From Inquiry to Simulation: Leveraging ChatGPT and Chatbots for Dilemma-Based Learning in Healthcare Education

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Health Management

Background:

• The increasing integration of artificial intelligence (AI) in healthcare necessitates enhanced AI literacy among future professionals.
• Traditional pedagogical approaches may not adequately prepare healthcare management students for an AI-driven landscape.

Purpose of the Study:

• To examine a multi-stage learning framework integrating dilemma-based learning with AI tools (ChatGPT, chatbot development) for undergraduate healthcare management students.
• To advance AI literacy, critical thinking, and decision-making skills in this cohort.

Main Methods:

• A qualitative thematic analysis of 71 students' reflective journals.
• Implementation of a structured, multi-stage learning intervention involving AI tools and dilemma-based learning.
• Iterative engagement including prompt refinement, chatbot development, and AI-driven simulations.

Main Results:

• Four themes emerged: Learning Through Questioning, Learning Through Teaching and Prompt Refinement, Learning Through Simulation, and Struggles and Successes.
• AI-driven learning fostered prompt engineering, critical thinking, and problem-solving skills.
• Students initially faced challenges with prompt formulation and chatbot dialogue but improved through iterative learning.

Conclusions:

• Integrating AI literacy and chatbot development into healthcare education is crucial for preparing students to manage complex dilemmas.
• The AI-enhanced learning intervention effectively improved students' analytical skills and ability to engage with AI-driven simulations.
• This study provides insights into adapting medical education for the AI era.