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Recommendations for Training Faculty in Generative AI Use: Crafting Higher-Order Application Exercises in Team-Based
Deborah Dalmeida1, Nahla Gomaa2, Elizabeth Prabhakar3
1Ross University School of Medicine, St. Michael, Barbados.
The Clinical Teacher
|July 30, 2026
Summary
Artificial intelligence (AI) can streamline the creation of complex application exercises (AEs) for team-based learning (TBL). This approach empowers educators to design engaging, higher-order learning activities aligned with Bloom's taxonomy.
Area of Science:
- Educational Technology
- Pedagogy
- Artificial Intelligence in Education
Background:
- Application exercises (AEs) are crucial for deep learning and engagement in team-based learning (TBL).
- Designing effective AEs presents challenges for educators, including time constraints and alignment with learning objectives.
- Artificial intelligence (AI) offers a potential solution to expedite AE design and enhance their quality.
Purpose of the Study:
- To share knowledge and best practices for using AI to design effective TBL application exercises.
- To empower educators in creating higher-order AEs aligned with Bloom's taxonomy and TBL principles.
- To provide faculty development recommendations for integrating AI into course design for TBL.
Main Methods:
- Educators were trained to use the Task-Role-Audience-Create-Intent (TRACI) framework for prompt engineering.
- AI tools, specifically Anthropic's Claude 4 Sonnet, were utilized for iterative AE design.
- Best practice recommendations were developed based on international workshop experiences and participant feedback.
Main Results:
- AI facilitates the creation of engaging AEs that meet the 4S principles of TBL (significant problem, same problem, specific choice, simultaneous reporting).
- The iterative AI-driven design process allows for the generation of higher-order AEs promoting critical thinking.
- The TRACI framework effectively guided educators in crafting AI prompts for AE development.
Conclusions:
- AI tools, when guided by frameworks like TRACI, can significantly reduce the time and effort required for designing high-quality TBL application exercises.
- Integrating AI into course design is a vital skill for health professions educators in the evolving educational landscape.
- This work provides practical recommendations for faculty development in AI-assisted TBL course design.
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