Reasons non-traditional students drop out: Identifying clusters through data mining

Non-traditional students are at increased risk of dropping out, despite good academic performance. This paper therefore aims to contribute to a better understanding of the reasons why these students drop out. In general, dropping out is a complex process that is difficult to grasp. In order to better understand this issue, a cluster analysis was conducted to identify patterns in the reasons for dropping out. The analysis yielded six groups whose members have similar reasons for dropping out. For example, family, performance and finances played a role in one cluster each. In other clusters, however, no clear reason can be identified.