3.8 Proceedings Paper

Increasing the Impact of Learning Analytics

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.1145/3303772.3303784

Keywords

Learning Analytics; epistemic network analysis; adoption

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Learning Analytics (LA) studies the learning process in order to optimize learning opportunities for students. Although LA has quickly risen to prominence, there remain questions regarding the impact LA has made to date. To evaluate the extent that LA has impacted our understanding of learning and produced insights that have been translated to mainstream practice or contributed to theory, we reviewed the research published in 2011-2018 LAK conferences and Journal of Learning Analytics. The reviewed studies were coded according to five dimensions: study focus, data types, purpose, institutional setting, and scale of research and implementation. The coding and subsequent epistemic network analysis indicates that while LA research has developed in the areas of focus and sophistication of analyses, the impact on practice, theory and frameworks have been limited. We hypothesize that this finding is due to a continuing predominance of small-scale techno-centric exploratory studies that to date have not fully accounted for the multidisciplinarity that comprises education. For the field to reach its potential in understanding and optimizing learning and learning environments, there must be a purposeful shift to move from exploratory models to more holistic and integrative systems-level research. This necessitates greater effort applied to understanding the research cycles that emerge when multiple knowledge domains coalesce into new fields of research.

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