Feature Extraction for Next-Term Prediction of Poor Student Performance

Developing tools to support students and learning in a traditional or online setting is a significant task in today's educational environment. The initial steps toward enabling such technologies using machine learning techniques focused on predicting the student's performance in terms of t...

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Veröffentlicht in:	IEEE transactions on learning technologies 2019-04, Vol.12 (2), p.237-248
Hauptverfasser:	Polyzou, Agoritsa, Karypis, George
Format:	Artikel
Sprache:	eng
Schlagworte:	Academic Achievement Academic student success Accuracy At Risk Students Classification Colleges & universities Data mining Educational Environment Feature extraction feature importance Grades (Scholastic) Identification Learning Learning management systems Low Achievement Machine learning Performance prediction Prediction Predictive models Special issues and sections Students Task analysis Teaching Methods Undergraduate Students
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