An LLM-Guided Tutoring System for Social Skills Training
This addresses the need for more effective social skills training for students, though it appears incremental as it builds on existing intelligent tutoring systems with LLM integration.
The paper tackles the problem of insufficient traditional classroom training for social skills by introducing a framework that uses large language models to dynamically design realistic scenarios for student rehearsal and feedback, enabling instructors to co-create scenarios without technical skills and generating new branches in real time.
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 do not fit the student's response.