relationship with their teacher played in shaping

their learning experiences. Approachability of the teacher so that students can seek help; the opportunity

to form student-student learning relationships as they shared ideas, shared notes and collaborated in

study to provide both moral and academic support; making classes more enjoyable and motivating

students to learn are all important factors. While practical classes were highly valued by students, they

found it helpful to have a combination of theoretical and practical teaching sessions, particularly when

they are integrated and related in a timely way.

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The unpublished paper “ How do we keep them? …………..” (2009)

by Foster and Armstrong reports that students expressed the value of working together and the desire to

have tutorials that were recognised by more than an attendance mark. As a response to this in 2010 and

in 2011, the Physics 120 laboratory tutorials were structured to include Team Based Learning.

Team Based Learning, TBL

The TBL strategy was developed by Michaelson, Fink and Knight at the University of Oklahoma. TBL

offers a strategy that engages students in the learning process, activates them to be more responsible for

their own learning (at least partially removing the expectation of „spoon-feeding), encourages them to

attend lectures, and provides relevant, supported challenges and greater opportunity of success through

formation and development of cohesive learning teams.

The TBL Objectives:

∙ To shift the primary learning objectives of the course from simply familiarizing students

with key concepts to ensuring students learn how to use the key concepts;

∙ To change the role and function of the teachers and tutors. They will need to move from

simply delivering information, to managers of the learning and instructional processes.

∙ To change the role and function of students in the course. Instead of being recipients of

information and content, students will become responsible for initial acquisition of content

and for working collaboratively with other students.

Team Based Learning is based on four principles:

Principle 1: Groups must be properly formed and managed to minimize barriers to group

cohesiveness and to share the abilities by equitable distribution of members (avoiding previously

established relationships, or avoiding group formation based on background factors such as nationality,

culture or native language). The group members need to have a range of ability levels, physics

experience, and language fluency abilities. Learning teams should be fairly large and diverse to

maximize their intellectual diversity, yet not so large as to prevent full participation by all team

members. Optimal size is 5 to 7 students per group. Groups should be permanent so they can evolve into

effectively functioning teams.

Principle 2: Students must be made accountable:

The development of groups into cohesive learning teams requires assessing and rewarding for a number

of different kinds of behaviour. Students must:

• be accountable for preparing the work - the Readiness Assurance Process that occurs at the

beginning of each session requires students to answer 8 - 10 multiple choice questions based on pre-

assigned readings. Then after the individuals complete their answers, the group re-takes the same test.

This promotes accountability to the tutor and their team members.

• give in-class time to completing group assignments. Students have accountability for coming to

tutorial and for being ready to contribute to the achievement of the team.

• interact with each other in productive ways that leads to high quality team performance. Each team

develops a group dynamic that is more than the sum of the individual contributions each student makes.

The group dynamic for each group can be compared across teams by considering each group‟s ability to

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express their expertise about the solutions to each problem. The grading system applied in the last TBL

session includes ratings for the students‟ preparation, their contribution to the work and the quality of the

group work.

Principle 3: Team assignments must address a key learning objective of the course and promote

both learning and team developments.

It is most important that effective team assignments require full-group interaction. Assignments that

require groups to make decisions and enable them to report their decisions in a simple form will usually

encourage group interaction. Assignments must avoid the ability of groups to sub-divide the work and

limit interactions.

Principle 4: Students must receive frequent and immediate feedback.

This happens in two ways:

• Timely feed-back from Readiness Assurance Tests (RAT). Each stage of the RAT is assessed

immediately while the next stage is being implemented. The tutor has time to assess the individual multi-

choice questions while the group multi-choice test is in progress. Similarly they assess the group multi-

choice tests while the team problem solving test is in progress. The individual student and group are

supported to determine how effective their current learning procedures are by receiving this immediate

notification of their previous efforts. High scores mean they are doing what they need to be doing to

learn, and vice versa for low scores.

• Timely feedback on application focused team assignments. Students receive quick feed-back on

application-based assignments and this encourages both learning and team development.

The Way Forward

This report will now develop each of these theoretical perspectives and provide evidence of outcomes

related to each. Then it will focus back on the question

“How can we keep them?”

and attempt to respond to the challenge “Have we found the answer?”

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Part 1: Influence of Student Requests, Lecture Representative Feed-back and

Assessment Schedule Changes

In the 2009 Report “How do we keep them? Identifying and dismantling barriers to participation,

performance and progression in Stage I Physics courses‟ students requested more recognition for

tutorial involvement and achievements. Additionally, new strategies such as Team Based Learning and

pre-lecture focus-questions have been introduced and student efforts given to test revision showed the

need to discriminate the assessment rewards between assignments and tests. The perspective of Team

Based Learning shall be discussed later in this report.

Over the past five years 2006 to 2010 the Physics Department has used the on-line learning and

assessment tool known as OASIS. This is an on-line program that is used to expand student

understanding of ideas presented in lectures through active learning. It was introduced and used for

assessment purposes to prevent time being used for marking. This generates lecturer time to give student

tutorial help and to provide time to write more OASIS questions. Students are given a schedule of dates

for each of four assignments; they are given one week to practice five or six questions and one hour to

complete the assessment.

As part of the 2009 report, Foster and Armstrong asked students to comment on OASIS. There was an

even split both for and against (53% for-47% against), but students reported they simply need more time

to practice the Physics problem solving. One week practice and one hour for assessment were too

compressed in their busy schedule of learning and assessment. Students reported requiring between five

and nine hours practice on OASIS problems. Some simply found algorithms to get the correct value

rather than understanding the physics.

Therefore, as the opportunity was presented by Pearson Education, it was decided to use Mastering

Physics. While this is similar in some aspects to OASIS, the separation between skill/practice time and

assessment time was not required. Students logged-in to Mastering Physics, worked through a set of

lecturer-selected problems (both qualitative and quantitative) and entered their answers to the problems.

Their score reflected the number of times they attempted each part of each question. Part of the

assessment mark was subtracted for incorrect entry values. In addition the stress was mostly removed by

extending the time the assignment was available. Students were given twelve days to complete the

problem solving in each assignment. This allowed better planning and time-management by students.

During 2009 and 2010 the lecture representatives have provided feedback on progress and difficulties

experienced by students during the semester. Two of the most familiar complaints have been that the

pace of lectures has been too quick for many students and that there is insufficient time given to students

to become involved in the problem solving process during lectures. In an attempt to overcome the

former (pace too quick), each of the thermal lectures was given a preliminary reading and set of

questions that set the context of the lecture. These questions were followed up during lecture.

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The skill of problem solving was supported during thermal and mechanics lectures through provision of

problem-solving guidelines, student involvement in problem-solving during lectures, the use of clickers

during lectures, Mastering Physics in assignments and Team Based Learning in laboratory tutorials.

Therefore there was a coordinated, coherent emphasis on problem solving

Therefore, over the past two years, adjustments have been made to the assessment schedule. This was

needed to ensure that students would give energy and commitment to the strategy, and that the strategy

would be recognized as being valuable to the whole assessment schedule.

