Actionable companion · Feedback & scaffolding

Learning with agency: Self-regulated and socially shared regulation of learning in adaptive collaborative educational environments: a scoping review

AI-assisted editorial implementation guide, separate from the original research. Proposed actions are not claims or recommendations attributed to the source authors. No independent peer review of this guide is asserted.

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Evidence and context

Title and abstract screening; stage labels describe reported settings, not verified numerical ages. Design labels require full-text appraisal. Reported stage(s): Higher education. Verify the participant population and task before transferring the findings.

Original authors’ abstract, reproduced under the linked source license:

Abstract Background Collaborative learning is central to higher education, yet its effectiveness depends on learners’ ability to regulate learning both individually and collectively. While self-regulated learning (SRL) and socially shared regulation of learning (SSRL) are recognised as complementary processes, their interaction within adaptive collaborative learning environments remains insufficiently synthesised. The objective of this scoping review was to map and synthesise existing literature describing the components, processes, and adaptive strategies underpinning the interplay between SRL and SSRL in collaborative learning contexts in higher education, and to identify the current evidentiary base within high-stakes fields like health professions education. Methods A scoping review was conducted following the Arksey and O’Malley framework and reported in accordance with PRISMA-ScR guidelines. Searches were performed across PubMed/MEDLINE, Google Scholar, ScienceDirect, Semantic Scholar, and Taylor & Francis for studies published between 2004 and 2024. Eligible studies addressed SRL, SSRL, collaborative learning, and/or adaptive learning in higher or health professions education. Data were systematically charted and analysed using a hybrid inductive-deductive thematic analysis. Results A total of 31 studies met the inclusion criteria, including 14 empirical, 12 conceptual/theoretical, 4 review-based contributions and one bibliometric analysis. Regulation in collaborative learning was found to be dynamic, involving continuous shifts between individual and shared processes across affective, cognitive, metacognitive, and motivational domains. Recurrent challenges included emotional strain, misaligned goals, invisible reasoning, uneven participation, and coordination breakdowns. Adaptive learning supported regulatory processes through personalised feedback, scaffolding, dashboards, and prompts. However, these systems largely operated in parallel, addressing either individual regulation or group-level processes, with limited emphasis on harmonising SRL and SSRL. Empirical evidence from health professions education was limited. Conclusions Effective collaborative learning depends on dynamic coordination between self- and socially shared regulation. Although adaptive learning environments show promise, current designs provide limited support for coordinating individual and collective regulatory processes. Notably, empirical research applying these frameworks within higher education is critically scarce, particularly in health professions education. This highlights a major gap for future theory-informed adaptive designs that must harmonise individual autonomy with shared accountability. Supplementary Information The online version contains supplementary material available at 10.1186/s12909-026-09355-9. Keywords: Self-regulated learning, Socially shared regulation, Collaborative learning, Adaptive learning, Health professions education

What kind of evidence is this?

Intelligent tutoring & adaptive learning · Qualitative / mixed methods

Stage: Higher education. Screening labels describe reported context and study-design language. They are not a risk-of-bias rating or proof of effectiveness for an age band.

Study methods · source passage

The 31 included studies represent a diverse body of work spanning self-regulated learning (SRL), co-regulation, socially shared regulation of learning (SSRL), collaborative learning, and adaptive learning systems. Study designs included quantitative (n = 2), qualitative (n = 4), mixed methods (n = 8) empirical studies, alongside non-empirical contributions, including conceptual/theoretical papers (n = 11), literature reviews (n = 4; three systematic and one narrative), and one bibliometric analysis. This distribution reflects both methodological breadth and the conceptual richness of the field.

Limitations and uncertainty · source passage

This scoping review provides a comprehensive synthesis of literature examining the interaction between self-regulated learning and socially shared regulation of learning within collaborative contexts. By integrating evidence across affective, cognitive, metacognitive, and motivational domains, it advances understanding beyond single-domain or individual-level perspectives that dominate existing research.

Design the system before the pilot

Document the learner model, mastery rule, hint sequence and adaptation signal. Compare adaptive routing with the same content in a non-adaptive sequence. Check whether early errors lead to persistent low-expectation pathways.

Give feedback on the learner’s reasoning, then fade hints. Record whether the learner can complete the next task without that scaffold.
Use plan–attempt–check–reflect prompts and compare confidence with actual performance. Keep learner choice and reflection visible.
Measure engagement separately from achievement. Check whether novelty-driven participation persists and whether it translates to independent performance.
Use common rubrics, blind scoring where feasible and a fresh unaided reasoning task. Document permissible assistance and avoid treating AI-detector scores as proof of misconduct.
Co-design accommodations with learners and specialists. Check access and error burden across groups without inferring subgroup effectiveness from small or unreported samples.

A 90-day district pilot

Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
Days 16–30 · Design. Choose one disciplinary task. Require a first attempt, a documented AI consultation, a critique of the output and an independent explanation. Align the comparison group and scoring rubric with the same objective. Name an accountable owner and set the baseline, success threshold and budget before implementation.
Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
Days 61–90 · Decide. Blind-score reasoning and accuracy on a new task without AI. Distinguish model examination scores, student perceptions and actual learner gains; only the last directly tests educational benefit. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Faiza Ikram; Rahila Yasmeen; Humaira Fayyaz. Self-regulated and socially shared regulation of learning in adaptive collaborative educational environments: a scoping review. BMC Medical Education (2026-06-15). https://doi.org/10.1186/s12909-026-09355-9

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.