NATIONAL AND INSTITUTIONAL CHANGE AND SYSTEM AND INSTITUTIONAL PERFORMANCE INDICATORS

1. NATIONAL AND INSTITUTIONAL CHANGE AND SYSTEM AND INSTITUTIONAL PERFORMANCE INDICATORS Transformation Colloquium Rolf Stumpf 8 May 2013

2. STRUCTURE OF PRESENTATION • Introduction: Assessing change and role of quantitative data as part of a multifaceted assessment approach • Main sources of quantitative data DHET, CHE, CHET- examples • No data at all on staff and students with ‘disabilities’- serious shortcoming

3. DATA SOURCES: DHET • DHET’s national and institutional enrolment planning data derived from annual HEMIS submissions: Runs from 2000 onwards • Contains 44 tables indicating change over periods of up to 10 years • Covers student enrolments (headcounts and FTEs), student outputs, general staff data, academic staff data and research data • 44 tables cover public HE system but for each table individual institutional table also exists

4. DATA SOURCES: DHET • National data can thus be compared to individual institutional data • National set of 44 tables contains only two dimensional tables • Multi-dimensional tables – from original HEMIS source data: Allow analyses by large number of variables simultaneously • Example Table 2.12 represents series of student enrolment tables by mode of delivery, qualification level, CESM category, race, gender

5. DHET DATA: STUDENT ENROLMENTS Proportional headcount distribution by field of study (Table 9)

6. DHET DATA: STUDENT ENROLMENTS Proportional headcount distribution by field of study for African males and females for 2010 Source: Table 2.12

7. DHET DATA : STUDENT ENROLMENTS Proportional distribution of headcount enrolments by race (Table 13)

8. DHET DATA: STUDENT ENROLMENTS Proportional distribution of headcount enrolments by gender (Table 17)

9. DHET DATA: STUDENT GRADUATIONS • From Table 2.13 student graduations by mode of delivery, qualification type//level, CESM category, race and gender can be analyzed • From Table 3.3 university staff can be analyzed according to type of staff category and race and gender

10. DATA SOURCES: CHE DATA (VITAL STATS, 2010) • Comprehensive 2005-2010 analyses on large number of performance indicators • Data derived from HEMIS submissions but analyzed graphically • Aggregated across institutional data • Contains extensive list of definitions • Covers student enrolment data, student completions data, data according to 3 institutional types, staff data, cohort analysis of student throughputs

11. CHE DATA: STUDENT ENROLMENTS Proportional HC enrolments and population distribution (Fig 3)

12. CHE DATA: HE PARTICIPATION RATES Proportional HE participation rates according to race (Fig 5)

13. CHE DATA: STUDENT ENROLMENTS AND COMPLETIONS • Headcount enrolments as proportional comparison to population by gender (Fig 4) • Participation rates by gender (Fig 6) • HC enrolments by mode of delivery and race (Fig 13) and by gender (Fig 14) • HC graduates by mode of delivery and race (Fig 15) and by gender (Fig 16) • Graduation rates by race (Fig 17) and by gender (Fig 18)

14. CHE DATA: STUDENT COMPLETIONS Graduation rates by qualification level and race (Fig 19) • Graduation rates by qualification level and gender (Fig 20)

15. CHE DATA: STUDENT COMPLETIONS Success rates by race (Fig 21) • Success rates by gender (Fig 22)

16. CHE DATA: STUDENT ENROLMENTS AND COMPLETIONS • Success rates by qualification level and race (Fig 24) and by gender (Fig 25) • HC of UG enrolments by type of qualification by race (Fig 28) and by gender (Fig 29) • HC of UG qualifications awarded by race (Fig 30) and by gender (Fig 31) • HC of PG enrolments by type of qualification by race (Fig 32) and by gender (Fig 33) • HC of PG qualifications awarded by race (Fig 34) and by gender (Fig 35)