2009 2010 2011

Assignments 4 @ 2.5% = 10% 4 @ 2.5% = 10% 4 @ 2.5% = 10%

Tests 2 @ 5% = 10% 2 @ 5% = 10% 2 @ 6% = 12%

Team Based Learning Tutorials 7% 8%

Laboratories 15% 15% 15%

Examinations 65% 58% 55%

Total 100% 100% 100%

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Part 2: What Colour Is Student Involvement in Lectures?

The strategy for measuring „student active involvement‟ in lectures followed that by Carl Wieman

Science Education Initiative at the University of British Columbia, Vancouver, Canada. An observer

was placed in lectures at least twice per week over the final ten weeks of semester 1, 2011. They

recorded the number of students in lecture and randomly chose two groups of ten people in the lecture

theatre for each lecture. The active involvement (engagement /dis-engagement) was measured by

recording the number of people in each group who were „on-task‟ at each of the times selected. These

times were at regular ten-minute intervals.

The average attendance at lectures was 74.2% of the 308 enrolled students.

This strategy provided data from twenty lectures, giving numbers of students in each lecture,

„involvement/ dis-involvement, and recorded the strategy being used at each of the recording times.

The data and graphs are attached as Appendix 1

The sum of the number of students from both groups involved in lecture and on-task was then recorded

as the „involvement index‟ and the strategy being used at that time was recorded with the involvement

index.

There was a judgment made about each strategy. This judgment matched the extent of student

involvement to a colour, using red as student independent work (e.g. students solve problems on their

own or with partners), pink as students involved in answering clicker questions, yellow as a strategy

involving class input but led by lecturer, green as lecturer developing explanations of ideas with some

class input (structured questions), blue as explaining ideas from slides, and purple as pure content

transfer teaching.

The strategies were listed beside each „involvement index‟ and the occurrence frequency within each

„involvement index‟ recorded. The graph of „frequency versus involvement index‟ shows the relative

use of each type of strategy, and the graph of frequency trend for each „involvement index‟ value shows

the trend in use of the activity as the activity index decreases.

It would seem that while student on-task attention is relatively high, with most involvement index scores

above 12/20, most of our lecturing strategies are still „content-focused‟ strategies that provide little

opportunity for direct student involvement.

It is perhaps not surprising that when there was higher use of content-focused strategies, the involvement

index decreased significantly as shown between involvement indices 18 to 16. However these also

corresponded to use of some class-input strategies during problem solving.

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Use of Clickers and other Strategies to Promote Student Involvement

During the semester two lecturers used the Qwizdom Clickers to enhance student learning and

involvement in lectures. Students responded to the PowerPoint questions,

Data from at least seven lectures was gathered and the responses analyzed. Where fewer than 80% of

students provided the correct response this was colour coded so that the data with darkest shading

showed the most need for review.

For example

Lecture 5 Qn A/True/Yes B/False/No C D E F # %

Involved Answer %

Correct

1 8 / 6% 9 / 7% 102 / 77%

0 / 0% 0 / 0% 0 / 0% 119 38.6 C 77 %

2 20 / 15% 83 / 62% 19 / 14%

0 / 0% 0 / 0% 0 / 0% 121 39.3 B 62 %

3 29 / 22% 54 / 41% 24 / 18%

7 / 5% 0 / 0% 0 / 0% 114 37.0 B 41 %

4 11 / 8% 6 / 5% 92 / 69%

5 / 4% 0 / 0% 0 / 0% 114 37.0 C 69 %

5 92 / 69% 3 / 2% 1 / 1% 11 / 8%

0 / 0% 0 / 0% 107 34.7 A 69 %

From these a document „Comments from Clicker Questions‟ was placed on CECIL. This gave feedback

about the questions that showed the lowest correct response rate.

In a typical lecture only 30 to 40% of students in the lecture were using Clickers.

End of Course Survey

The end-of-course survey provided students with questions related to the use of clickers,

problem-solving and Power-Point in lectures. Students used a Likert scale with 1 (strongly disagree) and

10 (strongly agree). The questions asked to what extent the strategy supported their learning.

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In the „End of Course Survey‟ the following questions and responses were given:

Question:

Lecturers‟ use of Clickers in lectures and the

correct explanations as part of that significantly

helped me to improve my understanding.

Data:

Mean = 4.91

Standard Deviation-A (σn-1) = 2.75

While there was a large group that did not respond

well to the use of clickers, there was a reasonably

even spread of student responses, with over 54%

(137) of students expressing support for their use.

It would seem that there is greater potential for use

of clickers in lectures by requiring use of clickers

as part of the assessment system, even if the

percentage recognition is low. This would at least

give lecturers a better view of student learning and

increase active involvement of students.

Question

Lecturers‟ use of problem solving in lectures

significantly helped me to improve my

understanding.

Data:

Mean = 6.61

Standard Deviation-A (σn-1) = 2.35

There was overwhelming support by students for

use of problem solving in lectures so that students

could have time to think about strategies to solve

the question. Over 80 % of students showed a

positive response to this strategy.

Question

Lecturers‟ use of Power-Point explanations in

lectures significantly helped me to improve my

understanding.

Data:

Mean = 6.22

Standard Deviation-A (σn-1) = 2.26

Over 78% of students supported the use of

PowerPoint presentations to significantly help them

improve their understanding.

It is suggested that this needs to be communicated

to lecturers who still do not use this strategy; there

may be a need for some professional development.

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Lecturers' use of PowerPoint

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Question:

Lecturers‟ use of write-on-board explanations in

lectures significantly helped me to improve my

understanding.

Data:

Mean = 6.40

Standard Deviation-A (σn-1) = 2.43

Not surprisingly, over 80% of students supported

the use of write-on-board explanations. However,

other lectures use equally effective strategies such

as fill-in notes and these give students greater

opportunity for involvement.

The purposeful use of problem solving, clicker strategies, involvement of students in opportunities of

perception checks and development of explanations using think-pair-share strategy, does provide

reasonable incentive for students to appreciate the use of these strategies and to stay on-task. This is

supported by the attendance-at-lectures data shown in Appendix 2 as percentage attendance.

It seems that continued development of in-lecture strategies to involve students more directly is required

if students are to understand and remember ideas more effectively and if they are not to experience

cognitive overload. During this semester at least one lecturer encouraged students to use pre-lecture

questions and reading of the text and Power Point slides to support effective in-lecture learning. If

lectures can be developed as „lect-orials‟ then student learning may be enhanced and achievement

improved.

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Lecturers' use of write-on-board explanations

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Part 3: Involvement and Cognitive Engagement

Students were asked to respond to several questions that were intended to help lecturers determine if the

balance of support strategies and activities helped students to achieve better learning and assessment

scores. It was the same survey used in 2010 with approval from the University of Auckland Human

Participants Ethics Committee Ref 2010/228.

Students scored their responses on a Likert scale with 1 being low and 10 being high. Some questions

were deliberately given as the negative sense. There were 308 students enrolled and 252 responses were

received from students. This gave a Confidence Level of 99% with a confidence interval of 2.03.

While the survey covered a wider range of aspects only aspects of engagement will be reported here.

