Oladipupo, O. O. and Oyelade, O. J. (2010) Knowledge Discovery from Students’ Result Repository: Association Rule Mining Approach. International Journal of Computer Science and Security, 4 (2). pp. 199-207.
Over the years, several statistical tools have been used to analyze students’ performance from different points of view. This paper presents data mining in education environment that identifies students’ failure patterns using association rule mining technique. The identified patterns are analysed to offer a helpful and constructive recommendations to the academic planners in higher institutions of learning to enhance their decision making process. This will also aid in the curriculum structure and modification in order to improve students’ academic performance and trim down failure rate. The software for mining student failed courses was developed and the analytical process was described.
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science|
|Depositing User:||Mr Adewole Adewumi|
|Date Deposited:||02 Nov 2012 11:13|
|Last Modified:||02 Nov 2012 11:13|
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