MathTales: Designing and Studying an AI Agent-Based Story Generation System for Teaching Mathematical Problem Solving to Children

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Authors: K. F. Zhang, Yuqi Niu, Mona Y. Alqassim, Andrina Louise Inglis, Charaka Palansuriya, Aurora Constantin
Cited by: 1
References: 23

Abstract

Mathematical stories, particularly those that incorporate problem-solving, are widely recognised as an effective approach to learning mathematics. By grounding problems in concrete examples, children can gradually develop problem-solving skills as the story unfolds. However, creating such stories typically relies on teachers or professional writers, making it challenging to produce stories for every problem at scale. In this paper, we present MathTales, a multi-agent system that leverages a locally deployed open-source large language model to automatically generate stories to teach children mathematical problems. Through human evaluation, we found MathTales produces reliable mathematical stories in terms of accuracy, relevance, coherence, integration and readability. A study with children and teachers revealed that MathTales-generated stories had a positive impact on engagement, enjoyment, and understanding. Additionally, we analyse teachers’ feedback to identify the pedagogical value of these stories and derive design implications for future mathematical story generation systems that support mathematics teaching and learning.

Fields of Study & Subjects

Artificial Intelligence in Games Intelligent Tutoring Systems and Adaptive Learning AI-based Problem Solving and Planning

Publication details

Journal / source
Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–13
Publication date
13 April 2026
Language
EN