The questions, survey data and comments are provided sequentially below:

Question:

I felt quite isolated as a student with little support

available as I studied Physics 120

Data:

Mean = 3.31

Standard Deviation-A (σn-1) = 1.90

More than 68 % of students (± 1 σ) indicated they

were not isolated, rather they felt supported in the

study of Physics 120FC.

Question:

I worked most often on my own and not with other

Physics 120 students except when I needed to in

Laboratory Tutorials

Data:

Mean = 5.25

Standard Deviation-A ((σn-1) = 2.61

That this average score is not higher is good. It

indicates that students are working reasonably

cooperatively even in aspects of the course excluding

laboratory tutorials where cooperation was essential.

At the start of the semester students were encouraged

to form work groups and share their learning. This

occurred since research of strategies such as Team

Based Learning has shown the very positive effects

on achievement that occur when cooperative learning

occurs. This response seems to indicate that students

are benefiting from this encouragement.

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70

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1. Isolated or not?

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I worked on my own unless required to work in a group

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The next several questions sought to distinguish between „active involvement‟ and „engagement‟ by

asking questions that relate the person to activity, as indicated by Russell, Ainley and Frydenberg, 2005,

(P1). These questions may not provide the ability to discern if the named activity type provided “ the

conditions to generate high quality learning” as in the definition by Ball and Perry (2010). However in

this report the intended focus is on cognitive engagement.

The questions were developed to utilize Jung‟s Eight-Functions Model in which he defines the

Perception Processes and the Judgment Functions and then indicates that the dominant process is the

one we most commonly use and trust. In Jung‟s theory, the relationship between the dominant and

auxiliary is the combination of how we prefer to take in information and our preferred processing and

decision making.

The Four Perception Processes

we use these to focus attention and gather

information

The Four Judgment Processes

We use these to organize experiences and make

decisions

Extraverted Sensing (Se) Extraverted Thinking (Te)

Introverted Sensing (Si) Introverted Thinking (Ti)

Extraverted Intuiting (Ne) Extraverted Feeling (Fe)

Introverted Intuiting (Ni) Introverted Feeling (Fi)

Question:

I preferred learning activities that provided hand-on

experiences (interactive & experiments) and did not

prefer the conceptual & symbolic (book-type)

learning.

Data:

Mean = 5.96

Standard Deviation-A (σn-1) = 2.49

The data seems to indicate we have a balance of

students that have a slight bias toward extraverted

intuiting (Ne). When Ball and Perry‟s theory is

applied to the Physics 120 cohort it is possible to

identify that the students in Physics 120 do have a

bias towards being highly cognitively and being able

to be engaged in many more types of activities

including working with other students both inside

and outside class, making presentations, and in in-

class discussions.

It seems we should be reasonably confident that we

can increase the range of activities including class

discussions and other interactions and know that

most students will be capable of good cognitive

engagement in these.

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I preferred hands-on experiences

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Question:

I preferred learning activities in Physics 120 that

provided learning about ideas in Physics that had

applications and worth and did not prefer learning

through thinking and deciding type activities.

Data:

Mean = 6.19

Standard Deviation-A (σn-1) = 2.18

The student cohort is strongly Extroverted Feeling

(Fe) in Jung‟s Judgment Processes. This indicates

that over 68% (± 0.5 Standard Deviation-A) do

prefer to learn ideas that have application and worth.

It signals to lecturers that leaning may occur best if

contextual learning is used, giving actual

applications.

Question:

Physics 120 has provided experiences that have

required me to respond by using most of my senses

including touch, sight, hearing etc.

Data:

Mean = 4.93

Standard Deviation-A (σn-1) = 2.26

This question tested the extent to which students

used the Perception process of extroverted sensing.

There is a reasonable balance showing that only

about half of the students in the cohort utilized their

senses. It signals that we might need to use a greater

variety of strategies to encourage students to

perceive ideas fully

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Preferred learning activities that showed applications

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I have needed to respond by using most of my senses

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Question:

Physics 120 has required me to gather and organize a

large amount of information and I have been able to

compare ideas to earlier learning about Physics. This

has allowed me to develop a more accurate

understanding about Physics.

Data:

Mean = 6.35

Standard Deviation-A (σn-1) = 2.07

This question was intended to determine the degree

of introverted sensing used by students. There is a

strong bias of students with over 70% expressing that

they were able to gather and organize, compare

earlier learning and to gain a more accurate idea

about Physics through the teaching and learning

strategies used.

Question

Physics 120 has enabled me to see some new and

different possibilities in Physics ideas and to better

understand relationships between ideas and

applications.

Data:

Mean = 6.56

Standard Deviation-A (σn-1) = 2.11

This question was intended to determine the relative

bias on the Extroverted Intuiting (Ne) Perception

Process. Ball and Perry indicate that the Extroverted

Intuiting (Ne) student is highly cognitively engaged

in many more types of activities including working

with other students both inside and outside class,

and in in-class discussions.

It would seem that, since over 78% of Physics 120

students indicated a score greater than 5.40, the

cohort of students is highly engaged in cognitive

activities.

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I have needed to gather, organise and compare earlier learning

Series1

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Physics 120 has allowed new ideas and understand relationships better

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Question

Physics 120 has allowed me to see ideas from

several perspectives and allowed me to better

understand ideas by correcting ideas I did not

understand correctly. It has required different ways

of thinking about ideas.

Data:

Mean = 6.37

Standard Deviation-A (σn-1) = 1.95

This question was intended to determine the relative

bias on the Introverted Intuiting Perception Process.

Again the data shows that over 70% of students are

also strongly able to personally consider and

perceive ideas from several perspectives and have

shown divergent thinking processes, enabling them

to correct misconceptions.

By applying Jung‟s „Eight-Functions Model‟ it has been possible to show that, in terms of Cognitive

Engagement, the 2011 cohort of Physics 120 FC students are strong in all of the Perception Processes,

though there is a need for more strategies that will support the use of more student senses to develop

their extroverted sensing Perception Processes. This identifies a potential area for teaching strategy

development.

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Physics 120 has shown different perspectives and understand ideas better

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Part 4: Applying socio-cultural theory using modified Team Based Learning

Significant changes were made to the Team Based Learning (TBL) strategy. In 2010 an Ethics

Committee approved survey was used to make the division of students into their random groups. The

criteria used enabled equivalent groupings using criteria of Physics experience, attitude to Physics and

Mathematics and gender/ethnic mixture. When TBL was introduced it was necessary for students to

adapt to both the strategy and the people in their group. So that this could occur with the additional stress

of assessment, the first session was not assessed and only the last three sessions were assessed.

In 2011 the four TBL tutorials took place after all five experiments were completed and the TBL groups

were identical to the groupings for their experimental sessions. This meant that students were already

familiar with their peers and were able to quickly adapt to the new TBL strategy without having to adapt

to new people in their group. All four TBL sessions were assessed.

