Analysis of learning analytics in higher educational institutions: A Review

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Abstract

Learning analytics is relatively new in the field of research models, assessment/evaluation, and business intelligence. The critical analysis of literature explains that, as a consequence of more and better data, learning analytics gained significant attention in education. This paper emphasized integration of three major components: educational data mining, learning analytics, and academic analytics. It gives the comprehensive background for increasing understanding of the positive aspects of implementing the framework of learning analytics (LA) in higher educational institutions in Malaysia. Besides emphasizing LA, the role of educational data mining (EDM) in adaptive learning is also discussed. It gives an empirical-based overview with the key objectives of adopting the proposed model of LA in generic educational strategic planning by Malaysian HEIs. It examined the literature on experimental case studies, conducted during the last six years (2012–2017) for extracting recently updated information on increasing HEIs performance in Malaysia. The results have highlighted some major directions of LA, EDM, and academic analytics in driving techniques for achieving student retention and enhancing employability.

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APA

Rajesh Kumar, S., & Hamid, S. (2017). Analysis of learning analytics in higher educational institutions: A Review. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10645 LNCS, pp. 185–196). Springer Verlag. https://doi.org/10.1007/978-3-319-70010-6_18

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