文章基本信息

标题：Predicting Student Performance Using Artificial Neural Network: in the Faculty of Engineering and Information Technology
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作者：Samy Abu Naser ; Ihab Zaqout ; Mahmoud Abu Ghosh 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：2
页码：221-228
DOI：10.14257/ijhit.2015.8.2.20
出版社：SERSC
摘要：In this paper an Artificial Neural Network (ANN) model, for predicting the performance of a sophomore student enrolled in engineering majors in the Faculty of Engineering and Information Technology in Al-Azhar University of Gaza was developed and tested. A number of factors that may possibly influence the performance of a student were outlined. Such factors as high school score, score of subject such as Math I, Math II, Electrical Circuit I, and Electronics I taken during the student freshman year, number of credits passed, student cumulative grade point average of freshman year, types of high school attended and gender, among others, were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was developed and trained using data spanning five generations of graduates from the Engineering Department of the Al-Azhar University, Gaza. Test data evaluation shows that the ANN model is able to correctly predict the performance of more than 80% of prospective students.
关键词：; Artificial Neural Networks; Student performance; ANN; Education; Predictive ; Model