This study aims to investigate the artificial intelligence (AI) literacy levels of pre-service teachers and their views on the use of AI in education. Adopting a mixed-methods approach, the study employed both quantitative and qualitative techniques to ensure comprehensive analysis. The quantitative data were collected using the “Artificial Intelligence Literacy Scale,” while qualitative data were gathered through open-ended questions developed by the researchers. The sample consisted of 323 pre-service teachers from different departments and grade levels at Nigde Omer Halisdemir University Faculty of Education. Statistical analyses, including independent samples t-tests and one-way ANOVA, were used to examine differences in AI literacy levels based on variables such as gender, age, grade level, field of study, parental education level, and use of AI technologies. Content analysis was applied to the qualitative data. The findings revealed that pre-service teachers generally possess high levels of AI literacy. Significant differences were observed based on personal factors such as having AI applications, receiving technology-related education, and using AI in academic tasks. However, no significant differences were found for gender, age, or parental education level. Qualitative findings indicated that pre-service teachers mostly use AI tools for academic purposes, recognize their benefits in terms of time-saving and knowledge access, but also express ethical concerns and the need for critical awareness. The study highlights the importance of embedding AI literacy into teacher education programs to prepare future educators for the digital age.
Building similarity graph...
Analyzing shared references across papers
Loading...
Oğuz Çetin
Niğde Ömer Halisdemir Üniversitesi
Gizem Celen
Niğde Ömer Halisdemir Üniversitesi
Journal of Education in Science Environment and Health
Niğde Ömer Halisdemir Üniversitesi
Building similarity graph...
Analyzing shared references across papers
Loading...
Çetin et al. (Wed,) studied this question.
synapsesocial.com/papers/68ebe3d6becc64ad52fdad8d — DOI: https://doi.org/10.55549/jeseh.850