Data-Driven Hints in Intelligent Tutoring Systems

Fuente: arXiv
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Main Authors: Tithi, Sutapa Dey, Fazeli, Kimia, Droujkov, Dmitri, Yasir, Tahreem, Tian, Xiaoyi, Barnes, Tiffany
Format: Preprint
Published: 2026
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author Tithi, Sutapa Dey
Fazeli, Kimia
Droujkov, Dmitri
Yasir, Tahreem
Tian, Xiaoyi
Barnes, Tiffany
author_facet Tithi, Sutapa Dey
Fazeli, Kimia
Droujkov, Dmitri
Yasir, Tahreem
Tian, Xiaoyi
Barnes, Tiffany
contents 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).
format Preprint
id arxiv_https___arxiv_org_abs_2603_07311
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Data-Driven Hints in Intelligent Tutoring Systems
Tithi, Sutapa Dey
Fazeli, Kimia
Droujkov, Dmitri
Yasir, Tahreem
Tian, Xiaoyi
Barnes, Tiffany
Artificial Intelligence
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).
title Data-Driven Hints in Intelligent Tutoring Systems
topic Artificial Intelligence
url https://arxiv.org/abs/2603.07311