Year: 2025
Type: conference-paper
Abstract: According to the internationally recognized PIRLS (Progress in International Reading Literacy Study) assessment standards, reading comprehension questions should encompass all four comprehension processes: retrieval, inferencing, integrating and evaluation. This paper investigates whether Large Language Models can produce high-quality questions for each of these categories. Human assessment on a Chinese dataset shows that GPT-4o can generate usable and category-specific questions, ranging from 74% to 90% accuracy depending on the category.
Source: CityU Scholars
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
Funder: City University of Hong Kong
OpenAlex ID: W7014551142
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