PERFORMANCE INDICATORS AND INSTITUTIONAL CASE STUDIES University of Ghana 8 May 2012

1. PERFORMANCE INDICATORS AND INSTITUTIONAL CASE STUDIES University of Ghana 8 May 2012

2. INTRODUCTION This presentation draws on CHET’s recently published report Cross-National Performance Indicators: a Case Study of Eight African Universities. Eight universities selected for inclusion in the performance indicator project. Each is regarded as the most prominent (or “flagship”) public university in the participating country. They are: University of Botswana University of Cape Town University of Dar es Salaam Eduardo Mondlane University University of Ghana Makerere University University of Mauritius University of Nairobi The final data sets collected from the universities enabled CHET to produce descriptive and performance indicator profiles for the eight universities. The text of each institutional profile appears on the CHET website.

3. The focus of the performance indicators produced is on what CHET has described as the academic core of each university. The academic core consists of the inputs available for the delivery of teaching and research, and the research and teaching outputs which the university produces on basis of these inputs. The graphs and analyses which follow use the academic core data for four of the eight universities. The main reason is that they are the largest of the five universities who were able to give CHET data for years beyond the original cut-off date of 2007. HERANA’s eight academic core goals, and their related targets, are identified in various of the graphs which follow.

4. TOTALSTUDENT ENROLMENTS (1) A head count enrolment is literally a “counting of heads”, because a registered student = I unit regardless of her/his course load. Ghana’s enrolment increased by 20 200 (or 132%) over the 9-year period. Graph 1

5. TOTAL STUDENT ENROLMENTS (2) Full-time equivalent (FTE) enrolments take account of course loads. One FTE student = a student following a full curriculum for an academic year. So a part-time student taking 50% of a curriculum = 0.5 FTE students. Graph 2

6. TOTALSTUDENT ENROLMENTS (3) Average annual growth rates have been calculated from the enrolment totals in Graphs 1 and 2. Ghana had considerably higher growth rates than the other three universities. Graph 3

7. TOTALSTUDENT ENROLMENTS (4) Science & technology includes agriculture, architecture, computer sciences, engineering, health sciences, life and physical sciences, mathematical sciences Business and management cover accounting, auditing, banking, public finance, investments and securities, taxation, insurance, marketing, human resource management Humanities and the social sciences includes the visual and performing arts, education, languages and literature, psychology, philosophy, social services, sociology, political studies, history Graph 4 on the next slide shows that Ghana has been a predominantly humanities and social sciences university. In 2001/2 7500 students (62% of the total) and in 2009/10 20700 (64% of all students) were registered for programmes in these fields. Enrolments in science & technology programmes rose from 2900 (or 19% of the total) in 2001/2 to 9400 (26%) of the total in 2009/10. Ghana’s proportion of science and technology students was in 2009/10 well below those of Cape Town (41%) and Makerere (40%). Makerere had changed its proportion of humanities and social sciences from 65% in 2001/2 to 50% in 2009/10. HERANA’s target is: 40% of student enrolments to be in science and technology programmes.

8. Graph 4

9. TOTALSTUDENT ENROLMENTS (5) Masters and doctoral enrolments are central components of high level knowledge production. Graph 5 shows what average shares masters and doctors have had of head count enrolments. HERANA’s target is: 15% of enrolments to be masters and doctors students. Graph 5

10. TOTALSTUDENT ENROLMENTS (6) Graph 6 shows what changes occurred in head count doctoral enrolments between 2001/2 and 2009/10. Ghana’s doctoral student enrolment grew from 92 in 2001/2 to 249 in 2009/10. Graph 6

11. GRADUATES (1) Graph 7 is a productivity indicator. It shows what the annual totals of graduates were during 2001/2 to 2009/10. Ghana’s total increased from 2900 in 2001/2 to 7200 in 2009/10. Graph 7

12. GRADUATES (2) Graph 8 is an efficiency indicator. It compares average annual increases in head count enrolments and in total graduates. HERANA’s target is: average annual increases in graduates should exceed average annual increases in enrolments Graph 8

13. GRADUATES (3) Graph 9 is a further efficiency indicator. It sets out standard measures of graduate output efficiency used in the South African higher education system. These indicators are based on the ratios between graduate qualifiers in any given year and undergraduate student enrolments in that same year. These ratios are converted into cohort output equivalents which indicate what proportions of groups of undergraduate students entering a university for the first time can be expected to finally complete their qualifications and graduate. For example, a cohort output equivalent of 60% indicates that only 60 of every 100 undergraduate students entering a programme of studies for the first time are likely to complete their qualifications. The remaining 40 students would drop out without completing their qualifications. HERANA’s target is: a cohort output equivalent of 75% in each broad field of studies.

14. Graph 9

15. ACADEMIC STAFF (1) Academic staff are employees who spend at least 50% of their official time on duty on instruction and/or research activities. A permanent staff member is an employee who either contributes to an institutional retirement fund or is employed on at least a three year contract. A full-time equivalent (FTE) staff member is an employee who is paid on a full-time basis for 12 months. So an academic who is paid full-time for 4 months = 0.33 FTE employees, and one who is paid 50% for 12 months = 0.5 FTE employees. Graph 10 on the next slide gives the totals of permanent academics employed by the four universities during the period 2001/2 to 2009/10.

