Actionable companion · Feedback & scaffolding

Learning with agency: Structured Development of Learning and Assessment Tasks to Prevent Generative AI Misuse and Enhance AI Literacy in the Faculty in Physiotherapy Education

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, Adult & professional learning. Verify the participant population and task before transferring the findings.

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

Abstract Objective The rapid emergence of generative artificial intelligence (GAI) in higher education necessitates redesign of learning activities and assessments to uphold academic integrity and foster AI literacy. This article presents a structured approach to developing educational strategies that mitigate GAI misuse while enhancing students’ understanding of GAI, with a focus on collaborative faculty engagement and curricular adaptation in physiotherapy education. Methods Using the Quality Implementation Framework (QIF), we conducted a comprehensive review of all courses within a Swedish physiotherapy program employing a problem-based learning (PBL) model. Faculty-wide, time-bound development initiatives were implemented, including targeted AI literacy training. A student survey was conducted to assess GAI usage patterns and perceptions. Results Assessment formats were adapted to emphasize clinical reasoning and critical thinking, reducing opportunities for GAI misuse. Standardized guidelines on acceptable GAI use were integrated across all courses. The survey results 2 months after implementation indicated diverse usage patterns: 13% of students reported daily use of GAI, while 24% had never used it. Additionally, 42% felt adequately informed about GAI. Faculty AI literacy and confidence improved through structured group work and feedback, supporting the integration of AI-related tasks into the curriculum. Conclusions The systematic approach using QIF and PBL, expert support, faculty champions, problem-solving strategies, and feedback, enabled meaningful curricular changes within 4 months. The variability in student GAI use underscores the need for equitable AI literacy education. This approach not only reduced the risk of GAI misuse but also enhanced faculty preparedness, offering a scalable model for other health sciences programs. Keywords: faculty development, detection and prevention, plagiarism, AI literacy, clinical reasoning

What kind of evidence is this?

Supporting AI learning science · Evidence synthesis

Stage: Higher education; Adult & professional learning. 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 setting for this GAI initiative was a Swedish physiotherapy program, using problem-based learning (PBL) which is a student-centered pedagogical approach, where the students learn by analyzing authentic problems.14,15 Typically conducted in small groups, PBL is facilitated by a tutor who guides the learning process rather than delivering direct instruction. This method facilitates the development of domain-specific knowledge, professional competence, collaboration, problem-solving abilities, critical thinking, and independent learning. Through active inquiry and peer interaction, students are encouraged to take ownership of their learning, reflect on their reasoning, and apply theoretical concepts to practical scenarios. 16

Limitations and uncertainty · source passage

A core learning objective in physiotherapy education is the development of clinical reasoning (CR) to enable informed decisions and person-centered actions. 6 Strengthening CR is crucial for reducing diagnostic errors and improving timely diagnoses. 7 Best practices in teaching, learning, and assessment are vital to support this skill. 8 Overreliance on GAI in medical education poses a risk of declining critical thinking and clinical decision-making skills. 9 Furthermore, although ChatGPT-generated responses to CR questions may appear comprehensive, they frequently lack causal reasoning and demonstrate limited cognitive depth. It is essential for students to recognize these limitations and develop more effective strategies for engaging with GAI, including refining their prompting techniques. 10 This highlights the need to revise pedagogical approaches and assessment designs to ensure they continue to support learning objectives, particularly in CR and critical thinking. 9

Design the system before the pilot

Use this study to inform a learning mechanism or implementation question. It is not direct evidence that autonomous agents improve learning. Keep the proposed agent behavior separate from what the source actually tested.

Give feedback on the learner’s reasoning, then fade hints. Record whether the learner can complete the next task without that scaffold.
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.

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

Yvonne Lindbäck; Karin Valeskog; Karin Schröder; Sofi Sonesson. Structured Development of Learning and Assessment Tasks to Prevent Generative AI Misuse and Enhance AI Literacy in the Faculty in Physiotherapy Education. Journal of Medical Education and Curricular Development (2025-01-01). https://doi.org/10.1177/23821205251378794

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.