Data Mining: Analysis of the Influence of College Students' Daily Behaviors on Their Academic Performance

被引：0
|
作者：
Zhang, Yujia [1 ]
机构：
[1] Chengdu Polytechnic, Sichuan, Chengdu,610041, China
来源：
Engineering Intelligent Systems | 2024年 / 32卷 / 02期
关键词：
Students' academic performance reflects the quality of a university. It is of vital practical significance to find the daily behaviors that affect students' academic performance and improve them in a targeted manner. This paper mined and analyzed the academic performance and daily behaviors of college students by using the decision tree algorithm in data mining technology to find the correlation between the students' daily behaviors and their academic performance. By means of a decision tree model; it was found that students' class attendance had the greatest influence on their academic performance; followed by the time spent daily on the Internet. Moreover; the decision tree model achieved a correct rate of 82.07%. The study shows that the decision tree algorithm can identify the daily behaviors that affect college students' performance; help them study better; and have a positive impact on improving college students' academic performance. ©2024CRL Publishing Ltd;
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页码：121 / 126
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