A systematic mapping review at the intersection of artificial intelligence and self-regulated learning
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| Publicat a: | International Journal of Educational Technology in Higher Education vol. 22, no. 1 (Dec 2025), p. 50 |
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| Altres autors: | , , , |
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Springer Nature B.V.
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| Accés en línia: | Citation/Abstract Full Text Full Text - PDF |
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| 003 | UK-CbPIL | ||
| 022 | |a 2365-9440 | ||
| 022 | |a 1698-580X | ||
| 024 | 7 | |a 10.1186/s41239-025-00548-8 |2 doi | |
| 035 | |a 3235190030 | ||
| 045 | 2 | |b d20251201 |b d20251231 | |
| 084 | |a 142233 |2 nlm | ||
| 100 | 1 | |a Banihashem, Seyyed Kazem |u Open Universiteit, Heerlen, The Netherlands (GRID:grid.36120.36) (ISNI:0000 0004 0501 5439) | |
| 245 | 1 | |a A systematic mapping review at the intersection of artificial intelligence and self-regulated learning | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Recently, artificial intelligence (AI) has increasingly been integrated into self-regulated learning (SRL), presenting novel pathways to support SRL. While AI-SRL research has experienced rapid growth, there remains a significant gap in understanding the intersection between AI and SRL, resulting in oversight when identifying critical areas necessitating additional research or practical attention. Building upon a well-established framework, from Chatti and colleagues, this systematic mapping review identified 84 studies through the Web of Science, Scopus, IEEE Xplore, ACM Digital, EBSCOHost, Google Scholar, and Open Alex, to explore the intersection of AI and SRL within the four key aspects—Who (stakeholders), What (theory), How (methods), and Why (objectives). The main results revealed that AI-SRL research predominantly focuses on higher education students, with minimal attention to primary education and educators. AI is primarily implemented as an intervention—through adaptive systems and personalization, prediction and profiling, intelligent tutoring systems, and assessment and evaluation—to support students' SRL and learning processes. The direct impact of AI on SRL was primarily focused on the metacognitive and cognitive aspects of SRL, while the motivational aspect of SRL remains underexplored. While over one-third of the AI-SRL studies did not specify an SRL theory, Zimmerman’s model of SRL was the most frequently applied among those that did. The use of AI in supporting SRL has extended beyond just focusing on and supporting SRL itself; it has also aimed to enhance various educational and learning activities as end outcomes such as improving academic performance, motivation and emotions, engagement, and collaborative learning. The results of this study extend our understanding of the effective application of AI in supporting SRL and optimizing educational outcomes. Suggestions for further research and practice are provided. | |
| 653 | |a Students | ||
| 653 | |a Collaboration | ||
| 653 | |a Mapping | ||
| 653 | |a Educational technology | ||
| 653 | |a Feedback | ||
| 653 | |a Teachers | ||
| 653 | |a Cognition & reasoning | ||
| 653 | |a Adaptive systems | ||
| 653 | |a Learning | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Education | ||
| 653 | |a Metacognition | ||
| 653 | |a Self regulation | ||
| 653 | |a Collaborative learning | ||
| 653 | |a Academic achievement | ||
| 653 | |a Tutoring | ||
| 653 | |a Higher education | ||
| 653 | |a College students | ||
| 653 | |a Research | ||
| 653 | |a Emotions | ||
| 653 | |a Learning processes | ||
| 653 | |a Cognitive aspects | ||
| 653 | |a Motivation | ||
| 653 | |a Attention | ||
| 653 | |a Elementary education | ||
| 653 | |a Cooperative learning | ||
| 653 | |a Educational activities | ||
| 653 | |a Learning outcomes | ||
| 653 | |a Profiles | ||
| 653 | |a Learning Analytics | ||
| 653 | |a Literature Reviews | ||
| 653 | |a Educational Development | ||
| 653 | |a Scaffolding (Teaching Technique) | ||
| 653 | |a Stakeholders | ||
| 653 | |a Self Efficacy | ||
| 653 | |a Intelligent Tutoring Systems | ||
| 653 | |a Influence of Technology | ||
| 653 | |a Distance Education | ||
| 653 | |a Cognitive Processes | ||
| 653 | |a Educational Change | ||
| 653 | |a Trust (Psychology) | ||
| 653 | |a At Risk Students | ||
| 653 | |a Short Term Memory | ||
| 653 | |a Student Records | ||
| 653 | |a Science Instruction | ||
| 653 | |a Elementary Secondary Education | ||
| 653 | |a Language Processing | ||
| 653 | |a Theory Practice Relationship | ||
| 653 | |a Algorithms | ||
| 700 | 1 | |a Bond, Melissa |u University College London, London, UK (GRID:grid.83440.3b) (ISNI:0000 0001 2190 1201); University of Stavanger, Stavanger, Norway (GRID:grid.18883.3a) (ISNI:0000 0001 2299 9255) | |
| 700 | 1 | |a Bergdahl, Nina |u Stockholm University, Stockholm, Sweden (GRID:grid.10548.38) (ISNI:0000 0004 1936 9377); Halmstad University, Halmstad, Sweden (GRID:grid.73638.39) (ISNI:0000 0000 9852 2034) | |
| 700 | 1 | |a Khosravi, Hassan |u The University of Queensland, Brisbane, Australia (GRID:grid.1003.2) (ISNI:0000 0000 9320 7537) | |
| 700 | 1 | |a Noroozi, Omid |u Wageningen University and Research, Wageningen, The Netherlands (GRID:grid.4818.5) (ISNI:0000 0001 0791 5666) | |
| 773 | 0 | |t International Journal of Educational Technology in Higher Education |g vol. 22, no. 1 (Dec 2025), p. 50 | |
| 786 | 0 | |d ProQuest |t Political Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3235190030/abstract/embedded/Q8Z64E4HU3OH5N8U?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3235190030/fulltext/embedded/Q8Z64E4HU3OH5N8U?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3235190030/fulltextPDF/embedded/Q8Z64E4HU3OH5N8U?source=fedsrch |