research-article

Exploring the relation between self-regulation, online activities, and academic performance: a case study

Authors:

Abelardo Pardo,

Robert A. EllisAuthors Info & Claims

LAK '16: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge

Pages 422 - 429

https://doi.org/10.1145/2883851.2883883

Published: 25 April 2016 Publication History

Abstract

The areas of educational data mining and learning analytics focus on the extraction of knowledge and actionable items from data sets containing detailed information about students. However, the potential impact from these techniques is increased when properly contextualized within a learning environment. More studies are needed to explore the connection between student interactions, approaches to learning, and academic performance. Self-regulated learning (SRL) is defined as the extent to which a student is able to motivationally, metacognitively, and cognitively engage in a learning experience. SRL has been the focus of research in traditional classroom learning and is also argued to play a vital role in the online or blended learning contexts. In this paper, we study how SRL affects students' online interactions with various learning activities and its influence in academic performance. The results derived from a naturalistic experiment among a cohort of first year engineering students showed that positive self-regulated strategies (PSRS) and negative self-regulated strategies (NSRS) affected both the interaction with online activities and academic performance. NSRS directly predicted academic outcomes, whereas PSRS only contributed indirectly to academic performance via the interactions with online activities. These results point to concrete avenues to promote self-regulation among students in this type of learning contexts.

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Index Terms

Exploring the relation between self-regulation, online activities, and academic performance: a case study
1. Applied computing
  1. Education
    1. Computer-assisted instruction
    2. E-learning

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cover image ACM Other conferences

LAK '16: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge

April 2016

567 pages

ISBN:9781450341905

DOI:10.1145/2883851

General Chairs:
Dragan Gašević
University of Edinburgh, United Kingdom
,
Grace Lynch
Society for Learning Analytics Research
,
Program Chairs:
Shane Dawson
University of South Australia
,
Hendrik Drachsler
University of the Netherlands
,
Carolyn Penstein Rosé
Carnegie Mellon University

Copyright © 2016 ACM.

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Published: 25 April 2016

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LAK '16: 6th International Conference on Learning Analytics and Knowledge

April 25 - 29, 2016

Edinburgh, United Kingdom

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LAK '16 Paper Acceptance Rate 36 of 116 submissions, 31%;

Overall Acceptance Rate 236 of 782 submissions, 30%

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Dol SJawandhiya P(2024)Systematic Review and Analysis of EDM for Predicting the Academic Performance of StudentsJournal of The Institution of Engineers (India): Series B10.1007/s40031-024-00998-0105:4(1021-1071)Online publication date: 4-Feb-2024
https://doi.org/10.1007/s40031-024-00998-0
Alruwais NZakariah M(2023)Student-Engagement Detection in Classroom Using Machine Learning AlgorithmElectronics10.3390/electronics1203073112:3(731)Online publication date: 1-Feb-2023
https://doi.org/10.3390/electronics12030731
Zhao SCao C(2023)Exploring Relationship Among Self-Regulated Learning, Self-Efficacy and Engagement in Blended Collaborative ContextSage Open10.1177/2158244023115724013:1Online publication date: 24-Feb-2023
https://doi.org/10.1177/21582440231157240
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Dima ABusu MVargas V(2022)The mediating role of students' ability to adapt to online activities on the relationship between perceived university culture and academic performanceOeconomia Copernicana10.24136/oc.2022.03613:4(1253-1281)Online publication date: 30-Dec-2022
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Han FEllis RPardo A(2022)The Descriptive Features and Quantitative Aspects of Students’ Observed Online Learning: How Are They Related to Self-Reported Perceptions and Learning Outcomes?IEEE Transactions on Learning Technologies10.1109/TLT.2022.315300115:1(32-41)Online publication date: 1-Feb-2022
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