1. Lecture attendance does matter: evidence from lecture attendance in psychology classes Prof. Andrew Thatcher, University of the Witwatersrand

3. Psychology Classes Characterised by large student registrations (>250) At Wits, instruction is face-to-face classroom (supplemented by tutorials) interaction where lecture attendance is not compulsory Anecdotal evidence (at Wits) of poor classroom attendance Anecdotal evidence of poor classroom participation

4. Raises important questions Is the anecdotal evidence true? If it is true, why aren’t students attending lectures? What is the perceived purpose of lectures if many students don’t attend? How do these perceived purposes differ between lecturing staff and students?

5. Possible factors in non-attendance Lecturer characteristics (poor lecturing methods, boring style, etc.) Student characteristics (motivation, ability, perceptions, etc.) Extraneous factors (finances, etc.)

6. Pilot study - appearing SAJP, 37(3), pp. 656-660 9 registers taken randomly across 7 weeks of a 2 nd year class (289 registrations) Linked to performance on academic assignments (test, essay, examination, and the total mark) Removed from analysis any assignments not submitted

7. Attendance patterns 0 attendances: 14 students (5%) 9 attendances: 13 students (5%) 4 attendances or fewer: 140 students (48%) Largest lecture attendance: 189 students (65%) Smallest lecture attendance: 115 students (40%) Average attendance: 147 students (51%)

8. Attendance related to academic performance (correlations) All significant (p<0.01), but moderate: –Test: 0.28* –Essay:0.18* –Examination:0.20* –TOTAL:0.26*

9. Attendance related to academic performance (ANOVAs) Re-categorised groups due to problems in register collection: –0 – 1 registers: NEVER –2 – 4 registers: SELDOM –5 – 7 registers: FREQUENTLY –8 – 9 registers: ALWAYS

10. Attendance related to academic performance (ANOVAs) - TEST ALWAYS > NEVER and > SELDOM FREQUENTLY > NEVER

11. Attendance related to academic performance (ANOVAs) - ESSAY ALWAYS > SELDOM

12. Attendance related to academic performance (ANOVAs) - EXAM ALWAYS > NEVER

13. Attendance related to academic performance (ANOVAs) - TOTAL ALWAYS > NEVER and > SELDOM

14. Observations from the pilot study Academic performance clearly related to attendance –Academic benefits related to attendance (knowledge & comprehension; hint & tips) Academic performance made up of so much more than simple attendance –Ability, past knowledge and experience, motivation, learning/studying style, assignment coping style

15. Current research 3 large classes (1 st, 2 nd, 3 rd year) across 14 weeks of term Questionnaires probing reasons for attendance/non-attendance; motivation for University, and learning styles Telephonic interviews with non-attendees Interviews with lecturers regarding lecturing style and purpose of lectures Focus groups with students regarding lecturing style and purpose of lectures Related to student data (e.g. past performance, matric., gender, race, etc.)

16. 3 rd Year attendance patterns Class 1: 114 students, 6 registers (over 7 weeks) 0 attendances: 2 students (2%) 6 attendances: 11 students (10%) Correlations: –Test:0.26* –Essay:-0.02 –Examination:0.20* –Overall:0.22*

17. 3 rd year attendance related to academic performance (ANOVAs) - TEST ALWAYS > NEVER and > FREQ

18. 3 rd Year attendance related to academic performance (ANOVAs) - TOTAL ALWAYS > NEVER

19. 3 rd Year attendance patterns Class 2: 102 students, 10 registers (over 7 weeks) 0 attendances: 3 students (3%) 10 attendances: 4 students (4%) Correlations: –Assignment:0.26* –Essay:0.27* –Examination:0.02 –Overall:0.19

20. 3 rd year attendance related to academic performance (ANOVAs) – Assign. ALWAYS > NEVER FREQ > NEVER

21. 3 rd year attendance related to academic performance (ANOVAs) - ESSAY ALWAYS > NEVER

22. 2 nd Year attendance patterns 233 students, 16 registers (over 14 weeks) 1 attendance: 13 students (5.6%) 16 attendances: 6 students (2.6%) Correlations: –Test 1:0.29*Test 2:0.29* –Essay 1:0.12Essay 2:0.20* –Examination:0.26* –Overall:0.28*

23. Attendance related to academic performance (ANOVAs) – TEST1 ALWAYS > NEVER FREQ > NEVERSELDOM > NEVER

24. Attendance related to academic performance (ANOVAs) – TEST2 ALWAYS > NEVER FREQ > NEVER

25. 2 nd Year attendance related to academic performance (ANOVAs) - EXAM ALWAYS > NEVER FREQ > NEVER

26. 2 nd year attendance related to academic performance (ANOVAs) - TOTAL ALWAYS > NEVERFREQ > NEVER ALWAYS > SELDOM

27. 1 st Year attendance patterns 280 students, 15 registers (over 14 weeks) 1 attendance: 13 students (4.6%) 15 attendances: 7 students (2.5%) Correlations: –Test 1:0.11Test 2:0.007 –Essay 1:-0.001Essay 2:0.08 –Examination:0.04 –Overall:0. 06

28. Why the lack of relationship at 1 st Year? 1 st year closely follows textbook (students can learn just as easily from textbook) Misalignment of assessments with classroom teaching MCQ examinations not linked to deeper understanding obtained in classroom Class sizes too large for effective T&L Attendance doesn’t matter at 1 st year

29. Inter-related factors Academic performance and attendance inter- related (partial-out past performance) Those with higher ability might also have higher attendance habits Academic performance and class attendance highly inter-related with student motivation (assessing motivation as a covariate) Other factors serve to confound attendance (e.g. financial constraints, study habits, etc.)

30. Possible reasons for non-attendance Internal student factors (e.g. motivation, commitment, interest, ability, self-esteem, language differences, learning styles/preferences, etc.) External student factors (e.g. socio-economic context, transport, family commitments, overlapping study commitments, etc.) Lecturer/Lecture factors (e.g. boring content, boring lecturer, lecture size, alienation in lecture, de- individuation in lectures, lack of active participation, etc.)

31. Possible solutions All solutions should be guided by research and reasons for non-attendance A.Making lectures compulsory B.Provide lectures in alternative media formats C.Improve student motivation (classroom exercises and selection D.Informed decision-making for students

32. Problem-solving workshop Workshop to discuss possible solutions based on research and data reporting Invitation extended to interested parties regionally and nationally Scheduled for 1 st quarter of 2008 (during Wits University’s T&L week) More information available later this year Please leave business card/contact details if you wish to attend

33. Prof. Andrew Thatcher Associate Professor Department of Psychology School of Human & Community Development Email: Andrew.Thatcher@wits.ac.za http://www.wits.ac.za/psyc212/andrewthatcher.htm