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Cited by 10Artificial Intelligence in EducationInnovative Teaching and Learning MethodsProblem and Project Based Learning

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Generative AI and student collaboration: a scoping review of group work processes, outcomes, and risks

Open access
Wei, Yan, Perkins, Mike·2026·International Journal for Educational Integrity
DOI 10.1007/s40979-026-00217-x
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Abstract

Generative artificial intelligence is increasingly used by higher education students during group work; however, evidence on how it reshapes collaboration remains fragmented. This scoping review maps recent research on how generative AI influences student group work in higher education and identifies the reported benefits, risks, and implications for practice. Following the PRISMA extension for scoping reviews, Scopus, Web of Science, and Google Scholar were searched for English-language publications from January 2023 to March 2025. After screening, 18 studies were included and analysed using reflexive thematic analysis. The literature reports the potential benefits of group knowledge development, idea generation, reflective thinking support, communication efficiency, task coordination, and timely feedback. Reported risks include reduced peer-to-peer interaction and critical engagement when tools are over-relied on, alongside privacy, transparency, and bias concerns in AI-mediated collaboration. Across studies, outcomes appear contingent on task design, degree of integration into group workflows, and students’ AI literacy and subject expertise. The review highlights the need for clearer pedagogical guidance on when and how generative AI should be used in group work to preserve human agency, support academic integrity and equitable participation, and align assessments with collaborative learning processes. Future research should prioritise longitudinal and intervention-based studies that examine both learning outcomes and group dynamics over time.

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  • GenAI became part of the distributed cognitive system of the team rather than replacing the expertise of individual members.

    “In this sense, GenAI became part of the distributed cognitive system of the team rather than replacing the expertise of individual members, extending emerging observations that GenAI can facilitate collaborative knowledge construction and exchange (An et al. 2025; Wei and Perkins 2026).”

    From Generative AI Expands the Intellectual Reach of Course Based Undergraduate Research Experiences (CUREs) (2026) · cites this paper as Wei and Perkins 2026

    Theme 1 describes knowledge development as becoming more distributed and interactive, with GenAI acting as a collaborator and cognitive scaffold. The 'Human agency should be prioritised' section recommends augmenting rather than replacing human contributions, but the review does not establish that GenAI joined a particular team's cognitive system without replacing its members' expertise. Page numbers are unavailable in our copy. (LLM, conf=0.86)

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Research works printed but not linked: 34

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Metadata

Authors
Wei, Y., & Perkins, M.
Affiliations
  • Lancaster University (GB)
  • British University Vietnam (VN)
Corresponding author
Perkins, Mike
ORCID
Venue
International Journal for Educational Integrity
Publisher
Springer Science and Business Media LLC
Published
2026-04-30
Volume
22
Issue
1
ISSN
1833-2595 (ISSN-L)
DOI
10.1007/s40979-026-00217-x
OpenAlex
W7159957271
Cited by
10
References
9
Citations by year
2026: 10
FWCI
45.44
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal for Educational Integrity (publishedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
RMIT University
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Social Sciences › Education › Problem and Project Based Learning
Keywords
generative AI, student group work, cooperative learning, higher education, peer interaction, AI literacy, academic integrity, risks of AI in education, group dynamics, task design, equitable participation, human agency

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