Knowledge Discovery in Higher Educational Big Dataset

Authors:
Robab Saadatdoost;Alex Tze Hiang Sim;Jee Mei Hee;Hosein Jafarkarimi
Affiliations:
Department of Information Systems, Faculty of Computing, Universiti Teknologi Malaysia,Johor Bahru, Johor, Malaysia & Department of Computer and Information Technology, Parand Branch, Islamic Azad ...;Department of Information Systems, Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia;Department of Educational Foundation, Faculty of Education, Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia;Department of Computer, Damavand Branch, Islamic Azad University, Damavand, Iran
Venue:
International Journal of Information Retrieval Research
Year:
2013

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Abstract

This paper seeks to address one of the current issues of large organizations; it is rapid growth of data without any quick way to extract worthwhile and hidden knowledge from considerable huge volume of data. It seems that management of higher education institutes interest to the best method for solving this problem and making a good decisions and strategies. Contrast to the authors' initial sample consisted of five medical universities of Tehran, in this paper a large sample was chosen because of the expected valuable discovered knowledge. This data was collected from 65 universities of Iran based 18 years. The data is in Persian. The present paper confirms the authors' previous findings and contributes additional discovered knowledge related to the major group of program with different geographical, the main factor of sharp increase in the number of students and preferred learning style, study mode and programs and considerable growth of female students after 1996. The findings of this study have a number of important implications for future planning of higher education to improve ranking of universities. Another important practical implication is that other researchers can use them in their studies on higher education.