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Title:      LEARNING ANALYTICS BASED INTERVENTIONS: A SYSTEMATIC REVIEW OF EXPERIMENTAL STUDIES
Author(s):      Mustafa Tepgec and Dirk Ifenthaler
ISBN:      978-989-8704-43-6
Editors:      Demetrios G. Sampson, Dirk Ifenthaler and Pedro IsaĆ­as
Year:      2022
Edition:      Single
Keywords:      Learning Analytics, Intervention, Educational Data Mining, Experimental Studies, Systematic Literature Review
Type:      Short Paper
First Page:      327
Last Page:      330
Language:      English
Cover:      cover          
Full Contents:      click to dowload Download
Paper Abstract:      Learning analytics includes interventions that will support learning and improve learning environments. Despite the fact that learning analytics is a promising field of study, the lack of empirical evidence on the effects of learning analytics-based interventions has been widely addressed in recent years. In this context, insights validated by experimental studies may play a crucial role. Therefore, there is a need for a report describing the methodological aspects and effects of current experimental interventions based on learning analytics. This systematic review provides an in-depth examination of learning analytics research that reports experimental findings to evaluate learning analytics-based interventions. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 protocol provided the basis for the work of this systematic review. This review contained 52 papers that met the inclusion and exclusion criteria. The results show that student-facing dashboards are the most common learning analytics-based intervention. Evidence from how user data is handled for interventions demonstrates that the most common method is the distillation of data for human judgment. This study confirms that a significant proportion of experimental studies employing learning analytics interventions have demonstrated significant effects on learning outcomes. The effectiveness of learning analytics-based interventions is also addressed in this review in terms of motivation, engagement, and system usage behaviors. The findings of this study will contribute to the literature in terms of describing the experimentally validated findings of learning analytics-based interventions in depth.
   

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