Personality-aware Student Simulation for Conversational Intelligent Tutoring Systems

arXiv:2404.06762v1 Announce Type: new
Abstract: Intelligent Tutoring Systems (ITSs) can provide personalized and self-paced learning experience. The emergence of large language models (LLMs) further enables better human-machine interaction, and facilitates the development of conversational ITSs in various disciplines such as math and language learning. In dialogic teaching, recognizing and adapting to individual characteristics can significantly enhance student engagement and learning efficiency. However, characterizing and simulating student's persona remain challenging in training and evaluating conversational ITSs. In this work, we propose …

abstract arxiv conversational cs.cl cs.hc development emergence experience human human-machine interaction intelligent language language models large language large language models llms machine math personality personalized simulation systems teaching tutoring type