Predicting Academic Success of College Students Using Machine Learning Techniques

College context and academic performance are important determinants of academic success; using students’ prior experience with machine learning techniques to predict academic success before the end of the first year reinforces college self-efficacy. Dropout prediction is related to student retention...

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Bibliographic Details

Published in:	Data
Main Authors:	Jorge Humberto Guanin-Fajardo, Javier Guaña-Moya, Jorge Casillas
Format:	Article
Language:	English
Published:	MDPI AG 2024-04-01
Subjects:	educational data mining machine learning educational analysis higher education academic success
Online Access:	https://www.mdpi.com/2306-5729/9/4/60