Abstract
While student attrition constitutes a major institutional concern at the undergraduate level, this topic is overlooked at the master’s level. Dropout rates have been documented, but no solid predictive models are to be found. Likewise, little is known about students’ decision to terminate their studies. With growing enrolment numbers in postgraduate programmes, this blind spot should be addressed. The multi-method research presented here, combining student administrative data from The Hebrew University of Jerusalem with a survey for students who dropped out of the institution, brings the research on this topic a step forward. The study found that dropout rates of master’s students are 12%. To identify possible predictors of these dropouts, we employed a four-step hierarchical logistic regression model. Academic performance variables predict dropping out far better than background variables, though much of the variation remains unaccounted for. An exploratory factor analysis of dropout survey items identified five factors linked to departure: work obligations, institutional difficulties, family and personal obligations, degree’s economic feasibility, and harassment. These subjective reasons for dropping out should be major targets for dropout prevention efforts.
| Original language | English |
|---|---|
| Pages (from-to) | 1070-1084 |
| Number of pages | 15 |
| Journal | Higher Education Research and Development |
| Volume | 40 |
| Issue number | 5 |
| DOIs | |
| State | Published - 2021 |
Bibliographical note
Publisher Copyright:© 2020 HERDSA.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 4 Quality Education
Keywords
- Attrition
- dropout
- institutional policies and practices
- master’s students
- postgraduate
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