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Author/Affiliation: Sameh HallaqPredicting School Children Academic Performance Using Machine Learning Techniques
Advances in Science, Technology and Engineering Systems Journal,
Volume 6,
Issue 5,
Page # 08–15,
2021;
DOI: 10.25046/aj060502
Abstract:
The study aims to assess the machine learning techniques in predicting students’ associated factors that affect their academic performance. The study sample consisted of 5084 middle and high school students between the ages of 10 and 17, attending public and UNRWA schools in the West Bank. The ‘Health Behaviors School Children’ questionnaire for the 2013-2014…
Read More(This article belongs to the SP11 (Special Issue on Innovation in Computing, Engineering Science & Technology 2021) & Section Interdisciplinary Applications of Computer Science (CSI))
