A Theme-Rewriting Approach for Generating Algebra Word Problems
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Abstract (arXiv)
Texts present coherent stories that have a particular theme or overall setting, for example science fiction or western. In this paper, we present a text generation method called it rewriting that edits existing human-authored narratives to change their theme without changing the underlying story. We apply the approach to math word problems, where it might help students stay more engaged by quickly transforming all of their homework assignments to the theme of their favorite movie without changing the math concepts that are being taught. Our rewriting method uses a two-stage decoding process, which proposes new words from the target theme and scores the resulting stories according to a number of factors defining aspects of syntactic, semantic, and thematic coherence. Experiments demonstrate that the final stories typically represent the new theme well while still testing the original math concepts, outperforming a number of baselines. We also release a new dataset of human-authored rewrites of math word problems in several themes.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Oct 2016.
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Citing papers per year: 2022: 3; 2023: 3; 2024: 2; 2025: 2.
10 papers.
- 2024Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?cited by 19
- 2023Learning by Analogy: Diverse Questions Generation in Math Word Problemcited by 18
- 2023World Models for Math Story Problemscited by 11
- 2024MATHWELL: Generating Educational Math Word Problems Using Teacher Annotationscited by 7
- 2023Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Reviewcited by 5
- 2022Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generationcited by 4
- 2025THiNK: Can Large Language Models Think-aloud?cited by 3
- 2022COMPASS: a Creative Support System that Alerts Novelists to the Unnoticed Missing Contentscited by 2
- 2025EDUMATH: Generating Standards-aligned Educational Math Word Problemscited by 1
- 2022OLGA : An Ontology and LSTM-based approach for generating Arithmetic Word Problems (AWPs) of transfer typecited by 0
- 2025EDUMATH: Generating Standards-aligned Educational Math Word Problems8 Oct 2025
- 2025THiNK: Can Large Language Models Think-aloud?26 May 2025
- 2024MATHWELL: Generating Educational Math Word Problems Using Teacher Annotations24 Feb 2024
- 2024Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?31 Jan 2024
- 2023Learning by Analogy: Diverse Questions Generation in Math Word Problem15 Jun 2023
- 2023World Models for Math Story Problems7 Jun 2023
- 2023Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Review23 Jan 2023
- 2022OLGA : An Ontology and LSTM-based approach for generating Arithmetic Word Problems (AWPs) of transfer type22 Nov 2022
- 2022Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation29 Oct 2022
- 2022COMPASS: a Creative Support System that Alerts Novelists to the Unnoticed Missing Contents26 Feb 2022