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DOI: 10.14569/IJACSA.2020.0110425
PDF

Predict Students’ Academic Performance based on their Assessment Grades and Online Activity Data

Author 1: Amal Alhassan
Author 2: Bassam Zafar
Author 3: Ahmed Mueen

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 4, 2020.

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Abstract: The ability to predict students’ academic performance is critical for any educational institution that aims to improve their students' learning process and achievement. Although students’ performance prediction problem is studied widely, it still represents a challenge and complex issue for educational institutions due to the different features that affect students learning process and achievement in courses. Moreover, the utilization of web-based learning systems in education provides opportunities to study how students learning and what learning behavior leading them to success. The main objective of this research was to investigate the impact of assessment grades and online activity data in the Learning Management System (LMS) on students’ academic performance. Based on one of the commonly used data mining techniques for prediction, called classification. Five classification algorithms were applied that decision tree, random forest, sequential minimal optimization, multilayer perceptron, and logistic regression. Experimental results revealed that assessment grades are the most important features affecting students' academic performance. Moreover, prediction models that included assessment grades alone or in combination with activity data perform better than models based on activity data alone. Also, random forest algorithm performs well for predicting student a cademic performance, followed by decision tree.

Keywords: Predict student performance; learning management system; data mining; educational data mining; classification model

Amal Alhassan, Bassam Zafar and Ahmed Mueen, “Predict Students’ Academic Performance based on their Assessment Grades and Online Activity Data” International Journal of Advanced Computer Science and Applications(IJACSA), 11(4), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110425

@article{Alhassan2020,
title = {Predict Students’ Academic Performance based on their Assessment Grades and Online Activity Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110425},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110425},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {4},
author = {Amal Alhassan and Bassam Zafar and Ahmed Mueen}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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