{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T08:40:59Z","timestamp":1792485659522,"version":"4.5.0"},"reference-count":74,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T00:00:00Z","timestamp":1792454400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T00:00:00Z","timestamp":1792454400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72274076"],"award-info":[{"award-number":["72274076"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["30106250036"],"award-info":[{"award-number":["30106250036"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bera-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Brit J Educational Tech"],"abstract":"Abstract<\/jats:title>\n \n \n Socially shared regulation of learning (SSRL) is essential for successful collaboration, yet effectively scaffolding it remains challenging because regulatory needs are dynamic and context\u2010dependent. While generative AI (GenAI) offers potential for adaptive support, current applications in collaborative learning largely position it as a content\u2010oriented tutor for knowledge explanation or idea generation, leaving its role as a process\u2010oriented team moderator for scaffolding SSRL processes underexplored. To address this gap, we conducted a 16\u2010week quasi\u2010experiment with 64 undergraduates in China, comparing adaptive SSRL scaffolding delivered by a GenAI agent in the adaptive\u2010SSRL condition with static scaffolding via structured digital worksheets in the static\u2010SSRL condition. Survey data and group discussion transcripts were analysed using statistical methods and epistemic network analysis. Results indicated several differences in students' multidimensional engagement between the two conditions: (1) Behaviourally, the adaptive\u2010SSRL group showed significantly higher participation equality, although participation intensity did not differ significantly between groups. (2) Cognitively, the adaptive\u2010SSRL group demonstrated deeper cognitive engagement, reflected in more advanced cognitive presence phases and more integrative, solution\u2010oriented discourse patterns. (3) Emotionally, the adaptive\u2010SSRL group reported significantly higher overall emotional engagement, particularly feeling more relaxed during collaboration and more connected with peers. These findings extend human\u2013AI collaboration research by showing that GenAI can function as an SSRL\u2010informed team moderator rather than a content\u2010oriented tutor. They also offer design implications for GenAI\u2010enabled adaptive SSRL scaffolding and human\u2013AI role division in CSCL.<\/jats:p>\n <\/jats:sec>\n \n \n \n \n \n Practitioner notes<\/jats:title>\n <\/jats:caption>\n \n What is already known about this topic\n \n \n Socially shared regulation of learning (SSRL) is critical for successful collaboration and is closely associated with the quality of student engagement.<\/jats:p>\n <\/jats:list-item>\n \n While static scaffolds (eg, worksheets) provide a basic regulatory structure, they fail to adapt to the dynamic and emergent needs of collaborating teams.<\/jats:p>\n <\/jats:list-item>\n \n Generative AI (GenAI) is increasingly used for personalised content support, yet its potential as a process\u2010oriented team moderator remains underexplored.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n \n What this paper adds\n \n \n This study introduced SSRLAgent, a GenAI agent grounded in SSRL theory and established principles of collective metacognitive support, to provide adaptive and interactive regulatory scaffolding.<\/jats:p>\n <\/jats:list-item>\n \n In a 16\u2010week quasi\u2010experiment, we compared GenAI\u2010enabled adaptive SSRL scaffolding (SSRLAgent) with static scaffolding (structured digital worksheets) in CSCL.<\/jats:p>\n <\/jats:list-item>\n \n Adaptive\u2010SSRL scaffolding was associated with higher\u2010quality engagement: greater participation equality, deeper cognitive engagement and higher overall emotional engagement.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n \n Implications for practice and\/or policy\n \n \n The study underscores the necessity of shifting SSRL scaffolding from static, \u2018one\u2010size\u2010fits\u2010all\u2019 support to adaptive GenAI interventions to improve collaborative engagement.<\/jats:p>\n <\/jats:list-item>\n \n The findings provide design guidance for developing SSRL agents that are embedded in the shared interaction space and responsive to groups' moment\u2010to\u2010moment regulatory needs.<\/jats:p>\n <\/jats:list-item>\n \n The study suggests a productive human\u2013AI division of labour: GenAI agents can support process coordination and regulatory prompting, while teachers and peers remain essential for relationally complex forms of support that collaborative learning requires.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n <\/jats:boxed-text>\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1111\/bjet.70096","type":"journal-article","created":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T08:21:46Z","timestamp":1792484506000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generative\n AI<\/scp>\n as a team moderator in\n CSCL<\/scp>\n : Facilitating students' multidimensional engagement through adaptive scaffolding for socially shared regulation of 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