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Using Data Mining Techniques with Open Source Software to Evaluate the Various Factors Affecting Academic Performance: A Case Study of Students in the Faculty of Information Technology

Using Data Mining Techniques with Open Source Software to Evaluate the Various Factors Affecting Academic Performance: A Case Study of Students in the Faculty of Information Technology

Feras Hanandeh, Majdi Y. Al-Shannag, Maha Mahdi Alkhaffaf
Copyright: © 2016 |Volume: 7 |Issue: 2 |Pages: 21
ISSN: 1942-3926|EISSN: 1942-3934|EISBN13: 9781466690653|DOI: 10.4018/IJOSSP.2016040104
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MLA

Hanandeh, Feras, et al. "Using Data Mining Techniques with Open Source Software to Evaluate the Various Factors Affecting Academic Performance: A Case Study of Students in the Faculty of Information Technology." IJOSSP vol.7, no.2 2016: pp.72-92. http://doi.org/10.4018/IJOSSP.2016040104

APA

Hanandeh, F., Al-Shannag, M. Y., & Alkhaffaf, M. M. (2016). Using Data Mining Techniques with Open Source Software to Evaluate the Various Factors Affecting Academic Performance: A Case Study of Students in the Faculty of Information Technology. International Journal of Open Source Software and Processes (IJOSSP), 7(2), 72-92. http://doi.org/10.4018/IJOSSP.2016040104

Chicago

Hanandeh, Feras, Majdi Y. Al-Shannag, and Maha Mahdi Alkhaffaf. "Using Data Mining Techniques with Open Source Software to Evaluate the Various Factors Affecting Academic Performance: A Case Study of Students in the Faculty of Information Technology," International Journal of Open Source Software and Processes (IJOSSP) 7, no.2: 72-92. http://doi.org/10.4018/IJOSSP.2016040104

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Abstract

This research paper studies the different factors that could affect the Faculty of Information Technology students' accumulative averages at Jordanian Universities, by verifying the students' information, background and academic records. It also has the objective to reveal how this information will affect the students to obtain high grades in their courses. The information of the students is extracted from the students' records and its attributes are formulated as a huge database. Then, a free open source software (WEKA) which supports data mining tools and techniques are used to decide which attribute(s) will affect the students' accumulative averages. It was found that the most important factor affects the students' accumulative averages, is the student acceptance type. A decision tree model and rules are also built to determine how the students can get high grades in their courses. The overall accuracy of the model was 46.8% which is an accepted rate.

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