PIRLS Category-specific Question Generation for Reading Comprehension

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.

Publication Details

Journal
CityU Scholars
Published
2025-02-17
Primary Topic
Text Readability and Simplification
Type
article
Field-Weighted Citation Impact
0.00

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article

PIRLS Category-specific Question Generation for Reading Comprehension

CityU Scholars
Text Readability and Simplification
article

PIRLS Category-specific Question Generation for Reading Comprehension

article en

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.

CityU Scholars
City University of Hong Kong
Quality Education
Openalex Percentile: Top 72%
Text Readability and Simplification
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PIRLS Category-specific Question Generation for Reading Comprehension · CityU Scholars (2025) | TGRS Research Map | TGRS