article · Computers and Education Open
Evaluating artificial intelligence literacy among pre-service teachers is increasingly important as classroom technologies evolve. A quantitative study of 529 pre-service teachers at a Nigerian university assessed multiple dimensions of artificial intelligence literacy using structural equation modelling. The results demonstrate that a strong understanding of artificial intelligence significantly predicts positive outcomes in artificial intelligence use, detection, ethics, creation, and problem-solving. In contrast, artificial intelligence knowledge showed no correlation with emotion regulation, and active use of artificial intelligence did not enhance the ability to detect artificial intelligence. Furthermore, the analysis revealed a trade-off between the application and creation of artificial intelligence tools, while confirming a direct link between artificial intelligence creation and problem-solving skills. These outcomes highlight the foundational importance of technological knowledge in teacher training programmes.
As artificial intelligence becomes common in education, teachers require specific competencies to guide learners safely and effectively. Understanding how artificial intelligence knowledge influences practical skills, ethics, and detection allows teacher training institutions and policymakers to design targeted curricula, ensuring future educators can balance using existing tools with developing creative solutions in the classroom.
The findings can inform the design of teacher professional development programmes, instructional software, and curriculum frameworks for education providers and policymakers. While the research is early-stage academic inquiry based on survey data, the identified skill relationships provide empirical guidance for educational technology developers creating training modules and assessment tools aimed at improving artificial intelligence competence in higher education.
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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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DOI: 10.1016/j.caeo.2024.100179
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