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An application of classification models to predict learner progression in tertiary education

https://doi.org/10.1109/iadcc.2014.6779384

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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inferred← citeshttps://doi.org/10.5220/0011847800003470openalex-snapshot

Effects of Early Warning Emails on Student Performance

inferred← citeshttps://doi.org/10.5281/zenodo.18620097openalex-snapshot

Decision Support System Model for Student Performance Detection using Machine Learning

inferred← citeshttps://doi.org/10.5334/dsj-2019-014openalex-snapshot

A Survey of Machine Learning Approaches and Techniques for Student Dropout Prediction

inferred← citeshttps://doi.org/10.53730/ijhs.v6ns5.8883openalex-snapshot

Students career prediction

inferred← citeshttps://doi.org/10.54097/jeer.v5i3.13646openalex-snapshot

Study on Predicting University Student Performance Based on Course Correlation

inferred← citeshttps://doi.org/10.5815/ijmecs.2021.01.01openalex-snapshot

Comparative Study of Supervised Algorithms for Prediction of Students’ Performance

inferred← citeshttps://doi.org/10.58694/20.500.12479/898openalex-snapshot

Data driven approach for predicting student dropout in secondary schools

inferred← citeshttps://doi.org/10.70675/3c0b884cz2d59z446fz9eeezc2da4763aa9copenalex-snapshot

Analyse prédictive des données d’apprentissage, en situation d’enseignement à distance

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