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Wang, Qin; Mousavi, Amin – British Journal of Educational Technology, 2023
Technologies and teaching practices can provide a rich log data, which enables learning analytics (LA) to bring new insights into the learning process for ultimately enhancing student success. This type of data has been used to discover student online learning patterns, relationships between online learning behaviors and assessment performance.…
Descriptors: Predictor Variables, Academic Achievement, Literature Reviews, Meta Analysis
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Ozan Rasit Yürüm; Tugba Taskaya-Temizel; Soner Yildirim – Technology, Knowledge and Learning, 2024
The purpose of this study was to investigate the use of predictive video analytics in online courses in the literature. A systematic literature review was performed based on a hybrid search strategy that included both database searching and backward snowballing. In total, 77 related publications published between 2011 and April 2023 were…
Descriptors: Literature Reviews, Distance Education, Online Courses, Video Technology
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Jongile, Sonwabo – International Journal on E-Learning, 2022
The identification of predictor variables for students at-risk of dropping out of university has received increased attention in higher education settings internationally concerning the context of origin in which they are developed and the different academic context in which they are introduced, often lacking schema-theoretic perspectives to offer…
Descriptors: Predictor Variables, At Risk Students, Potential Dropouts, College Students
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Phillips, Tanner; Ozogul, Gamze – TechTrends: Linking Research and Practice to Improve Learning, 2020
In this study the authors conducted an empirical, bibliometric analysis of current literature in learning analytics. The authors performed a citation network analysis and found three dominant clusters of research. A qualitative thematic review of publications in these clusters revealed distinct context, goals, and topics. The largest cluster…
Descriptors: Learning Analytics, Educational Research, Bibliometrics, Citation Analysis
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Saqr, Mohammed; Jovanovic, Jelena; Viberg, Olga; Gaševic, Dragan – Studies in Higher Education, 2022
Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…
Descriptors: Meta Analysis, Learning Analytics, Predictor Variables, Correlation