The responses to the intervention of using Team-Based Learning were measured by looking at both

individual and team scores as the team strategy proceeded. and through the student survey that sought a

Likert scale response to questions. The first question was categorised as „student responses to the TBL

strategy‟, while the other two questions gave a measure of „immersion-into-Physics responses resulting

from the inclusion of more engagement strategies in physics 120‟. The former provides evidence of

differences in achievement made by using Team based Learning as an intervention strategy to improve

learning, while the latter provides evidence of the students‟ perceptions about their engagement in and

commitment to the course.

Question:

The Team Based Learning strategy in lab tutorial

time was effective in developing group work and

shared learning techniques.

Data:

Mean = 6.80

Standard Deviation-A (σn-1) = 2.43

Students expressed very strong support for TBL.

Informal feedback after TBL sessions provided

expressions of enjoyment and genuine involvement

of teams. Over 77% expressed support for this

strategy. The graph of response distribution shows

the high support by the majority of students through

its heavy bias at scores ≥ 5.

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The Team Based Learning effectively helped develop group work and shared

learning

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Question:

The Team Based Learning strategy did help me

improve my learning about the main Physics ideas.

Data:

Mean = 6.45

Standard Deviation-A (σn-1) = 2.37

Students expressed strongly that Team Based

Learning did help them improve their learning.

Again over 77% expressed support through

scores ≥ 5.

Question:

The Team Based Learning strategy did help me to

improve my score in assessment more than I could

have done through personal effort.

Data:

Mean = 5.93

Standard Deviation-A (σn-1) = 2.45

Over 73 % of students recorded scores ≥ 5 showing

very strong support for TBL as a strategy that helps

improve their assessment scores.

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Team Based Learning did help me improve my learning about the main Physics ideas

Series1

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Team Based Learning did help me to improve my assessment scores

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To test the effectiveness of Team Based Learning the individual scores of all students in the multiple

choice were averaged and compared to the average scores of the teams‟ multiple choice. The average

scores for the team-based problem solving are also provided.

Average

score for

individuals‟

multiple

choice /15

Standard

deviation-A

(σn-1)

Average

score for

team-based

multiple

choice /15

Standard

deviation-A

(σn-1)

Average

score for

team-based

problem

solving /15

Standard

deviation-A

(σn-1)

2010 7.24 3.63 10.41 4.43 9.88 4.62

2011 7.10 1.85 8.55 5.10 9.47 5.54

The average scores for the team-based multiple choice are nearly one standard deviation above the

average scores for the individual multiple choice, and the average scores for the team-based problem

solving are approximately 0.5 standard deviation-A above the individual multiple choice. This shows a

significant improvement in learning over individual effort.

After the Team-Based Learning sessions each group member was provided with a feed-back sheet.

Some of the comments were:

“ Good input from each member. Idea well explained so each person understood”

“My group members worked well by sharing their ideas and knowledge on questions.”

“E,A and E contributed a lot towards problem solving. E and A pointed out a lot of important points and

formulas regarding the problems. Overall I think we were an effective team.”

“Team-based learning is kind of fun. Being able to work in a group and all.”

It seems that team-based learning was well received and contributed effectively to improving student

learning and understanding.

Is this the Answer?

27

Part 5: First-half semester survey 2011

A survey at the end of the first half of the semester was used to determine student responses to strategies

being used at that time. After providing a whole class survey, 150 of their surveys were randomly

selected and analyzed. The students rated the answer using a 1 to 5 Likert Scale. After calculations of

averages and Standard-Deviation was completed the data was considered

Average + StDevA < 2.50 approx. was ranked 4

Average + StDevA < 3.0 approx. was ranked 3

Average + StDevA < 3.2 approx. was ranked 2

Average + StDevA < 3.4 was ranked 1

Thermal and Thermodynamics Average StDevA Rank

I really enjoyed the interactive teaching techniques during Thermal

lectures 2.56 0.86 1

I really enjoyed the clicker questions 2.11 0.90 3

I found the explanations given to clicker Qs to be helpful to my learning 2.29 0.85 2

I really enjoyed then discussion and perception check opportunities 2.60 0.84 1

I enjoyed seeing the demonstrations and practicals in lectures 1.83 0.89 3

I found the pre-quiz questions to be very helpful to my learning 2.52 0.86 1

I found then pre-reading to be helpful to my learning 2.26 0.87 2

What two things contributed most to my learning during thermal

lectures? #

Pre -reading 44

Pre-lecture quiz questions 9

Lecture objectives 16

Clicker questions 34

In Class problem solving and discussions 79

Explanations of ideas 75

Mechanics Average StDevA Rank

I really enjoyed the interactive teaching techniques during mechanics

lectures 1.40 0.59 4

I really enjoyed the clicker questions 2.20 0.90 2.5

I found the explanations given to clicker Qs to be helpful to my learning 2.11 0.83 3

I really enjoyed then discussion and perception check opportunities 1.79 0.73 4

I enjoyed seeing the demonstrations and practicals in lectures 1.23 0.47 4

What two things contributed most to my learning during mechanics

lectures #

Pre-reading 22

Clicker questions 17

In-class problem solving 96

Explanations of ideas 96

This survey has a 95% confidence level and

a confidence interval of 5.67.

N (c) = 300 and n (s) = 150

Is this the Answer?

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If only Rank 3 & 4 statements are considered:

> Students enjoyed the interactive teaching techniques in Mechanics.

> Students really enjoyed then discussion and perception check opportunities in Mechanics

> students greatly enjoyed seeing demonstrations and practicals in both Mechanics and Thermal

> Students enjoyed using the Clicker questions in both Mechanics and Thermal & the explanations to

Clicker Qs in mechanics.

Rank 2 statements showed explanations to clicker Qs were enjoyed in thermal

Is this the Answer?

29

Summative Effectiveness of the Strategies – Internal Assessments and Examination

To determine the effectiveness of the introduced and modified strategies in 2011 it is necessary to

consider the components of the internal assessments

2009 Exam Lab Assign T1 T2

n 299 316 306 306 291

Average 50.43 12.04 6.79 2.68 2.51

St Dev A 20.58 2.19 2.63 0.90 0.82

Total value 100.00 15.00 10.00 5.00 5.00

2010 Exam Lab Assign T1 T2 Lab Tut Total

n 277 299

294 289 274 288

Average 43.47 10.85 5.39 2.25 2.40 4.14

St Dev A 20.37 2.47 2.86 1.01 0.89 1.36

Total Value 100.00 15.00 10.00 5.00 5.00 7.00 100.0

2011 Exam Lab Assign T1 T2 Lab Tut Lab Tut Total

n 277 307 292 295 278 303 303

Average 27.96 11.51 7.72 2.40 2.82 4.44 5.14

St Dev A 11.97 2.35 2.43 0.97 1.02 1.62 1.77

Total Value 55.00 15.00 10.00 *5.00 *5.00 7.00 8.00 100.0

* These assessed values were scaled from total / 6 to total /5

Is this the Answer?

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Data Analysis: T Tests

This is used to assess whether the averages of two groups are statistically different from each other. It is

particularly appropriate as the analysis for the post-test-only two-group randomized experimental design.

The following data compares 2011 achievements with each of 2009 and 2010.

