1. INVESTIGATING SUCCESS in entry level modules at ukzn: 2005 – 2009
Delia North
Temesgen Zewotir
Michael Murray
SCHOOL OF STATISTICS AND ACTUARIAL SCIENCE
UKZN
UTLO Seminar, November 2011

2. Aim of the study
To investigate the effect of academic /demographic factors on successful progression of students in first year at UKZN between 2005 and 2009 Unpack performance of first year students
UTLO Seminar, November 2011

3. OUTLINE Background – setting the scene The Data Descriptive Statistics
Multi -Level Logistic Regression
Results: Factors affecting failure rates
Factors affecting drop out rates
Conclusion
UTLO Seminar, November 2011

4. Background HEI’s play a pivotal role in development of human capital
educational, social, economic and cultural
development of society
so that Governments around the world invest in
Higher Education
UTLO Seminar, November 2011

5. Funding of universities in South African
Department of Education (DOE) funds HEI’s – government funds HEI’s, focusing on two key outputs – student throughput and research productivity. Accordingly, each of the South African Universities has got their own strategies to improve deliverance on these outputs in order to secure the maximum share of the South African Higher Education budget
UTLO Seminar, November 2011

6. Identifying factors that are a threat to successful progression of students is vital for improving throughput rates - deans and other decision makers can put strategies in place for potential “at risk students” so that effective intervention strategies can be designed.
UTLO Seminar, November 2011

7. To inform strategies that improve throughput rates
we thus need to identify factors that increase the
risk of
* failure
* drop out
UKZN study: Entry level focus (North)
Modeling attrition – UG and PG (Zewotir)
Competing risks framework (Murray)
UTLO Seminar, November 2011

8. Relevance of this study
UKZN 7 years post merger and about to restructure. How do school results in English and Mathematics affect failure rates and drop out rates of first year students….and what other factors affect these rates? Valuable information for new Deans and Heads of schools, Teaching and Learning officers, etc.
Mention 15 August article in Sunday tribune
UTLO Seminar, November 2011

9. THE DATA DMI - 71 954 records of first year students
Year to 2009
faculty – 8 faculties
race – African, White, Other (Indian)
gender – male, female
alien – Yes, No
access – Yes, No
repeats – Yes, No
Maths –symbol and English symbol
residence – Yes, No
fin aid – Scholarship, Bursary, Loan, No financial aid
cleared – Yes, No, Out
Students first year until passed 96 credits
UTLO Seminar, November 2011

10. Descriptive Stats
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11. Change in racial profile of students in first year at UKZN between 2005 and 2009
14%
46%
40%
2009 5%
60%
35%
UTLO Seminar, November 2011

12. Fin aid profile change – more students on bursaries, fewer on scholarship
Scholarships
Bursary
Loan
No Fin Aid
2005
12%
14%
15%
58%
2009 4%
23%
16%
So see the profiles but how did these changes affect failure rates and drop out rates over the years???
UTLO Seminar, November 2011

13. Pattern of student success% NO
OUT
YES
2005
10.86
36.24
52.89
2006
10.48
37.32
52.2
2007
21.11
28.57
50.32
2008
17.91
30.9
51.19
2009
22.09
30.66
47.25
UTLO Seminar, November 2011

14. MULTI-LEVEL LOGISTIC REGRESSION Outcome of year 1: Fail, Left, Pass
This model produces odds ratio based interpretation Links odds of * No (Fail) vs Yes (Pass) * Out (Left) vs Yes (Pass) (Pass = baseline) to a set of exploratory variables (academic/demographic factors)
UTLO Seminar, November 2011

15. MULTI-LEVEL LOGISTIC REGRESSION Outcome of year 1: Fail, Left, Passed
Odds are relative to students passing
UTLO Seminar, November 2011

16. UTLO Seminar, November 2011

17. UTLO Seminar, November 2011 RESIDENCE (REFERENCE: IN UKZN RESIDENCE)
NOT IN UKZN RES
FAILED
1.49*
1.10
1.23*
1.59*
1.24
1.51
1.40*
1.29*
LEFT
1.01
1.47*
1.14*
1.90*
1.44
1.21*
REPEATS OF YEAR 1 (REFERENCE: REPEATING YEAR 1)
FIRST ATTEMPT of YEAR 1
0.01
0.02
0.58*
0.24*
0.90*
0.72*
0.34*
0.41*
0.75*
1.30*
CITIZENSHIP (REFERENCE: NOT SOUTH AFRICAN)
SOUTH AFRICAN
1.57
1.62
1.36
1.86
0.10
0.00
1.75
1.67*
1.69
1.34*
3.38*
0.88
267.89
1.18
1.76*
UTLO Seminar, November 2011

