Early prediction of undergraduate Student's academic performance in completely online learning: A five-year study

作者：

Highlights：

• Prediction of academic performance of 802 undergraduate students in a completely online learning.

• Exploratory factor analysis, multiple regression model and clustering are utilized to predict the academic performance.

• The prediction model is mainly based on variables of interaction data in Moodle.

• Age has been identified as a factor that is inversely proportional to the academic performance.

摘要

•Prediction of academic performance of 802 undergraduate students in a completely online learning.•Exploratory factor analysis, multiple regression model and clustering are utilized to predict the academic performance.•The prediction model is mainly based on variables of interaction data in Moodle.•Age has been identified as a factor that is inversely proportional to the academic performance.

论文关键词：Analytics,Learning management systems,Online learning,Modeling,Prediction

论文评审过程：Received 15 January 2020, Revised 30 June 2020, Accepted 2 October 2020, Available online 12 October 2020, Version of Record 28 October 2020.

论文官网地址：https://doi.org/10.1016/j.chb.2020.106595