Test 1 and Test 2 Test 1 Test 2

2011 2010 2009 2011 2010 2009

Total score 5.0 5.0 5.0 5.0 5.0 5.0

n 295 289 306 278 274 291

average 2.40 2.25 2.68 2.82 2.40 2.51

Std-devA 0.97 1.01 0.90 1.02 0.89 0.82

Variance 0.941 1.02 0.81 1.04 0.79 0.67

variance / n 3.189E-3 3.529E-3 2.647E-3 3.742E-3 2.883E-3 2.302E-3

Test 1

T–test (2011-2009) -3.66 Degrees freedom 599 Probability -1.96

T-test (2011 – 2010) +1.83 582 1.96

Risk Level , α = 0.05 (95% confidence)

Since the T-value for 2011-2009 is larger than the probability values, the Test 1 achievement of the 2009

cohort was higher than that of the 2011 cohort.

The T-value for 2011-2010 Test 1 is not larger than the probability so there is no significant difference

between these two tests.

Test 2

T–test (2011-2009) +3.98 567 +1.65

T-test (2011 – 2010) + 5.16 550 +1.65

Risk Level , α = 0.05 (95% confidence)

Since the T-values for both the 2011-2009 and the 2011-2010 cohorts are higher than the probability

values, the Test 2 achievement of the 2011 cohort was higher than either the 2010 or 2009 cohorts.

While there was no significant statistical difference show by Test 1, there were significant differences

between the 2009-2011 Test 2 and 2010-2011 Test 2 scores. This may be the result of the accumulative

effort being made throughout the semester, or from a difference in test standard.

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Assignments

Assignments Total

2011 2010 2009

Total score 10.0 10.0 10.0

n 292 294 306

average 7.72 5.39 6.79

Std-devA 2.43 2.86 2.63

Variance 5.905 8.180 6.917

variance / n 0.0202 0.0278 0.0226

Assignments

T–test (2011-2009) 4.49 Degrees freedom 596 Probability 1.96

T-test (2011 – 2010) 10.63 584 1.96

Risk Level , α = 0.05 (95% confidence)

Since the T-values for both the 2011-2009 and the 2011-2010 cohorts are higher than the probability

values, the total assignment achievement of the 2011 cohort was higher than either the 2010 or 2009

cohorts. It seems that some combination of the strategies implemented is contributing to increase total

test scores.

Laboratory Tutorials

Assignments Total

2011 2010

Total score 7.0* 7.0

n 303 288

average 4.44 4.14

Std-devA 1.62 1.36

Variance 2.624 1.850

variance / n 0.00866 0.006423

Lab Tutorials

T–test (2011-2010) 2.44 Degrees freedom 589 Probability 1.96

Risk Level , α = 0.05 (95% confidence)

Since the T-value for 2011-2010 is larger than the probability, the achievement of the 2011 cohort was

significantly higher than that of the 2010 cohort. The students combined efforts in laboratory tutorials is

increasing their scores significantly. The removal of the peer assessment was likely to be a significant

factor contributing to this increase in the laboratory tutorial scores.

Is this the Answer?

32

Total Internal and External Achievements Comparison

To determine if total internal assessments contributed to the improved achievement, or if the exam was the major

source of improvement, the internal assessments were compared , then the raw exam assessments compard using

the T-test.

Internal Assessments

Total Internal

2011 2010 2009

Total score 100* 100* 100*

n 303 306 316

average 66.15 57.06 67.24

Std-devA 17.35 18.92 16.17

Variance 301.0 357.9 261.5

variance / n 0.9934 1.1696 0.8275

Total Internals

T–test (2011-2010) 6.18 Degrees freedom 607 Probability 1.96

T-test (2011-2009) -0.807 617 1.96

Risk Level , α = 0.05 (95% confidence)

Since the T-value for 2011-2010 is larger than the probability, the internal assessment achievement of

the 2011 cohort was significantly higher than that of the 2010 cohort.

Since the T-value for 2011-2009 is slightly smaller than the probability but less than the probability

value, the internal assessments achievement of the 2011 cohort was not significantly different than that

of the 2010 cohort. There was a significant increase in the internal achievement scores between 2010 and

2011.

Is this the Answer?

33

Examination Assessment

Examination

2011 2010 2009

Total score 100* 100* 100*

n 276 277 299

average 51.03 43.37 50.43

Std-devA 21.58 20.37 20.58

Variance 465.69 414.93 423.53

variance / n 1.6873 1.4979 1.4165

Examination

T–test (2011-2010) 4.29 Degrees freedom 551 Probability 1.96

T-test (2011-2009) 0.005 573 1.96

Risk Level , α = 0.05 (95% confidence)

Since the T-value for the examination assessment 2011-2010 is larger than the probability, the

achievement of the 2011 cohort was significantly higher than that of the 2010 cohort.

Since the T-value for the examination assessment 2011-2009 is smaller than the probability, the

achievement of the 2011 cohort was not significantly different than that of the 2009 cohort.

There was a significant increase in the examination assessment scores between 2010 and 2011.

Is this the Answer?

34

Conclusions and Recommendations

1. What Colour Is Student Involvement in Lectures?

The average attendance at lectures was 74.2% of the 308 enrolled students.

It would seem that while student on-task attention is relatively high, with most involvement index

scores above 12/20, most of our lecturing strategies are still „content-focused‟ strategies that provide

little opportunity for direct student involvement.

It is perhaps not surprising that when there was higher use of content-focused strategies, the

involvement index decreased significantly as shown between involvement indices 18 to 16. However

these also corresponded to use of some class-input strategies during problem solving.

2. Use of Clicker Response system

From these a document „Comments from Clicker Questions‟ was placed on CECIL. This gave

feedback about the questions that showed the lowest correct response rate.

In a typical lecture only 30 to 40% of students in the lecture were using Clickers.

While there was a large group that did not respond well to the use of clickers, there was a reasonably

even spread of student responses, with over 54% (137) of students expressing support for their use. It

would seem that there is greater potential for use of clickers in lectures by requiring use of clickers as

part of the assessment system, even if the percentage recognition is low. This would at least give

lecturers a better view of student learning and increase active involvement of students.

Recommendation: That the use of clickers is extended to all lecturers in this course and that

there be an assessment component for participation with the clickers.

3. There was overwhelming support by students for use of problem solving in lectures so that students

could have time to think about strategies to solve the question. Over 80 % of students showed a

positive response to this strategy.

4. Over 78% of students supported the use of PowerPoint presentations to significantly help them

improve their understanding. It is suggested that this needs to be communicated to lecturers who still

do not use this strategy; there may be a need for some professional development.

5. Not surprisingly, over 80% of students supported the use of write-on-board explanations. However,

other lectures use equally effective strategies such as fill-in notes and these give students greater

opportunity for involvement.

Recommendation: The Physics Department should provide development of in-lecture strategies

to involve students more directly is required if students are to understand and

remember ideas more effectively and if they are not to experience cognitive overload.

Is this the Answer?

35

Recommendation: All lecturers should develop use of pre-lecture questions and reading of the text

and Power Point slides to support effective in-lecture learnin so that lectures

can evolve towards being more in the „lect-orial‟ style.

