Using Decision Trees and Random Forest Algorithms to Predict and Determine Factors Contributing to First-Year University Students’ Learning Performance

First-year students’ learning performance has received much attention in educational practice and theory. Previous works used some variables, which should be obtained during the course or in the progress of the semester through questionnaire surveys and interviews, to build prediction models. These...

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Autores principales:	Thao-Trang Huynh-Cam, Long-Sheng Chen, Huynh Le
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	students’ learning performance prediction model random forest (RF) decision tree (DT) feature selection technological and vocational education Industrial engineering. Management engineering T55.4-60.8 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/b2e7c55f69b846f0ad6e1ec1a64bc336
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Using Decision Trees and Random Forest Algorithms to Predict and Determine Factors Contributing to First-Year University Students’ Learning Performance

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