Abstract
Adaptive learning and learning analytics are powerful learning tools on their own. Scholars have reported outcomes on combining them, but the lack of a summary from these studies prevents stakeholders from having a clear view of this combination. In this paper, we consider the key dimensions of learning analytics applications in adaptive learning, in order to suggest a proper reference framework that serves as the basis to systematically review the literature. The findings suggest that interesting research work has been carried out during the last years on the topic. Yet, there is a clear lack of studies (a) on school education and in topics outside STEM and (b) that do not focus solely on the (self-)reflection of students or tutors. Finally, the majority of the studies merely concentrates on narrow measures of learning like student performance. A niche area taking into account more complex student behaviors, like collaboration, is emerging.
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This research work is supported by the European Research Consortium for Informatics and Mathematics (ERCIM).
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Mavroudi, A., Giannakos, M., Krogstie, J. (2016). Combining Adaptive Learning with Learning Analytics: Precedents and Directions. In: Verbert, K., Sharples, M., Klobučar, T. (eds) Adaptive and Adaptable Learning. EC-TEL 2016. Lecture Notes in Computer Science(), vol 9891. Springer, Cham. https://doi.org/10.1007/978-3-319-45153-4_39
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DOI: https://doi.org/10.1007/978-3-319-45153-4_39
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