Data Mining Application in Higher Learning Institutions

Naeimeh Delavari (1) , Somnuk Phon-Amnuaisuk (1) , Mohammad Reza Beikzadeh (2)

1 Faculty of Information Technology
2 Faculty of Engineering

One of the biggest challenges that higher learning institutions face today is to improve the quality of managerial decisions. The managerial decision making process becomes more complex as the complexity of educational entities increase. Educational institute seeks more efficient technology to better manage and support decision making procedures or assist them to set new strategies and plan for a better management of the current processes. One way to effectively address the challenges for improving the quality is to provide new knowledge related to the educational processes and entities to the managerial system. This knowledge can be extracted from historical and operational data that reside in the educational organization's databases using the techniques of data mining technology. Data mining techniques are analytical tools that can be used to extract meaningful knowledge from large data sets. This paper presents the capabilities of data mining in the context of higher educational system by i) proposing an analytical guideline for higher education institutions to enhance their current decision processes, and ii) applying data mining techniques to discover new explicit knowledge which could be useful for the decision making processes.

Mots clés: neural networks; clustering; classification; association rules; explicit knowledge; prediction; decision tree; radial basis function

Domaines: Environnements Informatiques pour l'Apprentissage Humain; Education

Naeimeh Delavari, Somnuk Phon-Amnuaisuk, Mohammad Reza Beikzadeh. Data Mining Application in Higher Learning Institutions. Informatics in Education - International Journal, 2008, 7, No. 1, pp.31-54. ⟨hal-00588765⟩