Learning Analytics for Blended Learning: A Systematic Review of Theory, Methodology, and Ethical Considerations

Nina Bergdahl, Jalal Nouri, Thashmee Karunaratne, Muhammad Afzaal, Mohammed Saqr

Abstract


Learning Analytics (LA) approaches in Blended Learning (BL) research is becoming an established field. In the light of previous critiqued toward LA for not being grounded in theory, the General Data Protection and a renewed focus on individuals’ integrity, this review aims to explore the use of theories, the methodological and analytic approaches in educational settings, along with surveying ethical and legal considerations. The review also maps and explores the outcomes and discusses the pitfalls and potentials currently seen in the field. Journal articles and conference papers were identified through systematic search across relevant databases. 70 papers met the inclusion criteria:  they applied LA within a BL setting, were peer-reviewed, full-papers, and if they were in English. The results reveal that the use of theoretical and methodological approaches was disperse, we identified approaches of BL not included in categories of BL in existing BL literature and suggest these may be referred to as hybrid blended learning, that ethical considerations and legal requirements have often been overlooked. We highlight critical issues that contribute to raise awareness and inform alignment for future research to ameliorate diffuse applications within the field of LA.


Keywords


litterature review; learning analytics; blended learning; systematic review

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Copyright (c) 2020 Nina Bergdahl, Jalal Nouri, Muhammad Afzaal, Mohammed Saqr, Thashmee Karunaratne


International Journal of Learning Analytics and Artificial Intelligence for Education. ISSN: 2706-7564
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