Knowledge Discovery from Educational Database Using Apriori Algorithm

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dc.contributor.authorAbdulsalam, S.O.
dc.contributor.authorHambali, M.A.
dc.contributor.authorSalau-Ibrahim, T.T.
dc.contributor.authorSaheed, Y.K.
dc.contributor.authorBabatunde, A.N.
dc.date.accessioned2025-10-29T11:02:49Z
dc.date.available2025-10-29T11:02:49Z
dc.date.issued2017
dc.description.abstractAbility to predict student’s performance has become very crucial in educational environments and plays important role in producing the best quality graduates. There are several statistical tools for analyzing students' performance for knowledge discovery from available data. This study presents data mining in educational sector that identifies students’ failure pattern using Apriori algorithm. The results of 20 students in 25 courses taken in their 100 and 200 level of an educational institute in North Central Nigeria were considered as a case study. The patterns discovered were used to provide recommendations to academic planners so as to improve their level of decision making, restructuring of curriculum, and modifying the prerequisites of various courses. This study revealed some interesting patterns in failed courses as some failed courses have a relationship with other failed courses. A data mining software for mining student failed courses was developed, used to mine students result, and the analysis were described. Keywords: Association Rule Mining, Apriori Algorithm, Academic performance, Educational data mining, Curriculum, Educational database, Students' result repository
dc.identifier.urihttps://kwasuspace.kwasu.edu.ng/handle/123456789/6203
dc.language.isoen
dc.publisherGeorgian Technical University an Niko Muskhelishvili Institute of Computational Mathematics, Georgia - Georgian Electronic Scientific Journals (GESJ): Computer Science and Telecommunications, 1(51): 41 – 51
dc.titleKnowledge Discovery from Educational Database Using Apriori Algorithm
dc.typeArticle
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