An LLM-Guided Tutoring System for Social Skills Training

Abstract

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.

Cite

Text

Guevarra et al. "An LLM-Guided Tutoring System for Social Skills Training." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35353

Markdown

[Guevarra et al. "An LLM-Guided Tutoring System for Social Skills Training." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/guevarra2025aaai-llm/) doi:10.1609/AAAI.V39I28.35353

BibTeX

@inproceedings{guevarra2025aaai-llm,
  title     = {{An LLM-Guided Tutoring System for Social Skills Training}},
  author    = {Guevarra, Michael and Bhattacharjee, Indronil and Das, Srijita and Wayllace, Christabel and Epp, Carrie Demmans and Taylor, Matthew E. and Tay, Alan},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {29643-29645},
  doi       = {10.1609/AAAI.V39I28.35353},
  url       = {https://mlanthology.org/aaai/2025/guevarra2025aaai-llm/}
}