17. CHE DATA: STUDENT ENROLMENTS AND COMPLETIONS • Success rates by qualification level and race (Fig 24) and by gender (Fig 25) • HC of UG enrolments by type of qualification by race (Fig 28) and by gender (Fig 29) • HC of UG qualifications awarded by race (Fig 30) and by gender (Fig 31) • HC of PG enrolments by type of qualification by race (Fig 32) and by gender (Fig 33)

18. CHE DATA: HE PARTICIPATION RATES HC of PG qualifications awarded by race (Fig 34) • HC of PG qualifications awarded by race (Fig 34) and by gender (Fig 35)

19. CHE DATA: STUDENT ENROLMENTS AND COMPLETIONS AND STAFF • HC enrolments by field of study and by race (Fig 39) and by gender (Fig 40) • HC graduates by field of study and by race (Fig 41) and by gender (Fig 42) • HC staff members by employment status and race (Fig 55) and by gender (Fig 56)

20. CHE DATA: ALL STAFF Senior management staff by race (Fig 57) • Senior management staff by gender (Fig 58): 2005-29%, 2010-42%

21. CHE DATA: ACADEMIC STAFF Permanent academic staff by race (Fig 61) • Permanent academic staff by gender (Fig 62): 2005-41%, 2010-44%

22. CHE DATA: ‘ADMIN’ AND SERVICE STAFF • Admin staff by employment status and race (Fig 65) and gender (Fig 66) • Service staff by employment status and race (Fig 67) and gender (Fig 68) • HC Academic staff by qualification level by race (Fig 69) and gender (Fig 70)

23. CHE DATA: ACADEMIC STAFF DATA HC academic staff by qualification level by race (Fig 69) : Doctoral degree • HC academic staff by qualification level by gender (Fig 70): Doctoral in 2005 – 30% ; in 2010 - 35% .

24. CHE DATA: COHORT STUDY (EXCLUDING UNISA) Throughput rates for 360 credit diplomas by race – first enrolment in 2005 (Fig 75): Dropout in brackets

25. CHE DATA: COHORT STUDY (EXCLUDING UNISA) Throughput rates for 3year degrees by race – first enrolment in 2005 (Fig 78): Dropout in brackets

26. CHE DATA: COHORT STUDY (EXCLUDING UNISA) Throughput rates for 4year professional degrees by race – first enrolment in 2005 (Fig 81): Dropouts in brackets

27. DATA SOURCES:CHET • CHET’s Performance Indicator Project • Data derived from HEMIS submissions but applied differently • PI project’s aim: Measuring institutional performance – mainly for councils and senior management • 20 input and output indicators relating to general institutional performance • PI and institutional differentiation

28. DATA SOURCES:CHET • www.chet.org.za • Click ‘Data’ on home page • Click ‘South African Higher Education Open Data’ • Click ‘ Create graph’ • Click ‘ Click here to create a graph’ • Select an indicator from list of 20 indicators • Select up to 4 universities • Click ‘ Generate graph’

29. DATA SOURCES:CHET • Advantages • 20 indicators updated annually • Allows comparisons with up to 4 HEIs • Generates graphs and data for graphs given • Graphs and data can be downloaded • Glossary of terms used for each graph • Disadvantages • Limited number of indicators

30. CHET DATA: STUDENT ENROLMENTS • Enrolments by race for NMMU – Graph 1 • Enrolments by race – only White and African- for NMMU and for NMMU and NWU- Graph 2

31. CHET DATA : STUDENT ENROLMENTS – GRAPH 1

32. CHET DATA: STUDENT ENROLMENTS- GRAPH 1 • Enrolments by race for NMMU from 2000-2010 • Changes in proportional enrolment figures for NMMU influenced by: • Strategic decision by former UPE to downscale teacher education by distance education ( mainly African students) from 2003/4 onwards; • Merger of UPE, PE Technikon and Vista (Missionvale) to form NMMU in 2005.

33. CHET DATA: STUDENT ENROLMENTS – GRAPH 2

34. Conclusion: • Quantitative data and motivation for change • Quantitative data and assessment of change