1. Project overview So where is the problem? Cohort analysis of student drop-out – the class of 2010 Conceptual framework for the study Shaping (lens for) a fine grained analysis within a bounded system Literature review: Poor school background Poor preparation for Higher Ed Etc. Literature review: Poor school background Poor preparation for Higher Ed Etc. Stats and prelim data analysis (Dalia) What about the numbers – drop out across the years of study (Busi)/Michael Students’ personal reasons for drop-out Academic development co- ordinators’ perspective on academic support Students’ concerns about institutional issues that led to their drop-out AD co-ordinators’ concerns about institutional issues that leads to student drop- out Students’ concerns about institutional issues that led to their drop-out AD co-ordinators’ concerns about institutional issues that leads to student drop- out

2. Drop out analysis from HEIs in South Africa (from literature) Status: – progression and retention rates at South African Universities currently rank amongst the lowest in the world – approx 15% of students of a cohort graduate in the minimum study period. – 40% of students drop out of university in their first year of study – The drop-outs are largely amongst Africa students

3. Reasons (most common) include: In SA - – finance, – poor school preparation, and – inadequate teaching and support at higher education institutions. In other parts of the world: – reasons for high dropout from higher education seems to be located within a students’ experience discourse suggesting that negative students experiences of higher education is the root cause of student dropout – lack of quality within higher education – academic staffs’ effectiveness

4. analysis of lit review: If you look through the students lens, student dropout is viewed largely as a result of negative students’ experiences of campus life. Looking through the lens of the institutions, student dropout is viewed largely as from external background factors.

5. Institutional stats on student throughput in undergraduate prog FacNo. RegNo. grad in min. time No. Excluded No. dropped out Currently registered Education42826278755 Engineering6078891108252 Health Sc407213195393 Humanities202263071433603 Law45416919108107 Managemen t Studies 163356528281646 Medicine2061710431 Science & Agriculture 121623592203473 Total69732333 (33%)327 (5%)1277 (18%)2260 (32%)

6. Institutional stats cont. student dropout patterns Fac1 st year of reg 2 nd year of reg 3 rd year of reg 4 th year of reg 5 th year of reg Education3812730 Engineering6820119 Health Sc2114 4 Humanities227951101 Law43361613 Managemen t Studies 13472741 Medicine121 Sc and Agric13437311 TOTAL666 (52%)288 (23%)263 (21%)59 (5%)

7. Conceptual framework guiding the study framework

8. Summary Symbolic vs actual achievements (statistical modeling could assist in evaluating this tension) Individual vs group achievements (need to shift our discourses from group discourses to particular discourses – as is evident in the various qualitative analysis) Access does not stand on its own. It must be accompanied by support and monitoring (the questions is: what support and by whom) EFA issues of target setting and target attainment are playing out in higher educ (how can we learn from other agendas within a transformation gaze?)