Investigating the Impact of COVID-19 Pandemic on Education by Learning Analytics

被引:0
作者
Abe, Keisuke [1 ]
Cheng, Kai [1 ]
机构
[1] Kyushu Sangyo Univ, Grad Sch Informat Sci, Fukuoka, Japan
来源
2024 IEEE CONFERENCE ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING, DASC 2024 | 2024年
关键词
learning analytics; machine learning; educational big data; data analysis; online classes; COVID-19; pandemic;
D O I
10.1109/DASC64200.2024.00022
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper we propose a predictive model for learning analysis using student teaching data and demonstrate the effectiveness of machine learning methods in predicting retention and dropout. We also examine the impact of online classes due to the COVID-19 pandemic on academic performance, and analyze the correlation between changes in academic performance and prediction of retention and dropout based on recall and precision.
引用
收藏
页码:105 / 109
页数:5
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