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ERIC Number: EJ1462858
Record Type: Journal
Publication Date: 2025-Mar
Pages: 26
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1360-2357
EISSN: EISSN-1573-7608
Available Date: 2024-08-30
How Educational Chatbots Support Self-Regulated Learning? A Systematic Review of the Literature
Education and Information Technologies, v30 n4 p4493-4518 2025
Engagement in self-regulated learning (SRL) may improve academic achievements and support development of lifelong learning skills. Despite its educational potential, many students find SRL challenging. Educational chatbots have a potential to scaffold or externally regulate SRL processes by interacting with students in an adaptive way. However, to our knowledge, researchers have yet to learn whether and how educational chatbots developed so far have (1) promoted learning processes pertaining to SRL and (2) improved student learning performance in different tasks. To contribute this new knowledge to the field, we conducted a systematic literature review of the studies on educational chatbots that can be linked to processes of SRL. In doing so, we followed the PRISMA guidelines. We collected and reviewed publications published between 2012 and 2023, and identified 27 publications for analysis. We found that educational chatbots so far have mainly supported learners to identify learning resources, enact appropriate learning strategies, and metacognitively monitor their studying. Limited guidance has been provided to students to set learning goals, create learning plans, reflect on their prior studying, and adapt to their future studying. Most of the chatbots in the reviewed corpus of studies appeared to promote productive SRL processes and boost learning performance of students across different domains, confirming the potential of this technology to support SRL. However, in some studies the chatbot interventions showed non-significant and mixed effects. In this paper, we also discuss the findings and provide recommendations for future research.
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link-springer-com.bibliotheek.ehb.be/
Publication Type: Journal Articles; Information Analyses
Education Level: Elementary Secondary Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: 1Monash University, Centre for Learning Analytics at Monash, Faculty of Information Technology, Clayton, Australia; 2School of Informatics, University of Edinburgh, Edinburgh, UK