FAIMER GROUP 2 · NOVEMBER 2026

Using AI as a catalyst for interprofessional learning

A mentored, human-first learning journey for 2025 and 2026 fellows. This file works offline: it saves work in this browser and can export a portable learner record.

1–30 November 20262–3 hours each weekFictional cases onlyHuman accountability

Start here

Complete this short set-up before working through the module. Do not enter names, emails, phone numbers, patient details, or identifiable workplace information.

Privacy and safety boundary. This module is educational; it does not provide clinical advice. Any AI use must follow current institutional policy. Public AI tools must never receive identifiable or restricted information.
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completion evidence recorded

Your completion pathway

Work through the required evidence. A facilitator-verified certificate is unlocked only after the full record is complete.

    What you will do

    1–2 NovPre-assessment3–7 NovActivity 1 · compare a human and AI response8–15 NovActivity 2 · case-based teamwork16–22 NovActivity 3A · intervention design23–27 NovActivity 3B · sustainability appraisal28–30 NovReflection, post-assessment and feedback

    Learning outcomes

    Pre- and post-assessment

    Complete the knowledge items before the module and again at the end. Your score is for reflection; the facilitator uses aggregate, de-identified results.

    Knowledge check

    Confidence check

    Rate each statement from 1 (strongly disagree) to 5 (strongly agree).

    Activity 1 · Compare before you trust

    3–7 November · Individual · 45–60 minutes · Moderators: Siddalingaiah H S and Queen Alice

    Task: draft a human response first, then compare it with an AI output or the supplied sample. Your assessed skill is judgement, not access to a tool.

    Fictional vignette

    Mrs A, an older adult, has had two recent falls. She takes multiple medicines, worries about losing independence, and lives with a daughter who is exhausted by caregiving. A follow-up appointment is delayed because transport is unreliable. What should an interprofessional team notice and do?

    Know · Feel · Do

    Safe prompt pattern

    Role + task + boundary + verification. Example: “Act as a learning stimulus for an interprofessional student team. Using only this fictional, de-identified scenario, list questions the team should ask, possible role contributions and uncertainty to verify. Do not provide clinical advice or invent sources.”

    AI transparency

    Five-part audit

    CriterionSelf-rating 1–4
    Safe, bounded and transparent AI use
    Interprofessional reasoning and role integration
    Critical comparison and verification
    Person-centred, equitable next action

    Activity 2 · Build one shared plan

    8–15 November · Group · 90–120 minutes · Moderators: Faisal Hassan, Anand Bhosale and Purohit Saraswathi

    Choose or confirm your fictional case

    Team roles

    Rotate or assign: chair, equity monitor, evidence checker, AI auditor and rapporteur. Every profession speaks before synthesis begins.

    Audit the group’s AI plan or supplied sample

    CriterionSelf-rating 1–4
    Person-centred reasoning
    Role integration and communication
    Critical AI audit, safety and equity
    Feasible shared action and monitoring
    Clear disclosure and revision trace

    Activity 3A · Design an AI-supported IPE intervention

    16–22 November · Group project · 120–150 minutes · Moderators: Sidarth and Vrinda J Bhat

    Design a small, testable learning intervention—not a technology procurement proposal. The AI role must remain bounded and include a no-AI fallback.

    Proposal quality check

    CriterionSelf-rating 1–4
    Need and stakeholders
    IPE mechanism and learning alignment
    Responsible, equitable AI design
    Feasibility, evaluation and next test

    Activity 3B · Sustainability appraisal

    23–27 November · Individual · 60–75 minutes · Moderators: Sidarth and Vrinda J Bhat

    Educational rating only. This 1–4 rating is informed by the NHS Sustainability Model but is not its official weighted score. Rate using evidence, identify the weakest factor, then name one owned action.

