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Enhancing reflective practice with ChatGPT: A new approach to assignment design.
Anita Samuel1, Michael Soh2, Eulho Jung1
1Department of Health Professions Education, Uniformed Services University of Health Sciences, Bethesda, MD, USA.
AI tools like ChatGPT can create effective reflective practice assignments in health professions education, improving student performance and reducing faculty workload. This approach enhances clarity and structure in educational assessments.
Area of Science:
- Health Professions Education
- Educational Technology
- Artificial Intelligence in Education
Background:
- Reflective practice (RP) is crucial for professional growth but often lacks clear purpose and guidance.
- Designing effective RP assignments is time-consuming and requires specific faculty expertise.
- This study addresses challenges in creating scaffolded RP assignments and reducing faculty workload.
Purpose of the Study:
- To utilize ChatGPT 4o for designing reflective practice assignments in health professions education (HPE).
- To apply the Transparent Assessment Framework (TAF) in guiding the AI-assisted assignment design.
- To reduce faculty workload associated with creating comprehensive RP assignments.
Main Methods:
- A four-step process was employed to facilitate the AI-driven design of RP assignments.
- ChatGPT 4o was prompted to generate assignment structures, which were then refined for specific courses.
- The Transparent Assessment Framework (TAF) served as a guiding principle for assignment development.
Main Results:
- Pilot study in three graduate HPE courses demonstrated improved assignment clarity, structure, and student performance.
- Faculty preparation time for assignment design was significantly decreased.
- AI-assisted design offers a scalable solution for creating effective educational assessments.
Conclusions:
- AI tools can effectively support the creation of scaffolded reflective practice assignments in HPE.
- This method enhances educational quality while optimizing faculty resources.
- Future research should explore student feedback and AI-generated assignments for medical students.
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