Knowledge Discovery from Students’ Result Repository:Association Rule Mining Approach
Olufunke Oladipupo, Jelili O. Oyelade · Covenant University Repository (Covenant University) · 2010
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.