    Close the loop

    28–30 November · Reflection, post-assessment and feedback · Moderators: Harini Priya and Jasmeen Shaikh

    Monthly feedback

    Completion confirmation. These confirmations are a local checklist. The facilitator must review submitted work and allocate the certificate number before the learner prints the final certificate.

    Certificate generator

    Complete the local certificate details after the facilitator’s review. This tool prints a certificate; it does not replace the official completion register.

    Certificate locked: complete the module evidence and facilitator verification.
    FAIMER GROUP 2 · NOVEMBER 2026

    Certificate of completion

    This certifies that

    Participant name

    has successfully completed the mentored learning web module Using AI as a catalyst for interprofessional learning, including the required assessments, individual and group learning activities, sustainability appraisal, reflection and feedback.

    Module period: 1–30 November 2026

    Certificate numberTo be assigned
    Verified byTo be assigned
    Issue dateTo be assigned
    Implementation roles and sources

    Faculty in charge: Dr Sushma Prabhat. Record keeping: Sidarth, Anand Bhosale and Siddalingaiah H S. Summary: Queen Alice and Jasmeen Shaikh by 5 December 2026.

    Learning framework references: WHO Framework for Action on Interprofessional Education and Collaborative Practice; IPEC Core Competencies Version 3 (2023); UNESCO Guidance for Generative AI in Education and Research (2023); NHS Sustainability Model.

    Completion record: pre + post assessment, Activities 1, 2, 3A and 3B, reflection, feedback, and AI disclosure where applicable. Submit required work through the approved learning platform.

    References and resources

    Open the source publications, sustainability guide, learner deck and module materials used to build this learning experience.

    How to use these links: start with WHO and IPEC for the learning framework, use UNESCO for responsible AI boundaries, and use the NHS model during Activity 3B.

    Journal articles and methods references

    These references are drawn from the Group 2 research-papers pack. Use the links for further reading; verify final metadata and author order against the publisher record before formal publication.

    1. Hu L, Argus G, Pineda RC, et al. The role of artificial intelligence in enhancing interprofessional education and collaborative practice: a mixed methods scoping review. Journal of Interprofessional Care. 2026;40(2):390–399. DOI 10.1080/13561820.2025.2576241.
    2. Agustina PA, et al. The roles of artificial intelligence in interprofessional healthcare education: a systematic scoping review. Journal of Multidisciplinary Healthcare. 2026. PMID 42703522.
    3. Maphalala MC. Artificial intelligence as a catalyst for self-directed learning in an open and distance e-learning university in South Africa. South African Journal of Education. 2025;45(S1):S1–S13.
    4. Vinci V, Agrati LS, Berardi P, Berardi A. Artificial intelligence as a catalyst for transformative assessment: designing teacher literacy at the crossroads of ethics, pedagogy, and human relationships. Frontiers in Education. 2026;11:1760626.
    5. Guo Y, Lin Z. Generative AI as a catalyst for data-driven learning: efficacy, equity, and engagement in translation education. SAGE Open. 2025;15.
    6. Tricco AC, Lillie E, Zarin W, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Annals of Internal Medicine. 2018;169(7):467–473.
    7. Peters MDJ, et al. JBI Manual for Evidence Synthesis. Adelaide: Joanna Briggs Institute; 2024.
    8. White H, Albers B, Gaarder M, et al. Guidance for producing a Campbell evidence and gap map. Campbell Systematic Reviews. 2020;16:e1125.
    9. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.
    10. O’Cathain A, Murphy E, Nicholl J. The quality of mixed methods studies in health services research. Journal of Health Services Research & Policy. 2008;13(2):92–98.
    11. Yuh C, Cho CH, Lee YM. The AI colleague: reimagining interprofessional collaboration and education in medicine. JMIR Medical Education. 2026;12:e94034.
    Reading route: begin with Hu and Agustina for the AI–IPE evidence base, then use Maphalala, Vinci and Guo for learning, assessment and equity perspectives. Use Tricco, JBI, White, Page and O’Cathain for the research-methods foundation.
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