6. Since more than 68 % of students (± 1 σ) indicated they felt supported in the study of Physics 120FC

the combination of strategies should be continued.

7. The combination of strategies indicates that students are working reasonably cooperatively even in

aspects of the course excluding laboratory tutorials where cooperation was essential. Strategies such

as Team Based Learning show very positive effects on achievement that occur when cooperative

learning occurs. This response seems to indicate that students are benefiting from this

encouragement.

Cognitive Engagement

8. The data seems to indicate we have a balance of students that have a slight bias toward extraverted

intuiting (Ne). Ball and Perry‟s theory identifies that the students in Physics 120 do have a bias

towards being highly cognitively and being able to be engaged in many more types of activities

including working with other students both inside and outside class, making presentations, and in in-

class discussions.

It seems we should be reasonably confident that we can increase the range of activities including class

discussions and other interactions and know that most students will be capable of good cognitive

engagement in these.

9. The student cohort is strongly Extroverted Feeling (Fe) in Jung‟s Judgment Processes. This indicates

that over 68% (± 0.5 Standard Deviation-A) do prefer to learn ideas that have application and worth.

It signals to lecturers that leaning may occur best if contextual learning is used, giving actual

applications.

10. This question tested the extent to which students used the Perception process of extroverted

sensing. There is a reasonable balance showing that only about half of the students in the cohort

utilized their senses.

Recommendation: As part of lecture preparation there needs to be awareness by the lecturer to use a

greater variety of strategies to encourage students to perceive ideas fully

11. There is a strong bias of students showing introverted sensing. Over 70% expressed that they were

able to gather and organize, compare earlier learning and to gain a more accurate idea about Physics

through the teaching and learning strategies used.

Is this the Answer?

36

12. Ball and Perry indicate that the Extroverted Intuiting (Ne) student is highly cognitively engaged

in many more types of activities including working with other students both inside and outside class,

and in in-class discussions. It would seem that, since over 78% of Physics 120 students indicated a

score greater than 5.40, the cohort of students was highly engaged in cognitive activities.

13. In the question intended to determine the relative bias on the Introverted Intuiting Perception

Process, the data shows that over 70% of students are also strongly able to personally consider and

perceive ideas from several perspectives and have shown divergent thinking processes, enabling them

to correct misconceptions.

14. By applying Jung‟s „Eight-Functions Model‟ it has been possible to show that, in terms of

Cognitive Engagement, the 2011 cohort of Physics 120 FC students are strong in all of the Perception

Processes though there is a need for more strategies that will support the use of more student senses to

develop their extroverted sensing Perception Processes. This identifies a potential area for teaching

strategy development.

Applying socio-cultural theory using modified Team Based Learning

15. Students expressed very strong support for TBL. Informal feedback after TBL sessions provided

expressions of enjoyment and genuine involvement of teams. Over 77% expressed support for this

strategy. The graph of response distribution shows the high support by the majority of students

through its heavy bias at scores ≥ 5.

16. Students expressed strongly that Team Based Learning did help them improve their learning.

Again over 77% expressed support through scores ≥ 5.

17. Over 73 % of students recorded scores ≥ 5 showing very strong support for TBL as a strategy

that helps improve their assessment scores.

18. It seems that team-based learning was well received and contributed effectively to improving

student learning and understanding.

Quantitative analysis using T-Tests

19. The 2011 cohort‟s on-course achievements have shown to be significantly higher than the

achievements of either the 2009 or 2010 cohorts‟ achievements. The assignment and tutorial

strategies used have both contributed to the summative improvement in learning and achievement.

The tests have not contributed to any improvement to the on-course achievements though the Test 2

scores of the 2011 cohort have improved significantly as a result of the strategies being applied.

Is this the Answer?

37

20. The histograms attached as Appendix 3 show a gradual trend toward the decrease in the number

of students achieving in the D and D+ grade groups and a significant shift of these to the C and C-

groups.

21. While there was no significant statistical difference shown by Test 1, there were significant

differences between the 2009-2011 Test 2 and 2010-2011 Test 2 scores. This may be the result of the

accumulative effort being made throughout the semester, or from a difference in test standard.

22. Since the T-values for both the 2011-2009 and the 2011-2010 cohorts are higher than the

probability values, the total assignment achievement of the 2011 cohort was higher than either the

2010 or 2009 cohorts. It seems that some combination of the strategies implemented is contributing to

increase total test scores.

23. Since the T-value for 2011-2010 is larger than the probability, the achievement of the 2011

cohort laboratory tutorials was significantly higher than that of the 2010 cohort. The students

combined efforts in laboratory tutorials is increasing their scores significantly. The removal of the

peer assessment was likely to be a significant factor contributing to this increase in the laboratory

tutorial scores.

Recommendation:

Do not re-introduce the peer assessment strategy; rather consider use of bonus marks for the best

performing team each session.

24. Since the T-value for 2011-2009 is slightly smaller than the probability but less than the

probability value, the internal assessments achievement of the 2011 cohort was not significantly

different than that of the 2010 cohort. There was a significant increase in the internal achievement

scores between 2010 and 2011.

25. Since the T-value for the examination assessment 2011-2010 is larger than the probability, the

examination achievement of the 2011 cohort was significantly higher than that of the 2010 cohort.

Since the T-value for the examination assessment 2011-2009 is smaller than the probability, the

achievement of the 2011 cohort was not significantly different than that of the 2009 cohort. There was

a significant increase in the examination assessment scores between 2010 and 2011.

It is not possible to identify that the laboratory tutorials (Team Based learning) contributed significantly

to the improved achievement of students since there was a significant change made to the strategy.

Similarly it would be unwise to indicate that any other individual strategy contributed most significantly

to the improved achievement of students

Is this the Answer?

38

However, it seems that the combined effects of the changes resulting in the much greater

„student-centred‟ approach have significantly improved student achievement.

It was never intended to demonstrate and identify the relative effectiveness of one strategy over another

in this report. Rather, it has been possible to show that it has been possible to develop a combination of

strategies that together contribute to more effective learning and achievement. These strategies have

come from reciprocal development of stronger relationships between the course coordinator, lecturers,

tutors, demonstrators and students.

„The answer‟ seems to be that the strategies used should develop relationships, recognize and develop

student cognitive engagement, and provide a variety of learning and assessment approaches that builds

student efficacy and effectiveness. We may not know whether we can „keep them‟ immediately, but the

combination of strategies should contribute to students being encouraged to stay in Physics as they build

confidence and performance that competes with their performance in other subject departments.

“The idea itself -- getting students to solve problems in groups to make them both interact and learn -- is

great. Personally, I've witnessed a case when a group of 4 guys literally rose from not caring and doing

poorly to perfect work, understanding and enjoying the physics. That was highly satisfying to see, and I

think they loved that they could do it, too.”

Sophie Shamailov, graduate Physics student and Laboratory Tutor

The quality of your life is the quality of your relationships.

Anthony Robbins

Course Coordinator

Lecturers

Tutors

STUDENTS

Lab Demonstrators

Is this the Answer?

39

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Is this the Answer?

42

Appendix 1:

What Colour is Physics Student Active Involvement?

