Testing Machine Learning Models to Identify Computer Science Students at High-risk of Probation
H Errahmouni Barkam, M Wang… - Proceedings of the 53rd …, 2022 - dl.acm.org
Proceedings of the 53rd ACM Technical Symposium on Computer Science …, 2022•dl.acm.org
Pursuing higher education is a competitive process. Many students dropping out risk having
less career opportunities. We implemented machine learning (ML) models to identify
students at risk of probation and discover new factors correlated with probation cases. This
would allow to proactively provide students at risk with support to maximize academic
success, and also propose curricula changes.
less career opportunities. We implemented machine learning (ML) models to identify
students at risk of probation and discover new factors correlated with probation cases. This
would allow to proactively provide students at risk with support to maximize academic
success, and also propose curricula changes.
Pursuing higher education is a competitive process. Many students dropping out risk having less career opportunities. We implemented machine learning (ML) models to identify students at risk of probation and discover new factors correlated with probation cases. This would allow to proactively provide students at risk with support to maximize academic success, and also propose curricula changes.
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