Higher education is linked to economic mobility, but demand to fund access to university exceeds supply in South Africa, and elsewhere in the world. Thus, universities are pressed to ensure that in a situation of limited funds, funding is allocated in a strategic and prudent manner. However, little work has been undertaken in this field, and, as such, this study represents an attempt to fill the gap. The purpose of this research was to explore the current student funding model, to gain an understanding the current funding challenges and attempt to find ways in which funding decisions can be improved. The study is limited to one institution of higher education in South Africa, and, as such the results may not be generalizable. A mixed methods approach was used. The qualitative portion focused on establishing what were (1) the current model, (2) the criteria used, (3) the challenges encountered, (4) funding s ability to aid epistemological success and (5) stakeholder management. Interviews were conducted with senior staff involved in a range of student support directorates including Finance, Client Services, Recruitment and Information Technology. The quantitative portion focused on exploring the links between (1) the current criteria and success, (2) student funding and success, and (3) residence placement and success. This sample included all (8099) undergraduates for the 2011 cohort year and tracked them over a period of three years. Results of the study show that student funding is complex and challenging. In terms of academic criteria, the Grade Point Average was found to be the best predictor of success. However, the presence and value of funding does not guarantee success or even improve student performance, whereas the placement of a student in residence generates a statistically significant improvement in performance. Thus, student funding cannot be simply directed at individuals, as a portion must be allocated to student support initiatives such as residence; tutoring; cultural integration; mentorship and early warning systems.
Mini-disseration (MBA)--University of Pretoria, 2016.