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DC Field | Value | Language |
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dc.contributor.author | Kasthuriarachchi, S | - |
dc.contributor.author | Bhatt, C. M | - |
dc.contributor.author | Liyanage, S. R | - |
dc.date.accessioned | 2022-05-18T03:19:59Z | - |
dc.date.available | 2022-05-18T03:19:59Z | - |
dc.date.issued | 2018-02-11 | - |
dc.identifier.citation | Sanvitha 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_9 | en_US |
dc.identifier.isbn | 978-3-319-68318-8 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/2346 | - |
dc.description.abstract | Educational 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.iso | en | en_US |
dc.publisher | Springer, Cham | en_US |
dc.relation.ispartofseries | Software Data Engineering for Network eLearning Environments;Vol 11 Pages 179-197 | - |
dc.subject | Data mining | en_US |
dc.subject | Educational data mining | en_US |
dc.subject | Classification | en_US |
dc.subject | Knowledge discovery | en_US |
dc.subject | Feature extraction | en_US |
dc.title | A Data Mining Approach to Identify the Factors Affecting the Academic Success of Tertiary Students in Sri Lanka | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1007/978-3-319-68318-8_9 | en_US |
Appears in Collections: | Research Papers - SLIIT Staff Publications Research Publications -Dept of Information Technology |
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978-3-319-68318-8_9.pdf Until 2050-12-31 | 248.67 kB | Adobe PDF | View/Open Request a copy |
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