Abstract
Early Warning Systems (EWS) in higher education accommodate student counsellors by identifying at-risk students and allow them to intervene in a timely manner to prevent student dropout. This study evaluates an EWS that shares student-specific risk information with student counsellors, which was implemented at a large Dutch university. A randomised field experiment was conducted to estimate the effect of EWS-assisted counselling on first-year student dropout and academic performance. The results show that the EWS accurately predicts at-risk students. Yet, EWS-assisted counselling did not reduce dropout, nor improved academic performance. Solving the underlying problem of poor academic performance might require additional actionable feedback and recommended counselling practices.
| Original language | English |
|---|---|
| Pages (from-to) | 131-152 |
| Number of pages | 22 |
| Journal | Higher Education Quarterly |
| Volume | 76 |
| Issue number | 1 |
| Early online date | 9 Feb 2021 |
| DOIs | |
| Publication status | Published - Jan 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 4 Quality Education
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