Artificial Intelligence (AI) literacy questionnaire with confirmatory factor analysis

Tsz Kit NG, Wenjie WU, Jac Ka Lok LEUNG, Samuel Kai Wah CHU

Research output: Chapter in Book/Report/Conference proceedingChapters

15 Citations (Scopus)

Abstract

In recent years, schools started to incorporate artificial intelligence (AI) into computer science/STEAM curricula. However, few validated measurements have been designed to examine how secondary students develop AI literacy and perceive their learning outcomes. AI literacy has been measured from students' knowledge and skill acquisition, and behavior and attitudes. This research aims to develop and validate an instrument to assess AI literacy for secondary students. A questionnaire with 25 items measured in a 5-point Likert scale was created. In a pilot study, the questionnaire was administered to a sample of 363 secondary school students from two different schools in Hong Kong. Confirmatory factor analysis was conducted and grouped into six factors: (1) intrinsic motivation, (2) self-efficacy, (3) behavioral intention, (4) behavioral engagement, (5) know and understand, and (6) use and apply AI. The questionnaire showed a good fit model to support internal consistency reliability in most of the factors, with Cronbach's Alpha levels ranging from.58 to.88. A less-parsimonious model was proposed that help educators measure a wider AI literacy skill set with an acceptable model fit, with Cronbach's Alpha levels ranging from.91 to.94 based on affective, behavorial, cognitive and ethical (ABCE) learning framework. Further studies are needed to confirm the factor structure. Copyright © 2023 IEEE.

Original languageEnglish
Title of host publicationProceedings of 2023 IEEE International Conference on Advanced Learning Technologies, ICALT 2023
Place of PublicationUSA
PublisherIEEE
Pages233-235
ISBN (Electronic)9798350300543
DOIs
Publication statusPublished - 2023

Citation

Ng, D. T. K., Wu, W., Leung, J. K. L., & Chu, S. K. W. (2023). Artificial Intelligence (AI) literacy questionnaire with confirmatory factor analysis. In Proceedings of 2023 IEEE International Conference on Advanced Learning Technologies, ICALT 2023 (pp. 233-235). IEEE. https://doi.org/10.1109/ICALT58122.2023.00074

Keywords

  • AI
  • Machine learning
  • AI literacy
  • Psychometric measurement

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