Article ID: | iaor20171081 |
Volume: | 68 |
Issue: | 4 |
Start Page Number: | 416 |
End Page Number: | 430 |
Publication Date: | Apr 2017 |
Journal: | J Oper Res Soc |
Authors: | De Witte Kristof, Sneyers Eline |
Keywords: | quality & reliability, statistics: inference, optimization |
This paper investigates in a non‐parametric framework whether academic programmes maximize their student graduation rates and programme quality ratings given the first‐year student dropout rates. In addition, it explores what institutional and programme characteristics explain this interaction. The results show a large variation in how academic programmes are able to deal with the selective nature of first‐year dropout. Nevertheless, we can accurately explain the variation among programmes by programme and institutional characteristics. It seems that universities can maximize the relation between first‐year dropout, graduation rates and quality ratings in several ways: (1) by improving student programme satisfaction, (2) by better preparing certain groups of students for higher education, (3) by supporting male students, (4) by supporting ethnic minority students, (5) by attracting older staff, and (6) by strengthening the selective nature of the first year (ie, increasing the academic dismissal policy threshold).