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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Bibliographic Details
Main Authors:	Thao-Trang Huynh-Cam, Long-Sheng Chen, Huynh Le
Format:	article
Language:	EN
Published:	MDPI AG 2021
Subjects:	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
Online Access:	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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