Abstract
Ongoing competency-based assessment has now been adopted within the MChiro programme to better reflect authentic skill development. Traditional Objective Structured Clinical Examinations (OSCEs), often used as one-off end-point assessments, presented challenges including inter-observer variance and student performance-related anxiety (Haviari et al., 2024; Martin & Naziruddin, 2020). By transitioning to continuous, reflective, and inclusive methods of assessing clinical competence, the programme aims to empower students, enhance their confidence, and better support diverse learning needs (Lane & Roberts, 2022).
Session Aims:
• Harness live opinions of academics and students through panel discussion.
• Explore the transition from traditional practical assessment styles to skill-based competencies.
• Demonstrate the use of AI feedback through VEOTM.
• Showcase how the Virtual Learning Environment (VLE) enhances feedback and student experience.
Modules were broken into key competency areas. Students recorded their own clinical examinations on campus during self-directed learning time and uploaded them to VEOTM for self-reflection and academic feedback. AI-powered tagging and analytics within VEOTM supported structured, outcome-aligned feedback. Academic staff then reviewed videos, reflections, and provided focused feedback via the VLE, supporting personalised learning and self-regulated progress.
Seven modules across years 1–4 now include clinical competencies as core assessment components, with 40 competencies identified throughout the MChiro programme. Reported academic benefits included increased student engagement and improved feedback quality. Challenges included onboarding students to VEOTM, time demands for video review, and the need for clear student guidance.
This inclusive and reflective assessment model shows promise for empowering learners and developing confident, competent practitioners. Further research into student perspectives will be undertaken through focus group interviews and an open-ended questionnaire, following ethical approval.
Session Aims:
• Harness live opinions of academics and students through panel discussion.
• Explore the transition from traditional practical assessment styles to skill-based competencies.
• Demonstrate the use of AI feedback through VEOTM.
• Showcase how the Virtual Learning Environment (VLE) enhances feedback and student experience.
Modules were broken into key competency areas. Students recorded their own clinical examinations on campus during self-directed learning time and uploaded them to VEOTM for self-reflection and academic feedback. AI-powered tagging and analytics within VEOTM supported structured, outcome-aligned feedback. Academic staff then reviewed videos, reflections, and provided focused feedback via the VLE, supporting personalised learning and self-regulated progress.
Seven modules across years 1–4 now include clinical competencies as core assessment components, with 40 competencies identified throughout the MChiro programme. Reported academic benefits included increased student engagement and improved feedback quality. Challenges included onboarding students to VEOTM, time demands for video review, and the need for clear student guidance.
This inclusive and reflective assessment model shows promise for empowering learners and developing confident, competent practitioners. Further research into student perspectives will be undertaken through focus group interviews and an open-ended questionnaire, following ethical approval.
| Original language | English |
|---|---|
| Pages | 24-25 |
| Number of pages | 2 |
| Publication status | Published - 1 Jul 2025 |
| Event | LSBU Teaching and Learning Conference 2025 - LSBU, London, United Kingdom Duration: 1 Jul 2025 → 1 Jul 2025 |
Conference
| Conference | LSBU Teaching and Learning Conference 2025 |
|---|---|
| Country/Territory | United Kingdom |
| City | London |
| Period | 1/07/25 → 1/07/25 |