18. ACADEMIC SUPPORT PROGRAM (REFERENCE: IN ACADEMIC SUPPORT PROGRAM)
NOT IN AC SUPPORT PROGRM
FAILED
0.74
1.21
0.77*
1.42
0.10
7.40*
0.63*
0.90
LEFT
0.60*
1.45*
0.64*
1.62*
2.17
0.60
0.79*
0.76*
EFFECT SCHOOL MATHS MARK
MATHS AT SCHOOL
1.00
0.89*
1.08
0.91
1.45
0.99
0.97
MATHS
AT SCHOOL
1.17*
1.04
1.01
1.27*
1.09*
1.19
1.11*
1.02
EFFECT OF SCHOOL ENGLISH MARK
ENGLISH AT SCHOOL
0.93
1.29*
1.06
1.65*
1.40
0.98
1.05
1.16*
1.64*
1.26*
1.19*
1.14*
UTLO Seminar, November 2011

19. CONCLUSION
Faculties differ…..Heads of Schools/Deans and Teaching and Learning officers in colleges and schools are tasked to put strategies and processes in place to monitor and prevent student drop-out and failure, so this study should be of value to review current selection and teaching practices as the university heads to a restructure in 2012.
UTLO Seminar, November 2011

20. UTLO Seminar, November 2011

21. UTLO Seminar, November 2011

22. Changes in first year throughput over the period 2005 to 2009
Failure risk
Increased over 2005 to 2009: HDSSc, MntS
Decreasing over 2005 to 2009: ENG, HSc, MED, ScA
Drop-out risk
Increasing over 2005 to 2009: EDU
Decreasing over 2005 to 2009: ScA
UTLO Seminar, November 2011

23. Effect of Race Failure risk
African > White: EDU, HDSSc, HSc, MntS, ScA
White students > Indian: EDU
Drop-out risk
African > White : EDU, HSc, MntS, ScA
Indian > White: ENG, HDSSc, ScA
White > Indian: EDU, HSc, MED, MntS
UTLO Seminar, November 2011

24. Effect of Gender Failure risk Male > Female : EDU
Female > Male : HSc
Drop-out risk
Male > Female : EDU, LAW
Female > Male: HSc
UTLO Seminar, November 2011

25. Effect of Financial Aid
Failure risk
Scholarship > Bursary : ENG, MntS, ScA
Scholarship > Loan : ENG, ScA
Scholarship > No Fin Aid: ENG
Drop-out risk
Scholarship > Bursary: ENG, EDU, HSc, MntS,
Scholarship > Loan: EDU, HSc, ScA
No Financial Aid > Scholarship:
ENG, EDU, HDSSc,HSc, MntS, ScA
UTLO Seminar, November 2011

26. Effect of Residence (On campus or not)
Failure risk
Not UKZN campus > UKZN campus :
ENG, HDSSc, HSc, MntS, ScA
Drop-out risk
Not UKZN campus > UKZN campus:
EDU, HDSSc, HSc, LAW, MntS, ScA
UTLO Seminar, November 2011

27. Effect of repeating year one
Drop-out risk
Repeating Yr 1 > First attempt at Yr 1:
ENG, EDU, HDSSc, HSc, LAW, MED, MntS
First attempt at Yr 1 > Repeating Yr 1: Sc A
UTLO Seminar, November 2011

28. Effect of citizenship Drop-out risk
South African citizen > non- South African citizen:
ENG, HDSSc, HSc, ScA
UTLO Seminar, November 2011

29. Effect of academic support programs
Failure risk
academic support > not academic support:
HDSSc, MntS
academic support > not academic support: MED
Drop-out risk
ENG, HDSSc, MntS, ScA
not academic support > academic support: EDU, HSc
UTLO Seminar, November 2011

30. Effect of school Mathematics and English results
Failure risk Higher for better school Math mark: HDSSc Lower for better school English mark: EDU, HSc Drop-out risk Lower for better school Math mark: ENG, HSc, LAW, MntS Lower for better school English mark: HDSSc, HSc, Law, MntS, ScA
UTLO Seminar, November 2011

31. Humanities, Development and Social Sciences: Odds Fail vs Pass
African students are 50% more at risk of failing than White students
Students not in on campus res have increased odds (23%) to fail
Further contributing factors to failing in this faculty are those on academic support programs…..and those with better marks for Mathematics at school!
UTLO Seminar, November 2011

32. Engineering : Odds Out vs Pass
Indian students are the biggest racial group dropping out of this faculty in first year (29% more of a risk than White students)
Students with no financial aid are almost twice more likely to drop out than those with scholarships
Students repeating year 1 are almost twice as likely to drop out than first time registrations in year 1
South African students have 1.67 times the odds of dropping out than students from other countries
Better marks for school maths results in lower risk of dropping out
UTLO Seminar, November 2011

33. Threat: throughput rate
Evidence that a smaller proportion of students are passing level 1 (53% ->47%), more are failing and staying in the system (11% - 22%). Profile Change -> student race, fin aid, gender, etc -> students success profile ???? Which factors contributed to the risk of first year students failing or dropping out as opposed to successfully passing to level two modules.
UTLO Seminar, November 2011