Examining artificial intelligence literacy among pre-service teachers for future classrooms

Ayanwale, Musa Adekunle; Adelana, Owolabi Paul; Molefi, Rethabile Rosemary; Adeeko, Olalekan and Ishola, Adebayo Monsur (2024). Examining artificial intelligence literacy among pre-service teachers for future classrooms. Computers and Education Open, 6, article no. 100179.

DOI: https://doi.org/10.1016/j.caeo.2024.100179

Abstract

In the context of global integration and increasing reliance on Artificial Intelligence (AI) in education, evaluating the AI literacy of pre-service teachers is crucial. As future architects of educational systems, pre-service teachers must not only possess pedagogical expertise but also a strong foundation in AI literacy. This quantitative study examines AI literacy among 529 pre-service teachers in a Nigerian university, utilizing structural equation modeling (SEM) for comprehensive analysis. The research explores various dimensions of AI literacy, revealing that a profound understanding of AI significantly predicts positive outcomes in AI use, detection, ethics, creation, and problem-solving. However, no correlation exists between AI knowledge and emotion regulation or the assumption that active AI use enhances AI detection capabilities. The study identifies a trade-off between AI application and creation, emphasizing the ethical considerations intertwined with emotional and persuasive facets of AI use. It also supports the link between AI creation and problem-solving, emphasizing the foundational role of AI knowledge in shaping diverse aspects of AI literacy among pre-service teachers. The findings offer valuable insights for educators, administrators, policymakers, and researchers aiming to enhance AI literacy in pre-service teacher education programs.

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