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A metacognitive approach to learning and performance in human-AI interaction
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Generative artificial intelligence (GenAI) is rapidly becoming a pervasive technology across education, work, research, and everyday life. Yet growing evidence suggests that fluent, coherent, and seemingly transparent AI assistance can improve task performance while weakening the metacognitive engagement and deeper processing required for durable learning. This tension raises a central question about how does offloading to AI reshape human learning, and under what conditions do performance and learning decouple? In this Perspective, we introduce the Synergetic Notion of Human-AI Skills and Knowledge Construction (SYNC) model. The model offers a metacognitive account of human-AI interaction by conceptualising metacognitive offloading and metacognitive onloading. The SYNC model aims to explain how human-AI interaction unfolds across learning and performance dimensions, clarifying how learners may drift into overreliant AI-supported performance or move toward human-AI synergy. We further identify key pitfalls in ineffective human-AI interaction and outline strategies to address them through metacognitive onloading and support human-AI synergy.
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Flagged first, then by citations
Research works printed but not linked: 2
- Vygotsky, L. S. Mind in Society: The Development of Higher Psychological Processes (Harvard University Press, Cambridge, MA, 1978).
- Neisser, U.Cognitive Psychology (Appleton-Century-Crofts, New York, First edition; later reprinted by Prentice Hall. 1967).
Cited by
Sorted by citations
Shafiq, A. (2026) · Research Square · doi:10.21203/rs.3.rs-11596206/v1
Metadata
- Authors
- Fan, Y., Yan, L., Molenaar, I., Greiff, S., & Gašević, D.
- Affiliations
- Peking University (CN)
- Tsinghua University (CN)
- Radboud University Nijmegen (NL)
- Technical University of Munich (DE)
- Monash University (AU)
- Corresponding author
- Fan, Yizhou
- Gašević, Dragan
- Venue
- Communications Psychology
- Published
- 2026-10-30
- Volume
- 4
- Issue
- 1
- ISSN
- 2731-9121 (ISSN-L)
- PMC
- PMC13722690
- OpenAlex
- W7172215497
- Cited by
- 1
- References
- 180
- Citations by year
- 2026: 1
- FWCI
- 1.32
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Communications Psychology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Natural Science Foundation of China (62407001)
- Jacobs Foundation
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- metacognition, human-AI interaction, generative AI, task performance, overreliance on AI, human-AI synergy, metacognitive scaffolding, knowledge construction
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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