Problem
Research questions and friction points this paper is trying to address.
Math Word Problems
visual representations
lower-primary learners
symbolic systems
text-to-image systems
Math2Visual-X: A Modular Framework for Pedagogically Aligned Lower-Primary Math Visuals Generation
🤖 AI Summary
本文提出Math2Visual-X框架，通过结合符号系统与文本到图像技术，解决低年级数学题视觉表示生成难题，实现更广泛覆盖和更强性能。
📝 Abstract
Visual representations can help lower-primary learners understand Math Word Problems, but generating classroom-usable visuals remains difficult. Existing symbolic systems are controllable but limited in coverage, while end-to-end text-to-image systems often fail to satisfy exact mathematical constraints. This paper presents a symbolic visual generation framework for lower-primary MWP generation with broader problem coverage and more scalable asset generation. The framework includes an LLM-based routing layer, three worksheet-oriented generation modules, and two fallback mechanisms for open-world SVG asset acquisition. A human evaluation comparing Math2Visual-X with Stable Diffusion XL, Nano Banana, and GPT Image showed that the proposed method achieved the strongest overall performance. The results indicate that the framework offers a scalable and pedagogically grounded approach for automatic MWP visual generation.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Symbolic Visual Generation
LLM-based Routing Layer
Worksheet-oriented Modules
Fallback Mechanisms
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