Building a Decision Tree Model for Academic Advising Affairs Based on the Algorithm C4. 5
The ability to recognize students weakness and solving any problem may confront them in timely fashion is always a target of all educational institutions. Thus, colleges and universities implement so-called academic advising affairs. On the academic advisor relies the responsibility of solving any problem may confront students learning progress.
This paper shows how advisor can benefit from data mining techniques, namely decision trees techniques. The C4.5 algorithm is used as a method for building such trees. The output is evaluated based on the accuracy measure, Kappa measure, and ROC area. The difference between the registered and gained credit hours is considered as the main attribute on which advisor can rely.
Keywords: Decision tree, data mining, C4.5 algorithm, academic advisory.
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ABOUT THE AUTHOR
M. Al-Sarem
Dr. Al-Sarem is an assistant professor of information science at the Taibah University, Al Madinah Al Monawarah, KSA. He received the PhD in Informatics from Hassan II University, Mohammadia, Morocco in 2014. His research interests center on E-learning, educational data mining, Arabic text mining, and intelligent and adaptive systems. He published several research papers and participated in several local/international conferences.
M. Al-Sarem
Dr. Al-Sarem is an assistant professor of information science at the Taibah University, Al Madinah Al Monawarah, KSA. He received the PhD in Informatics from Hassan II University, Mohammadia, Morocco in 2014. His research interests center on E-learning, educational data mining, Arabic text mining, and intelligent and adaptive systems. He published several research papers and participated in several local/international conferences.
