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2021 | OriginalPaper | Chapter

Impact of Prerequisite Subjects on Academic Performance Using Association Rule Mining

Authors : Chandra Das, Shilpi Bose, Arnab Chanda, Sandeep Singh, Sumanta Das, Kuntal Ghosh

Published in: Progress in Advanced Computing and Intelligent Engineering

Publisher: Springer Singapore

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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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Metadata
Title
Impact of Prerequisite Subjects on Academic Performance Using Association Rule Mining
Authors
Chandra Das
Shilpi Bose
Arnab Chanda
Sandeep Singh
Sumanta Das
Kuntal Ghosh
Copyright Year
2021
Publisher
Springer Singapore
Book
Progress in Advanced Computing and Intelligent Engineering

Print ISBN: 978-981-15-6352-2

Electronic ISBN: 978-981-15-6353-9

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-6353-9_21