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Data Mining Application in Higher Learning Institutions
Volume 7, Issue 1 (2008), pp. 31–54
Naeimeh DELAVARI   Somnuk PHON-AMNUAISUK   Mohammad Reza BEIKZADEH  

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https://doi.org/10.15388/infedu.2008.03
Pub. online: 15 April 2008      Type: Article     

Published
15 April 2008

Abstract

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.

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Keywords
data mining explicit knowledge classification prediction association rule analysis clustering decision tree neural network classification radial basis function neural network prediction

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INFORMATICS IN EDUCATION

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