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The Use of ChatGPT for Reading Test Development and Validation: Two Case Studies

2025·0 ZitationenOpen Access
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2025

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Abstract

This chapter explores the application of ChatGPT in reading test development and validation through two case studies. Study 1 evaluates ChatGPT’s ability to estimate item difficulty and discrimination for a reading comprehension test without response data from test takers. Results show that ChatGPT estimated item difficulty with moderate agreement with empirical data, though it struggled with estimating item discrimination. Study 2 investigates ChatGPT's capacity to answer multiple-choice reading items without access to passages, revealing correct response rates that notably surpassed two human participants. These findings indicate ChatGPT’s potential as a tool for facilitating reading test development and validation, particularly in providing early-stage validity evidence when pilot data are unavailable. Future studies should explore diverse test formats and refine AI methodologies to enhance their utility in measurement practice.

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Artificial Intelligence in Healthcare and EducationIntelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics
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