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AI Literacy in Higher Education: A Systematic Approach to Questionnaire Development and Validation

AI Literacy in Higher Education: A Systematic Approach to Questionnaire Development and Validation
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Author(s): Maria Ranieri (University of Florence, Italy), Gabriele Biagini (University of Florence, Italy)and Stefano Cuomo (University of Florence, Italy)
Copyright: 2025
Volume: 16
Issue: 1
Pages: 25
Source title: International Journal of Digital Literacy and Digital Competence (IJDLDC)
Editor(s)-in-Chief: Tonia De Giuseppe (University of Benevento-Giustino Fortunato, Italy)
DOI: 10.4018/IJDLDC.388469

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Abstract

This paper presents the development, refinement, and validation of the Critical Artificial Intelligence Literacy Scale, an instrument designed to measure artificial intelligence literacy across four dimensions: knowledge-related, operational, critical, and ethical. The initial version of the questionnaire, based on a robust theoretical framework and expert consultation, included 40 items and was tested with 57 doctoral students. It demonstrated strong psychometric properties (comparative fit index = 0.946, Tucker-Lewis index = 0.92) but showed limitations such as item redundancy (α = 0.947) and low performance of general items. To address these issues, the questionnaire was refined to a concise 24-item version. The revised instrument was evaluated using a sample of 314 first-year student teachers. Exploratory and confirmatory factor analyses confirmed a four-factor structure, with each dimension demonstrating strong reliability (Cronbach's alpha ranging from 0.838 to 0.912) and excellent model fit indices (comparative fit index = 0.960, root mean square error of approximation = 0.0441). The results validate the Critical Artificial Intelligence Literacy Scale as a reliable and efficient tool for assessing artificial intelligence literacy in educational settings.

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