Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2370
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dc.contributor.authorKasthuriarachchi, K. T. S-
dc.contributor.authorLiyanage, S. R-
dc.date.accessioned2022-05-18T05:26:21Z-
dc.date.available2022-05-18T05:26:21Z-
dc.date.issued2017-10-31-
dc.identifier.issn2602-8549-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2370-
dc.description.abstractKnowledge discovery in educational data would be so basic to determine better expectations on the undergraduates. Distinguishing proof of the components influence to the execution of undergraduates in light of various attributes will be supportive for instructors, educators and managers viewpoints. This paper endeavors to utilize different data mining ways to deal with find forecast manages in undergraduates’ data to distinguish the components influence to the scholarly accomplishment in their tertiary education. The approach of this exploration observed the aftereffects of three mining algorithms with about 3800 undergraduates’ records and the calculation which demonstrated the most elevated exactness has chosen as the best model and the connections acquired through that were gotten to foresee various elements against the objective of whether they will get the degree or not following three years of the university life. Naïve Bayes, Decision Tree and Support Vector Machine were used in predicting the most affecting factors to the performance of students. According to the prediction accuracy levels, the results of Decision Tree were selected since it outperforms the rest for the selected data set. Finally, the results were evaluated using a correlation analysis to select the most prominent factor. According to the test, the age, past failure modules, performance of past semesters were selected as the most influencing factors to the success or failure of the students in tertiary education system in Sri Lanka.en_US
dc.language.isoenen_US
dc.publisherUniversity of Moratuwa, Sri Lankaen_US
dc.relation.ispartofseriesSLAAI-International Conference on Artificial Intelligence;Pages 56-
dc.subjectEducational Data Miningen_US
dc.subjectAlgorithmsen_US
dc.subjectKnowledge Discoveryen_US
dc.subjectFeature Extractionen_US
dc.subjectValidationen_US
dc.titleKnowledge Discovery with Data Mining for Predicting Students’ Success Factors in Tertiary Education System in Sri Lankaen_US
dc.typeArticleen_US
Appears in Collections:Research Papers - Open Access Research
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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