An observer in lectures randomly selected two groups of students in each lecture and recorded the

number of students who seemed to be on-task every 5 minutes. The lecture activity was also recorded .

Colours were assigned to the type of activity: red being activities that required independent work by the

student, orange being activities that were mostly student involvement, yellow

Data is presented in both tabular and graphical formats. Dated data displays for the first half of

Semester 1 2011 are provided.

Is this the Answer?

43

1st March

Time Group 1 Group 2

9:10 a.m. 10 10

9:15 a.m. 9 9

9:20 a.m. 10 8

9:25 a.m. 10 10

9:30 a.m. 9 10

9:35 a.m. 8 10

9:40 a.m. 8 9

9:45 a.m. 9 9

9:50 a.m. 8 8

9:55 a.m. 6 7

3rd March

Time Group 1 Group 2

9:10 a.m. 10 10

9:15 a.m. 10 10

9:20 a.m. 10 10

9:25 a.m. 8 9

9:30 a.m. 10 10

9:35 a.m. 9 9

9:40 a.m. 9 9

9:45 a.m. 9 9

9:50 a.m. 8 9

9:55 a.m. 8 10

10th March Vectors

Time Group 1 Group 2

9:10 a.m. 9 10

9:15 a.m. 8 10

9:20 a.m. 10 10

9:25 a.m. 8 10

9:30 a.m. 8 9

9:35 a.m. 10 10

9:40 a.m. 10 10

9:45 a.m. 10 10

9:50 a.m. 10 10

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

9:55 AM

# o

f st

ud

en

ts e

nga

ged

in le

ctu

re 1 03 11

Series1

Series2

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

9:55 AM

# o

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Series1

Series2

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

# o

f st

ud

en

ts e

nga

ged

in

lect

ure

10 03 11

Series1

Series2

Is this the Answer?

44

7th March Gas Laws

Time Group 1 Group 2

9:10 a.m. 10 10

9:15 a.m. 9 9

9:20 a.m. 9 10

9:25 a.m. 10 10

9:30 a.m. 10 10

9:35 a.m. 7 8

9:40 a.m. 7 7

9:45 a.m. 9 8

9:50 a.m. 9 8

9:55 a.m. 9 9

15th March Thermal transfers

Time Group 1 Group 2

9:10 a.m. 10 8

9:15 a.m. 8 10

9:20 a.m. 8 9

9:25 a.m. 6 9

9:30 a.m. 6 7

9:35 a.m. 8 9

9:40 a.m. 6 9

9:45 a.m. 10 10

9:50 a.m. 10 10

21st March Thermodynamic Processes

Time Group 1 Group 2

9:10 a.m. 10 10

9:15 a.m. 10 10

9:20 a.m. 9 8

9:25 a.m. 10 7

9:30 a.m. 10 10

9:35 a.m. 10 8

9:40 a.m. 7 7

9:45 a.m. 10 9

9:50 a.m. 8 7

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

9:55 AM

# o

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in le

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re 7 03 11

Series1

Series2

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

# o

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Series1

Series2

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

# o

f st

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ts e

nga

ged

in le

ctu

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21 03 11

Series1

Series2

Is this the Answer?

45

17th March

Time Group 1 Group 2

9:10 a.m. 9 9

9:15 a.m. 9 10

9:20 a.m. 10 8

9:25 a.m. 7 10

9:30 a.m. 8 7

9:35 a.m. 10 10

9:40 a.m. 10 10

9:45 a.m. 10 9

9:50 a.m. 9 10

24th March

Time Group 1 Group 2

9:10 a.m. 9 10

9:15 a.m. 10 10

9:20 a.m. 10 10

9:25 a.m. 7 10

9:30 a.m. 8 10

9:35 a.m. 8 7

9:40 a.m. 8 10

9:45 a.m. 8 10

9:50 a.m. 8 7

31st March

Time Group 1 Group 2

9:10 a.m. 8 10

9:15 a.m. 7 10

9:20 a.m. 9 9

9:25 a.m. 9 9

9:30 a.m. 6 8

9:35 a.m. 10 10

9:40 a.m. 8 8

9:45 a.m. 6 8

9:50 a.m. 7 10

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

# o

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17 03 11

Series1

Series2

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

# o

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ure

24 03 11

Series1

Series2

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

9:50 AM

# o

f st

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ts e

nga

ged

in

lect

ure

24 03 11

Series1

Series2

Is this the Answer?

46

0

2

4

6

8

10

12

9:1

0 A

M

9:1

5 A

M

9:2

0 A

M

9:2

5 A

M

9:3

0 A

M

9:4

0 A

M

9:4

5 A

M

9:5

0 A

M

9:5

5 A

M

# o

f st

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ts e

nga

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in

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ure

17 05 11

Series1

Series2

28th March Thermodynamics - Carnot Cycle

Time Group 1 Group 2

9:10 a.m. 10 8

9:15 a.m. 7 9

9:20 a.m. 9 6

9:25 a.m. 9 8

9:30 a.m. 9 9

9:35 a.m. 8 8

9:40 a.m. 9 8

9:45 a.m. 8 7

9:50 a.m. 8 6

4th April Heat Engines, Irreversible Processes

Time Group 1 Group 2

9:10 a.m. 10 10

9:15 a.m. 9 8

9:20 a.m. 9 8

9:25 a.m. 10 7

9:30 a.m. 9 8

9:35 a.m. 10 8

9:40 a.m. 9 7

9:45 a.m. 6 5

7th April Carnot Engines and Heat Engines

9:10 a.m. 7 8

9:15 a.m. 8 8

9:20 a.m. 9 7

9:25 a.m. 10 10

9:30 a.m. 7 6

9:35 a.m. 10 10

9:40 a.m. 7 7

9:45 a.m. 8 9

0

2

4

6

8

10

12

9:1

0 A

M

9:1

5 A

M

9:2

0 A

M

9:2

5 A

M

9:3

0 A

M

9:3

5 A

M

9:4

0 A

M

9:4

5 A

M

9:5

0 A

M #

of

stu

de

nts

en

gage

d in

le

ctu

re

28 03 11

Thermodynamics - Carnot Cycle Group 1

Thermodynamics - Carnot Cycle Group 2

0

2

4

6

8

10

12

9:10 AM

9:15 AM

9:20 AM

9:25 AM

9:30 AM

9:35 AM

9:40 AM

9:45 AM

# o

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en

ts e

nga

ged

in

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ure

4 04 11

Series1

Series2

Is this the Answer?

47

On-Task # Strategies

20

Class works exercise on own and discuss with neighbour

Worked example on w/board Lecturing on context/importance of information

Slides and demonstration

Worked example on w/board & class input

Explanation of notes demonstration

Demonstration on satellite problem

Clicker problem Admin slides Notes and examples on w/bd video

Demonstration Demonstration contd Demonstration

Lecturing

Explanation of slides Class working on problems Listening to application of new ideas Lecturing

Example Qn from slides Application of concepts Calculation on slides

admin info

Demonstration Worked example on WB Example calculation

Example on WB Definitions on WB Example on WB

Lecturing & notes on WB Lecturing from slides Lecturing & definitions on slides

Lecturing and definitions on slides

19 Lecturing

Example with class input

Historical development

Conceptual problem

Lecturing uniform circular motion Explanation of idea on W/Board Working through printed notes Worked example on bd with class input

Lecturing from slides

Example on WB

Notes on WB Revise solution of hmwk problem

Lecturing on WB

Example on WB & Qs to class

Example on WB

Example on WB

Concepts with demonstration

Is this the Answer?

