Concept Mapping, Chatbots and GIS: Re-engineering Community-Medicine Teaching for Gen-AI Learners
The implementation of artificial intelligence (AI) in the study of community medicine presents a possibility to connect to the medical students of Generation Z who tend to study the visual and engaging information. Concept maps help organize information and improve retention through collaborative visualization. Chatbots simulate patient interactions, allowing students to practice skills like history-taking. GIS enables visualization of disease patterns and geographical risk factors. These tools combine for "triad cycles": concept mapping, chatbot exploration, and GIS data anchoring, integrating into existing field visits without extra classes. Free resources like Cmap, sandboxed GPT chat, and QGIS keep costs low. Safeguards include data privacy, verifying chatbot outputs, and providing offline GIS guides. Assessment can include concept maps, chatbot reflections, and GIS storyboards. The goal is to modernize community medicine, transforming students into systems thinkers prepared for India's public health challenges.
Authors
- Urvish Joshi (ORCID: https://orcid.org/0000-0002-9204-5614)
Institutions
- B.J. Medical College (IN)
Publication Details
- Published
- 2025-08-03
- DOI
- https://doi.org/10.63486/jpchr.25080301
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00