Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2346
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dc.contributor.authorKasthuriarachchi, S-
dc.contributor.authorBhatt, C. M-
dc.contributor.authorLiyanage, S. R-
dc.date.accessioned2022-05-18T03:19:59Z-
dc.date.available2022-05-18T03:19:59Z-
dc.date.issued2018-02-11-
dc.identifier.citationSanvitha Kasthuriarachchi, K.T., Liyanage, S.R., Bhatt, C.M. (2018). A Data Mining Approach to Identify the Factors Affecting the Academic Success of Tertiary Students in Sri Lanka. In: Caballé, S., Conesa, J. (eds) Software Data Engineering for Network eLearning Environments. Lecture Notes on Data Engineering and Communications Technologies, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-319-68318-8_9en_US
dc.identifier.isbn978-3-319-68318-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2346-
dc.description.abstractEducational Data Mining has become a very popular and highly important area in the domain of Data mining . Application of data mining to education arena arises as a paradigm oriented to design models, methods, tasks and algorithms for discovering data from educational domain. It attempts to uncover data patterns, structure association rules, establish information of unseen relationships with educational data and many more operations that cannot be performed using traditional computer based information systems. It grows and adopts statistical methods, data mining methods and machine-learning to study educational data produced mostly by students, educators, educational management policy makers and instructors. The main objective of applying data mining in education is primarily to advance learning by enabling data oriented decision making to improve existing educational practices and learning materials. This study focuses on finding the key factors affecting the performance of the students enrolled for technology related degree programs in Sri Lanka. The findings of this study will positively affect the future decisions about the progress of the students’ performance, quality of the education process and the future of the education provider.en_US
dc.language.isoenen_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofseriesSoftware Data Engineering for Network eLearning Environments;Vol 11 Pages 179-197-
dc.subjectData miningen_US
dc.subjectEducational data miningen_US
dc.subjectClassificationen_US
dc.subjectKnowledge discoveryen_US
dc.subjectFeature extractionen_US
dc.titleA Data Mining Approach to Identify the Factors Affecting the Academic Success of Tertiary Students in Sri Lankaen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/978-3-319-68318-8_9en_US
Appears in Collections:Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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