Faculty of Computing

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Has files: YesSubject: search.filters.subject.Educational data mining

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    Predicting Students’ Academic Performance Using Utility Based Educational Data Mining
    (Springer, Singapore, 2017-07-03) Kasthuriarachchi, K. T. S; Liyanage, R. S
    Knowledge extracted from educational data can be used by the educators to obtain insights about how the quality of teaching and learning must be improved, how the factors affect the performance of the students and how qualified students can be trained for the industry requirements. This research focuses on classifying a knowledge based system using a set of rules. The main purpose of the study is to analyze the most influencing attributes of the students for their module performance in tertiary education in Sri Lanka. The study has gathered data about students in a reputed degree awarding institute in Sri Lanka and used three different data mining algorithms to predict the influential factors and they have been evaluated for interestingness using objective oriented utility based method. Subsequently, age of the students, their family background with regard to parents’ occupations, average monthly income of the family, their English language fluency level and knowledge of Mathematics were identified as the interesting factors. The findings of this study will positively affect the future decisions made regarding the progress of the students’ performance, quality of the education process and the future of the education provider.
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    A Data Mining Approach to Identify the Factors Affecting the Academic Success of Tertiary Students in Sri Lanka
    (Springer, Cham, 2018-02-11) Kasthuriarachchi, S; Bhatt, C. M; Liyanage, S. R
    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.