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Towards Automatic Tutoring of Custom Student-Stated Math Word Problems

Arnau-González, Pablo; Serrano-Mamolar, Ana; Katsigiannis, Stamos; Arevalillo-Herráez, Miguel

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Authors

Pablo Arnau-González

Ana Serrano-Mamolar

Miguel Arevalillo-Herráez



Abstract

Math Word Problem (MWP) solving for teaching math with Intelligent Tutoring Systems (ITSs) faces a major limitation: ITSs only supervise pre-registered problems, requiring substantial manual effort to add new ones. ITSs cannot assist with student-generated problems. To address this, we propose an automated approach to translate MWPs to an ITS’s internal representation using pre-trained language models to convert MWP to Python code, which can then be imported easily. Experimental evaluation using various code models demonstrates our approach’s accuracy and potential for improvement.

Citation

Arnau-González, P., Serrano-Mamolar, A., Katsigiannis, S., & Arevalillo-Herráez, M. (2023, July). Towards Automatic Tutoring of Custom Student-Stated Math Word Problems. Presented at International Conference on Artificial Intelligence in Education (AIED), Tokyo, Japan

Presentation Conference Type Conference Paper (published)
Conference Name International Conference on Artificial Intelligence in Education (AIED)
Start Date Jul 3, 2023
End Date Jul 7, 2023
Acceptance Date Apr 2, 2023
Online Publication Date Jun 30, 2023
Publication Date 2023
Deposit Date Apr 12, 2023
Publicly Available Date Jul 1, 2024
Publisher Springer
Volume 1831
Pages 639-644
Series Title Communications in Computer and Information Science
Book Title AIED 2023: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky
DOI https://doi.org/10.1007/978-3-031-36336-8_99
Public URL https://durham-repository.worktribe.com/output/1134170
Publisher URL https://link.springer.com/conference/aied

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