A Theme-Rewriting Approach for Generating Algebra Word Problems
This work addresses the need for engaging educational materials by enabling quick theme customization of math homework for students, though it is incremental as it builds on existing text generation methods.
The paper tackles the problem of generating algebra word problems with different themes while preserving the underlying math concepts, using a two-stage rewriting approach that outperforms baselines in producing thematically coherent stories.
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.