Abstract
Association rule mining is a popular approach to find out the frequent itemset from a database and hence discover the association rules exist for those itemsets. It often turns out to be useful to explore the interestingness among the data. Student’s educational information is one such important area where mining algorithms can be applied to uncover useful hidden information for improving academics. In this regard, the association rule mining techniques have been used in the present work to study the importance of prerequisite subjects on academic results of dependent subjects. The dataset used in this study contains subject-wise semester marks collected throughout the eight semesters of 117 students of Computer Science and Engineering bachelor course of a university of West Bengal. The study reveals the significant impact of prerequisite subjects on the academic result of dependent subjects of students very clearly.
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Das, C., Bose, S., Chanda, A., Singh, S., Das, S., Ghosh, K. (2021). Impact of Prerequisite Subjects on Academic Performance Using Association Rule Mining. In: Panigrahi, C.R., Pati, B., Mohapatra, P., Buyya, R., Li, KC. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 1199. Springer, Singapore. https://doi.org/10.1007/978-981-15-6353-9_21
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DOI: https://doi.org/10.1007/978-981-15-6353-9_21
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