This chapter explores the evolution of data-driven hint generation for intelligent tutoring systems (ITS). The Hint Factory and Interaction Networks have enabled the generation of next-step hints, waypoints, and strategic subgoals from historical student data. Data-driven techniques have also enabled systems to find the right time to provide hints. We explore further potential data-driven adaptations for problem solving based on behavioral problem solving data and the integration of Large Language Models (LLMs).
@article{arxiv.2603.07311,
title = {Data-Driven Hints in Intelligent Tutoring Systems},
author = {Sutapa Dey Tithi and Kimia Fazeli and Dmitri Droujkov and Tahreem Yasir and Xiaoyi Tian and Tiffany Barnes},
journal= {arXiv preprint arXiv:2603.07311},
year = {2026}
}
Comments
Book Chapter in the Encyclopedia of AI in Education