Self-regulated learning, study skills, and learning analytics dashboards in an undergraduate learning environment

This study explored the use of learning analytics dashboards (LADs) to support self-regulated learning (SRL) for undergraduates. Learning analytics data have become more widely available in the context of undergraduate learning environments. In recent years, it has become much easier to capture students’ online interactions with an institution’s learning management system (LMS) and third-party platforms associated with a course (e.g., textbook publishers, homework platforms, student response systems, etc.). These interactions generate log data that can be shared with learners to help them understand aspects of their own learning process. This presents an opportunity to support learners’ development and execution of SRL skills. Additionally, there is the potential to supplement traditional methods of measuring SRL (e.g., self-report survey instruments) with measures of behavior which are less prone to certain pitfalls.

Publication Details

Journal
Iowa Research Online (The University of Iowa)
Published
2025-05-21
DOI
https://doi.org/10.25820/etd.008124
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Self-regulated learning, study skills, and learning analytics dashboards in an undergraduate learning environment

Iowa Research Online (The University of Iowa)
Online Learning and Analytics
article

Self-regulated learning, study skills, and learning analytics dashboards in an undergraduate learning environment

article en

Abstract

This study explored the use of learning analytics dashboards (LADs) to support self-regulated learning (SRL) for undergraduates. Learning analytics data have become more widely available in the context of undergraduate learning environments. In recent years, it has become much easier to capture students’ online interactions with an institution’s learning management system (LMS) and third-party platforms associated with a course (e.g., textbook publishers, homework platforms, student response systems, etc.). These interactions generate log data that can be shared with learners to help them understand aspects of their own learning process. This presents an opportunity to support learners’ development and execution of SRL skills. Additionally, there is the potential to supplement traditional methods of measuring SRL (e.g., self-report survey instruments) with measures of behavior which are less prone to certain pitfalls.

Iowa Research Online (The University of Iowa)
Quality Education
Openalex Percentile: Top 36%
Online Learning and Analytics
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