Data mining is a process of identifying and extracting hidden patterns, knowledge and information from databases and data warehouses. Today, one of the biggest challenges that educational institutes face is to use educational data to improve the quality of managerial decisions. Due to the huge educational databases, data mining enables organizations to use their current reporting capabilities to uncover and understand hidden patterns in vast datasets. Furthermore, data mining techniques can be used to extract meaningful knowledge and useful information from the huge educational databases. Data mining is a powerful analytical tool that enables educational institutions to better allocate resources and staff, and improve the effectiveness of alumni development.
Topics of this seminar are:
- Data mining in higher education
- Importance of data mining in higher education
- Data mining and its application in higher education
- Educational data mining
- Data mining in course management
- Predicting student performance by data mining techniques
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- Kumar, V., & Chadha, A. (2011). An Empirical Study of the Applications of Data Mining Techniques in Higher Education. Internat. Journal of Advanced Computer Science and Applications, 2(3), 80-84.
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- Minaei-Bidgoli, B., Kashy, D. A., Kortmeyer, G., & Punch, W. F. (2003, November). Predicting student performance: an application of data mining methods with an educational web-based system. In Frontiers in Education, 2003. FIE 2003 33rd Annual (Vol. 1, pp. T2A-13). IEEE.
- Parack, S., Zahid, Z., & Merchant, F. (2012, January). Application of data mining in educational databases for predicting academic trends and patterns. In Technology Enhanced Education (ICTEE), 2012 IEEE International Conference on (pp. 1-4). IEEE.
- Romero, C., & Ventura, S. (2007). Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications, 33(1), 135-146.
- Romero, C., & Ventura, S. (2010). Educational data mining: A review of the state of the art. Systems, Man, and Cybernetics, Part C Applications and Reviews, IEEE Transactions on, 40(6), 601-618.
- Romero, C., Ventura, S. & García, E. (2008). Data mining in course management systems: Moodle case study and tutorial. Computers & Education, 51(19, 368-384
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