16. ACADEMIC STAFF (2) Graph 10

17. ACADEMIC STAFF (3) FTE academic staff totals are better measures than permanent staff of the resources which a university has available for teaching and research. Calculating FTE staff totals has been a problem for most universities on the HERANA project. The data below suggest that Ghana makes little use of part-time or temporary academics. Graph 11

18. ACADEMIC STAFF (4) • Graph 12 on the next slide uses the FTE academic staff data provided by the four universities to calculate FTE student to FTE academic staff totals within the three broad fields of (a) science and technology, (b) business and management, and (c) humanities and social sciences. • These ratios indicate what staffing resources each university has been able to allocate to the teaching of students within these fields of study. • HERANA’s targets are: • science and technology programmes: a maximum ratio of 16 FTE students per FTE academic staff member • (2) business & management programmes: a maximum ratio of 30 FTE students per FTE academic staff member • (3) humanities & social sciences programmes: a maximum ratio of 24 FTE students per FTE academic staff member

19. Graph 12

20. ACADEMIC STAFF (5) A well-qualified academic staff is essential for the delivery of a university’s teaching and research mandates. Academics with doctoral degrees are the major producers of research outputs and the main supervisors of doctoral students. Furthermore quality teaching at university level requires permanent academic staff to hold at least a masters degree. HERANA’s targets for a permanent academic staff profile are: (1) at least 50% with doctoral degrees (2) at least 90% with either a doctoral or a masters degree as their highest formal qualification (3) at most 10% with neither a masters nor a doctoral degree

21. Graph 13

22. RESEARCH OUTPUTS (1) High level knowledge outputs are critical if a country is to participate in the global knowledge economy. CHET has followed international bodies such as the OECD in taking research publications and doctoral graduates to be the key outputs in this category. Research publications consist mainly of articles which appear in journals which have editorial boards of experts in a field and which employ “blind” review procedures. Graphs 14 and 15 contain productivity indicators. They set out each university’s numbers of doctoral graduates and research publications. No productivity targets have been set by HERANA, but the graphs do show that output totals at three of the four universities have been low. Ghana produced a total of 17 doctoral graduates in 2009/10, compared to Cape Town’s total of 178 in that year. Ghana produced 101 research publications in 2009/10, and Cape Town a total of 1085.

23. Graph 14

24. Graph 15

25. RESEARCH OUTPUTS (2) • Graph 16 contains research output efficiency indicators, which measure the performance of the academic staff of each university. • HERANA’s targets for the output performance of permanent academics are: • (1) 0.15 for doctoral graduates • (2) 0.50 for research publications • A ratio of 0.15 doctoral graduates per permanent academic implies that each academic should produce on average 1 doctoral graduate every 7 years. • A ratio of 0.50 for research publications implies that permanent academic staff should publish one research paper every two years.

26. Graph 16

27. FUNDING (1) • Graph 17 shows what the main sources have been of the income of the four universities over the seven year period 2000/1 to 2006/7. The categories used are these: • government funds which include all subsidy amounts plus earmarked funds for special purposes; • student fees which include tuition and all class fees, as well as accommodation or residence fees; • private income which includes donations, non-government grants, investment income, and income from non-government research contracts.

28. Graph 17

29. FUNDING (2) • Graph 18 gives a summary of the total income of the four university in 2007, in terms of US dollars. Two different figures are used: • Market rate dollars which convert total income in local currency into US$, using average exchange rates quoted by the central banking authorities of each country. • Purchasing power parity dollars which rely on indicators in the World Bank’s 2008 World Development Indicators. These indicators give for each country a ratio between the PPP conversion factor and the market exchange rate. • Graph 19 uses the totals in Graph 18 and the FTE enrolled student totals in Graph 2 to show what each university’s income per FTE student was in 2007.

30. Graph 18

31. Graph 19

32. FUNDING (3) The delivery of high level research products depends on a university having a well-qualified and well-funded academic staff. One input measure of the ability of a university to deliver research outputs is the amount of research funding it has available per permanent academic staff member. Graph 20 compares the funds available to the four universities in 2007 in terms of purchasing power parity dollars per academic. The research funding data of three of the universities was obtained at the time at which their student and staff data were collected. Ghana did not provide specific information on research funding. In the graph which follows, it is assumed that their research income equals 3% of their total income. This proportion has still be confirmed by the university. HERANA’s target (which requires further analyses when better quality information is available): PPP$20 000 per permanent academic

33. Graph 20

34. CONCLUSION • CHET stresses in Cross-National Performance Indicators: a Case Study of Eight African Universities that an essential ingredient of any performance measurement system is a conceptually consistent and common set of data from which quantitative indicators can be extracted. • During HERANA 2 major co-operative efforts will be made with the eight participating universities (a) to rectify data problems referred to in this report, and (b) to broaden the scope of the performance indicators to be used in academic core analyses. These will include: • preparing manuals on the definitions and applications of the data elements required for performance measurements and institutional planning; • working with together on the practical application of the data concepts in institutional contexts; • analysing data and preparing institutional case studies for planning purposes.