A Review of Educational Data Mining Tools & Techniques

  • Haitham Alagib Alsuddig Hamza College of Computer Science and Information Technology, Sudan University of Science and Technology, Sudan
  • Piet Kommers Faculty of Behavioural Sciences, University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands


The purpose of this paper is to present a review study on the use of the tools and techniques of Education Data Mining (EDM); through the use of data mining techniques such as classification, aggregation, the correlation rules and the disclosure of cases and apply on the student grades to show the benefits of applying the techniques of data mining in the academic field to obtain a clear understanding of the factors success and failure of students. The paper presented a definition of the concept of (EDM) and then presents of several previous studies that used many different techniques of data mining. The paper concluded to review the most important applications of (EDM) and classification according to the objectives and methods used and General framework procedural can be use in (EDM).
Keywords: Educational data mining, Decision trees, performance, student, Predictive.


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Asif, R. A. (2017). Analysing undergraduate students' performance using educational data mining. Computers \& Education Asif, R. a. (2017). Analysing undergraduate students' performance using educational data mining. Computers \& Education.
Gulati, P. A. (2012). Educational data mining for improving educational quality. tell us, 3.
Guleria, P. A. (2014). Mining Educational Data Using K-Means Clustering. guleria2014mining.
Al-shargabi, (2010). Discovering vital patterns from UST students data by applying data mining techniques,
Kushwah, S. P. (n.d.). Analysis and comparison of efficient techniques of clustering algorithms in data mining. International Journal of Innovative Technology and Exploring Engineering (IJITEE): 2278--3075.
Lekeas, G. K. (200). Data mining the web: the case of City University’s Log Files. lekeas2000data.
Mining, T. E. (2012). Enhancing teaching and learning through educational data mining and learning analytics: An issue brief. Proceedings of Conference on Advanced Technology for Education.
Mythili, D. A. (2014). An Analysis of students’ performance using classification algorithms. IOSR Journal of Computer Engineering (IOSR-JCE), 16.
Ramaswami, M. (2014). Validating Predictive Performance of Classifier Models for Multiclass Problem in Educational Data Mining. International Journal of Computer Science Issues (IJCSI), 11: 86.
El-Halees, A. (2009). Mining students data to analyse e-Learning behaviour: A Case Study. el2009mining.
Kapur, B. A. (2017). Comparative Study on Marks Prediction using Data Mining and Classification Algorithms. International Journal of Advanced Research in Computer Science, 8.
Pal, S. A. (2017). Performance Analysis of Students Consuming Alcohol Using Data Mining Techniques. International Journal of Advance Research in Science \& Engineering, 06: 238--250.
Patil, P. S. (2017). Predicting Instructor Performance Using Na{\"\i}ve Bayes Classification Algorithm in Data Mining Technique: A Survey. International Journal of Advanced Electronics and Communication Systems, 6.
Yadav, S. K. (2012). Data mining: A prediction for performance improvement of engineering students using classification. arXiv preprint arXiv:1203.3832.
Baradwaj, B. K. (2012). Mining educational data to analyse students' performance. arXiv preprint arXiv:1201.3417, 2.
Borkar, S. A. (2013). Predicting students’ academic performance using education data mining. International Journal of Computer Science and Mobile Computing (IJCSMC, 2: 273--279.
Kabakchieva, D. (2013). Predicting student performance by using data mining methods for classification. kabakchieva2013predicting, 13: 61--72.
Kularbphettong, K. A. (2012). Mining educational data to analyse the student motivation behavior. World Acad. Sci. Eng. Techno, 6: 1036--1040.
Romero, C. A. (2008). Data mining in course management systems: Moodle case study and tutorial. Computers \& Education, 51: 368--384.
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How to Cite
Hamza, H.A.A. and Kommers, P. 2018. A Review of Educational Data Mining Tools & Techniques. International Journal of Educational Technology and Learning. 3, 1 (May 2018), 17-23. DOI:https://doi.org/https://doi.org/10.20448/2003.31.17.23.