2023
DOI: 10.5815/ijmecs.2023.01.04
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Analysis of Student’s Academic Performance based on their Time Spent on Extra-Curricular Activities using Machine Learning Techniques

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Cited by 11 publications
(7 citation statements)
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“…This is confi rmed by the results of the study. Student success in studies depending on the time spent on extracurricular activities [10].…”
Section: Discussion Of Research Resultsmentioning
confidence: 99%
“…This is confi rmed by the results of the study. Student success in studies depending on the time spent on extracurricular activities [10].…”
Section: Discussion Of Research Resultsmentioning
confidence: 99%
“…In [9], a student classification system was developed using naive Bayes and decision tree algorithms that used features like the occupation of parents to enhance the correctness of the grade-prediction framework. The Decision Tree classifier performed better than the naive Bayes Classification in terms of accuracy [10].…”
Section: Literature Reviewmentioning
confidence: 93%
“…In the part of lesson preparation and course design practice, ChatGLM (GPT artificial intelligence robot) and Wenxin large model are introduced to infer and improve ideas, and the function of digital teaching tools is deeply integrated with teaching activities [13,14]. In the design process, CAD, 3Ds max, SketchUp, Enscape, sheencity Mars, and other software are used for modeling and rendering, so as to make the design scheme more realistic and realize technology-enhanced learning [15,16]. In the presentation of teaching cases and design schemes, AR+VR is adopted to transform two-dimensional static pictures into three-dimensional dynamic scenes, and reshape the relationship between the elements of "human-space-art".…”
Section: Concrete Implementationmentioning
confidence: 99%