Factors Affecting Exam Absence in an ODL institution: The Case of UNISA

1. Factors Affecting Exam Absence in an ODL institution: The Case of UNISA Presentation by Lerato Sonia Tladi Institutional Researcher Department of Information and Strategic Analysis (DISA)

2. Structure of the Presentation • Introduction • Methodology • Results • Demographics • Academic Representation • Main Reasons for Exam Absence • Exam Preparedness • Reasons Unprepared • Exam Support • Academic Support from Lecturer • Tutorial Classes • Unisa Counseling Support • Study Time • Perceived Consequences of Exam Absence • Unisa Exam Support • Conclusion

3. Introduction • Efforts to improve the University of South Africa (Unisa)’s course success rates are thwarted not only by failure, but also attrition prior to writing. • Analyses have shown that a significant proportion of students who are admitted to exams do not write for a variety of reasons. • At the final signoff meeting for the exam results of the 2009 Oct/Nov sitting, it was decided to investigate the reasons for exam absence among Unisa students. Accordingly, the Department of Information and Strategic Analysis(DISA) was requested to design and conduct a survey to do this and to report by the end of January. • The survey was designed to investigate all probable reasons for exam absence – both academic & non-academic. The survey questionnaire comprised 13 questions & 158 items. Relevant students were identified (Problem of not being able to distinguish absentees from results outstanding, practical & PG students). Survey notification was sent by e-mail & SMS with link to access electronic survey toapproximately 27,000 students. • By January 25th 2010, 2359 students had submitted full responses, that is, an 8.7% response rate. By February 2nd, the total response rate was 5105 responses of which 3747 were full responses. At the closure of the survey, the number of full responses was 3865. This presentation presents the main findings of this survey and recommendations for action.

4. Methodology Data Collection Analysis Saved responses were extracted from Lime Survey into Ms Excel and then SPSS. Students’ demographic data was extracted from the student database using their student numbers as primary key. This data was then matched with student responses and then analyzed using SPSS. Given the nature of the majority of the key questions, Multiple response analysis was employed to analyze the data and Ms Excel was used to graph the results. • Data was collected usingLime Survey, an online questionnaire design and administration tool. A link to this survey was sent to all students who had missed one or more examinations via e-mail and sms. • Students could then access the survey using the link through either their WAP enabled mobile phones or through the internet. • Completed and incomplete surveys were saved on Lime Survey by the students after which the survey team imported the completed survey results to Ms Excel and SPSS for data analysis.

5. Methodology Sample Size Limitations/Errors Errors resulting from the type of the questionnaire: since this was a self-administered questionnaire, there is a possibility that some of the questions were unclear to participants thus leading to inaccurate responses, partly completed questionnaires or no-response at all. Errors resulting from incorrect filling in, punching, typing errors, etc. Active deception on the part of the respondents Passive deception on the part of the respondents(due to lack of accurate knowledge etc) Non-response Bias • N=27,387 • n1(respondents)=3,865 • n2(analysis)=3,738

6. Racial Breakdown (%)

7. Gender…

8. College

9. Qualifications

10. Exam Preparedness

11. Preparedness by College

12. Preparedness by Qualification Non-formal certificate taken out(only 2 respondents)

13. Preparedness by Race

14. Reasons Unprepared

15. Reasons Unprepared by College

16. Reasons Unprepared by Qualification

17. Academic Support from Lecturer

18. Why Lecturer not Contacted

19. Why Lecturer not Contacted

20. Why Lecturer not Contacted

21. Tutorial Attendance

22. Tutorial Ratings

23. Why Tutorials Not Attended

24. Unisa Counselling Support

25. Experience with Counselling Services

26. Why not Contact Counselling Services

27. Consulted Anyone re: Exam Decision

28. Enough Study Time

29. Why not Enough Study Time

30. Why not Enough Study Time

31. Why not Enough Study Time

32. Why not Spend Enough Time Studying

33. Why not Spend Enough Time Studying(College)

34. Why not Spend Enough Time Studying (Qualification)

35. Why not Spend Enough Time Studying (Race)

36. Exam Absence Consequences (by Race)

37. Absence Consequences

38. Absence Consequences by College

39. Absence Consequences by Qualification

40. Absence Consequences by Race

41. Why no Absence Consequences

42. Why no Absence Consequences (College)

43. Why no Absence Consequences (Qualification)

44. Why no Absence Consequences (Race)

45. Unisa Exam Support

46. Main Findings, Conclusion & Recommendations • Proportionately fewer Africans absent; proportionately more White students • Proportionally fewer females absent; proportionally more males • Proportionally fewer from CEMS, CHS; proportionally more from CSET and, marginally, from CAES and CLAW • Proportionately more from UG certificate/diplomas absent

47. Main Findings, Conclusion & Recommendations The overall findings corroborate the conceptual framework adopted for addressing success and retention at Unisa: • Despite being predominantly prepared for examinations and aware of the consequences of absence, the majority of students miss examinations due to factors beyond their control as well as non-academic factors • Topping the list of these factors are time-related work responsibilities as well as domestic responsibilities • Despite acknowledging the need to contact lecturers, tutors & counsellors, many students do not do so, mainly for time reasons but also due to perceived poor service & logistic obstacles

48. Main Findings, Conclusion & Recommendations In addition, however, attitudinal, motivational and social factors also impact strongly, despite awareness of consequences in most cases • A 3rd of respondents who indicated they had enough time to study did not spend enough time for these reasons • Almost 60% of those indicating that there were no consequences indicated that they felt they could simply write again at the next opportunity. Should Unisa reduce such opportunities?

49. Main Findings, Conclusion & Recommendations • Given that the majority of Unisa students are part-time, facing numerous non-academic commitments, Unisa faces a serious challenge in providing pre- and post-registration guidance and support to ensure realistic study loads • This is being addressed by Task Team 6 and also in MyChoice@Unisa • Unisa must expand and improve its tutorial, counseling and lecturer support services and help provide better access to these services to address motivational and attitudinal factors • This is being addressed by Task Team 4: Learner Support Framework • However, the onus rests on the students to make the time to access these services. This expectation must be communicated clearly to students

50. Main Findings, Conclusion & Recommendations • Operational factors should be vigorously pursued • Study material delivery • Availability of lecturers • Exam timetable flexibility • Tutorial classes logistics • This survey should be repeated regularly as part of Unisa’s emerging student intelligence system in order to track trends