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Teaching Thermodynamics with Collaborative Learning Larry Caretto Mechanical Engineering Department June 9, 2006.

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Presentation on theme: "Teaching Thermodynamics with Collaborative Learning Larry Caretto Mechanical Engineering Department June 9, 2006."— Presentation transcript:

1 Teaching Thermodynamics with Collaborative Learning Larry Caretto Mechanical Engineering Department June 9, 2006

2 2 Outline Background Teaching method – Spend 50% of class time on group work – Use weekly quizzes to keep students current Assessment Conclusions

3 3 Background Personal motivation for this approach – Long term interest in getting students involved with discussion during lecture – Educational research shows benefits of active learning versus lecture for student learning – Survey data shows that students now spend less time outside of class doing work than previously ABET wants assessment and improvement President Koester’s learning-centered university initiatives

4 4 Koester on a learning centered university (August 21, 2003) Learning in and outside classroom Specified learning outcomes Shift focus from teaching to learning – Learning is “cumulative consequence and judgments for all aspects of the learning environment” Document what students learn

5 5 ABET accreditation criteria are learning centered ABET has already focused engineering education on cumulative result – Having graduates meet overall objectives and outcomes is key to accreditation – ABET also emphasizes assessment and continuing improvement – Improvement means that we have to examine our practices as they effect student learning – ABET requires documentation of results

6 6 How to improve student learning in an individual class? Basic assumptions – Students do not devote much time outside class to work on homework problems to learn material – In class lecturing, without active student participation is not effective use of time – Students need motivation to learn material on a regular basis Each of these is addressed by the practices discussed here

7 7 Outline

8 8 Course organization and teaching schedules The course is organized into twelve subject- matter units, each taking one week Each unit contains – Lecture on new material for 30 – 40 minutes – Group problem solving for 75 minutes – A 30 minute quiz – Feedback on quizzes for 5 – 15 minutes Two different schedules tested and student preferences assessed

9 9 Course organization with initial schedule Each unit has the following time distribution – 30 to 40 minute lecture on new course material on day N – 75 minute group work session solving problems on new material with instructor providing help as needed on day N+1 – 30 minute quiz on material with 5 to 15 minutes of follow up discussion of quiz on day N+2

10 10 Initial Weekly Schedule of Activities TuesdayThursday Quiz on previous week material – 30 minutes Group problem solving Feedback on quiz solution 5 – 15 minutes Lecture on new material 30 – 40 minutes

11 11 Course organization with modified schedule Each unit has the following time distribution – Feedback on previous quiz 5 to 15 minutes on day N – 30 to 40 minute lecture on new course material on day N – 30 minute simple group exercise on day N – 45 minute group work session solving problems on new material with instructor providing help as needed on day N+1 – 30 minute quiz following group work on day N+1

12 12 Modified Weekly Schedule of Activities TuesdayThursday Group problem solving on material presented previous Thursday 45 minutes Return quiz and discuss difficult points (5 – 10 minutes) Lecture on new material 45 minutes Quiz on material covered in group problem solving 30 minutes Initial group problem solving (20 – 25 minutes)

13 13 Lecture notes Lectures use power point slides Students asked to respond to questions on slides during lecture, but no assessments of responses collected Handout sheets of slides made available on web for students to download Students find notes more useful than lectures themselves

14 14 Group problem-solving sessions – initial schedule Students self select groups (3 to 5 students) Problems handed out at start of class – Typically two problems to illustrate essential kinds of problems for week’s material – First problem is subdivided into steps that lead students through solution – Second problem does not provide steps Solutions posted on web after class

15 15 Group problem-solving sessions – modified schedule On day of quiz the group activities are similar to those of the initial schedule – Solutions posted on web after quiz On day of lecture there is a brief problem solving session that asking students to solve a modification of an example problem presented in lecture – Solutions included as part of lecture notes

16 16 Instructor role in group work sessions Prepare and hand out problems Get students working and encourage group interaction in dysfunctional groups Answer group questions and interrupt all groups to clarify common questions Lead discussion in final five minutes to review what students have learned and give hints for unsolved problems

17 17 Typical semester schedule for 30 classes of 75 minutes each 24 days to cover 12 instructional units with the cycle of lecture – group work – quiz 1 day for introductory lecture 2 days to review for midterm and administer midterm 2 days at end of semester for final review 1 holiday

18 18 Course elements and weighting in final grade Homework assigned but not collected; solutions posted on course web site Quizzes count 30% of total grade Midterm 20% Final 30% Writing assignment 10% Design project 10%

19 19 Outline

20 20 Five semesters of data Assessments based on students present on day of assessment; grade distribution based on total enrollment – Spring 2003: 20 students; 16 assessments – Fall 2003: 30 students; 29 assessments – Fall 2004: 31 students; 19 assessments – Spring 2005: 31 students; 23 assessments – Spring 2006: 32 students; 24 assessments – Total is 144 students and 111 assessments

21 21 Which schedule do students prefer? Switched schedule after spring break Asked preference with five responses – Initial much better (numerical score 2) – Initial better (numerical score 1) – No difference (numerical score 0) – Modified better (numerical score -1) – Modified much better (numerical score -2) Used numerical scores for statistical analysis

22 22 Results of student preferences regarding schedule

23 23 Mean student opinion is no difference in schedules Average scores for two semesters are 0.09 and -0.04 (0 is no difference) p values for null hypothesis that mean is zero are 0.81 and 0.90 for the two semesters Although the mean score is no difference there are sharp differences of student opinion about which schedule is better

24 24 Assessment questions Students value course elements in helping them learn course material – Preparation for quizzes and examinations – Group work – Text reading and homework assignments – Lectures and downloaded lecture notes – Writing assignment and design project Short abbreviation for these items shown on next chart

25 25 Not useful Some- what useful Students value of course elements for their learning Very useful Useful

26 26 Students perception of course load and difficulty Compare following items to other engineering courses – Time spent studying for course – Amount of material presented in course – Degree of difficulty of course material – Level of understanding of course material Abbreviations for these items used on next chart shown in bold italics above

27 27 Much less About the same Somewhat less Students’ perceptions of course material and work required Much more Somewhat more

28 28 Grade distributions

29 29 Students self-evaluation of how well they learned course topics Very good Good Adequate Poor Very poor

30 30 Conclusions Assessed student opinion of course activities that help them learn the material better This presentation covers one approach for teaching one course – Five classes with a total of 144 students (111 assessment forms) and no control group With this approach, students assess group work, downloaded notes and exam preparation as most helpful items in learning


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