An LLM-Guided Tutoring System for Social Skills Training

Social skills training targets behaviors necessary for success in social interactions. However, traditional classroom training for such skills is often insufficient to teach effective communication — one-to-one interaction in real-world scenarios is preferred to lecture-style information delivery. This paper introduces a framework that allows instructors to collaborate with large language models to dynamically design realistic scenarios for students to communicate. Our framework uses these scenarios to enable student rehearsal, provide immediate feedback and visualize performance for both students and instructors. Unlike traditional intelligent tutoring systems, instructors can easily co-create scenarios with a large language model without technical skills. Additionally, the system generates new scenario branches in real time when existing options don't fit the student's response.

Authors

• Michael Guevarra Illumia Labs
• Indronil Bhattacharjee New Mexico State University
• Srijita Das University of Michigan - Dearborn
• Christabel Wayllace New Mexico State University
• Carrie Demmans Epp University of Alberta
• Matthew E. Taylor University of Alberta Alberta Machine Intelligence Institute (Amii)
• Alan Tay Illumia Labs

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