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Decrypting Log Data
Author(s) -
Maria Klose,
Diana Steger,
Julian Fick,
Cordula Artelt
Publication year - 2022
Publication title -
zeitschrift für psychologie
Language(s) - English
Resource type - Journals
eISSN - 2190-8370
pISSN - 2151-2604
DOI - 10.1027/2151-2604/a000484
Subject(s) - operationalization , moderation , learning analytics , online learning , psychology , computer science , data science , world wide web , social psychology , philosophy , epistemology
. Analyzing log data from digital learning environments provides information about online learning. However, it remains unclear how this information can be transferred to psychologically meaningful variables or how it is linked to learning outcomes. The present study summarizes findings on correlations between general online activity and learning outcomes in university settings. The course format, instructions to engage in online discussions, requirements, operationalization of general online activity, and publication year are considered moderators. A multi-source search provided 41 studies ( N = 28,986) reporting 69 independent samples and 104 effect sizes. The three-level random-effects meta-analysis identified a pooled effect of r = .25 p = .003, 95% CI [.09, .41], indicating that students who are more active online have better grades. Despite high heterogeneity, Q(103) = 3,960.04, p < .001, moderator analyses showed no statistically significant effect. We discuss further potential influencing factors in online courses and highlight the potential of learning analytics.

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