48

18 Worked example on white bd and class input

Example from notes, worked through on slides and white bd.

Lecturing aspects of calculus from white bd

Lecturing from slides

Example on white bd.

Calculation on white bd

Calculation following printed notes

Example wked out on white bd

Explanation and notes on white bd

Lecturing from slides

Clicker Question

Explanation of graphics on slides

Lecturing from slides

Worked example on slides

Lecturing with slides

Derivation on WB

Wked example hmwk solution

Derivation of Work-energy theorem

Working through assignment type qn on white bd

Derivation of results related to demo

Notes and definitions on WB

Notes contd Lecturing notes on white bd.

Example calculation

Theroem derivation on WB Example on WB

Lecturing and notes on WB

Example on WB Example on WB

Example from text book

Derivation on slides Problems on WB

17 Slides and white board notes

Worked example on white bd

Worked example on white bd

historical account

Neighbour discussion of

demonstration

Example on white bd

Lecturing from slides

Lecturing from slides

Lecturing from slides

Discussion problem

Demonstration

worked problem on slides

Lecturing from slides

Clicker Question

Lecturing from slides and Qn for class

Class example with class input

Explanation of equn from slides

Example on WB to be done as hmwk Calculus based derivation

Example on white bd

Definition of Potential Energy explanation

Example on WB Calculations on WB

Lecturing from slides

Problems from text on WB

Example from text book on WB Definition on slides

Lecturing from slides

Lecturing from slides

Derivation on WB

Derivation on WB

Lecturing from slides

Example contd

Definition on WB

Lecturing & notes on slides

Example of theorem

Is this the Answer?

49

16 Lecturing from slides Lecturing from slides Lecturing & notes on white bd

Worked example on WB Solution of problem on WB Method of dimensional analysis

Revision problems on WB Example contd on WB Lecturing from slides

Lecturing from slides Derivation on WB Demonstration

Lecturing from slides & examples Concepts and definitions from slides

15 Demonstration and printed notes Working from printed notes example on white bd Lecturing from slides

Class problem solving on own Lecturing from slides Lecturing from slides Lecturing on WB

Class problem solving Class discussion of problem Example on WB

Lecturing from slides Lecturing from slides Demonstration and notes on WB

Discussing data from text book Example on WB contd Derivation on slides

Notes and demonstrations Lecturing from slides

14 Lecturing from slides

Using quiz questions

Example for class to work thro'

Lecturing from slides

Derivation of formula on WB

Example done on WB

Lecturing from slides & notes

Example on WB

Demonstration and notes on WB

Lecturing and explaining ideas

Problems on WB

13 Using slides to explain idea Work through problem on slides Demonstration

Lecture on WB Lecturing and definitions on WB Lecturing and definitions on slides

12 Lecturing from WB Derivation on White board Examples on WB Lecture from slides

Problems on WB Calculations on slides Example on WB

11 Examples on WB

10 Lecturing on slides

Is this the Answer?

50

Frequency Table for Each Level of Activity Active Participation Index

20 19 18 17 16 15 14 13 12 11 10

Class works exercise on own and discuss with neighbour 2 0 0 0 0 1 0 0 0 0 0

Clicker problem 1 0 1 1 0 1 0 0 0 0 0

Worked example on w/board & class input 2 3 2 3 0 1 2 1 0 0 0

Explaining idea 3 1 1 1 0 0 0 1 0 0 0

Example Qn from slides, demo, explain applications Exs on WB

14 7 9 11 5 5 3 1 2 0 0

Lecturing; admin; Explanation of slides 12 6 21 20 9 11 7 4 3 1 1

0

5

10

15

20

25

Fre

qu

en

cy o

f o

ccu

rre

nce

of

this

str

ate

gy

Total involvement index = sum of students involved

Frequency vs involvement index from two groups at 10 minute intervals

0

5

10

15

20

25

1 2 3 4 5 6 7 8 9 10 11

Fre

qu

en

cy p

er

22

lect

ure

s

Activity Level

Graph of frequency trend for each Activity Index value

Series2

Series3

Series4

Series5

Series6

Series7

Is this the Answer?

51

Appendix 2:

Achievement Groups and Profiles of Final Achievement Grades

Is this the Answer?

52

Table 1: 2009 Final Grades Achievement Data 2009 Physics 120FC Achievement Report Mark Grade Frequency

Score Frequency %

DNS 19

≥ 50 33.3 D- 23

≥ 49 44.4 D 36

≥ 48

49.2 D+ 26

# students sitting

exam 51.4 C- 21

54.3 C 17 59.3 C+ 46 64.2 B- 30 69.4 B 26 74.3 B+ 18 79.2 A- 18 84.4 A 8 98.8 A+ 22

Total 310

Graph: 2009 Histogram of Grade Frequency vs Grade

0

5

10

15

20

25

30

35

40

45

50

D- D- D+ C- C C+ B- B B+ A- A A+

Freq

uen

cy o

f st

ud

net

ach

ieve

men

t

2009 Frequency of Final Grades

Series1

Is this the Answer?

53

Table 2: 2010 Final Grades Achievement Data 2010 Physics 120FC Achievement Report Mark Grade Frequency

Score Frequency %

DNS

29

≥ 50 150 54.3

D- 26

≥ 49 157 56.9

D 60

≥ 48 161 58.3

D+ 17

# students sitting

exam

C- 17

C 39

C+ 27

Recommended Cut-Off

B- 35

Score No. students %

B 20

45.3 173 62.7

B+ 13

A- 9

A 5

A+ 8

Total 276

Graph: 2010 Histogram of Grade Frequency vs Grade

0

10

20

30

40

50

60

70

D- D D+ C- C C+ B- B B+ A- A A+

Freq

uen

cy o

f St

ud

net

ach

ieve

men

t 2010 Frequency of Grades

Series1

Is this the Answer?

54

Table 3: 2011 Final Grades

Achievement Data

2011 Physics 120FC

Achievement Report

Mark Grade Frequency

Score Frequency %

DNS

32

≥ 50 192 69.3

0 D- 8

≥ 49 201 72.5

29.5 D 24

≥ 48 208 75.1

41.5 D+ 19

# students sitting

exam 277

45 C- 28

49.5 C 36

54.5 C+ 34

Recommended Cut-Off

59.5 B- 34

Score No. students %

64.5 B 27

≥ 48.53 207 74.70%

69.5 B+ 27

74.5 A- 18

79.5 A 13

84.5 A+ 20

Graph: 2011 Histogram of Grade Frequency vs Grade

0

10

20

30

40

D- D D+ C- C C+ B- B B+ A- A A+

2011 Frequency of Grades