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Empowering Educators to Build AI Chatbots in Health Professions Education: Tutorial on a No-Code Design Workflow
Charlene Xing Le Goh1, Eugene Wang1, Juanita S M Kong2
1Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
JMIR Medical Education
|August 14, 2026
Summary
Educators can now build AI teaching tools without coding using a practical workflow for generative AI chatbots. This method ensures pedagogical grounding and ethical deployment for scalable, interactive learning experiences.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
- Health Professions Education
Background:
- Artificial intelligence (AI) is rapidly integrating into clinical practice, outpacing health professions education.
- Educators desire AI-based teaching tools but lack structured methods for their development and implementation.
- Generative AI chatbots offer scalable, interactive learning opportunities without requiring programming expertise.
Purpose of the Study:
- To provide a practical, platform-agnostic workflow for educators to design and deploy no-code AI chatbots.
- To ground AI chatbot design in pedagogical principles and established learning mechanisms.
- To offer guidance on ethical considerations, risks, and curriculum integration for AI tools.
Main Methods:
- A five-section workflow covering purpose definition, behavior configuration, learner experience refinement, realism enhancement, and ethical deployment.
- Utilizing the technological pedagogical content knowledge framework and learning mechanisms like deliberate practice and simulation-based learning.
- Illustrating design steps with real-world examples like the Virtual Integrated Patient and Depression Avatars projects.
Main Results:
- A structured, step-by-step method for creating no-code AI chatbots for educational purposes.
- Emphasis on pedagogical grounding over purely technical considerations in AI tool design.
- Identification of key risks, including hallucination, automation bias, and data privacy, with a governance checklist.
Conclusions:
- No-code AI chatbots present a feasible and accessible approach for educators to develop interactive learning tools.
- The provided workflow is discipline-agnostic and transferable across higher education settings.
- Further rigorous, multi-institutional evaluation is necessary to validate educational effectiveness.
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