ChatGPT as a Math Questioner? Evaluating ChatGPT on Generating Pre-university Math Questions
Phuoc Pham Van Long, Duc Anh Vu, Nhat M. Hoang, Xuan Long Do, Anh Tuan, Luu

TL;DR
This paper evaluates ChatGPT's ability to generate pre-university math questions, analyzing its performance in different settings and introducing a new dataset from curriculum crawling to assess its potential as an educational question generator.
Contribution
It is the first comprehensive analysis of ChatGPT's effectiveness in generating math questions across various educational levels and settings, supported by a new curriculum dataset.
Findings
ChatGPT performs well in context-aware question answering benchmarks.
ChatGPT can generate diverse math questions for different curriculum levels.
The study introduces TopicMath, a new dataset from 121 topics and 428 lessons.
Abstract
Mathematical questioning is crucial for assessing students problem-solving skills. Since manually creating such questions requires substantial effort, automatic methods have been explored. Existing state-of-the-art models rely on fine-tuning strategies and struggle to generate questions that heavily involve multiple steps of logical and arithmetic reasoning. Meanwhile, large language models(LLMs) such as ChatGPT have excelled in many NLP tasks involving logical and arithmetic reasoning. Nonetheless, their applications in generating educational questions are underutilized, especially in the field of mathematics. To bridge this gap, we take the first step to conduct an in-depth analysis of ChatGPT in generating pre-university math questions. Our analysis is categorized into two main settings: context-aware and context-unaware. In the context-aware setting, we evaluate ChatGPT on existing…
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Taxonomy
TopicsTopic Modeling · Intelligent Tutoring Systems and Adaptive Learning · Text Readability and Simplification
