Research Article

Pre-service teachers’ AI literacy: An exploratory study of predecessor literacies and personal characteristics predictors

Andreja Istenič 1 2 3 * , Tina Lekan Kraševec 1 , Žiga Turk 2 , Maja Lebeničnik 1
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1 Faculty of Education, University of Primorska, Koper, SLOVENIA2 Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, SLOVENIA3 Department of Philosophy, Samarkand State University named after Sharof Rashidov, Samarkand, UZBEKISTAN* Corresponding Author
Contemporary Educational Technology, 18(4), October 2026, ep702, https://doi.org/10.30935/cedtech/19641
Published: 20 October 2026
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ABSTRACT

Literacy is embedded in social practices that adopt socially constructed technologies. In the 20th century, the invention of the computer facilitated information literacy and computational thinking. Media literacy emerged alongside the development of media. In the 21st century, the accessibility of artificial intelligence (AI)-powered chatbots using conversational language has expanded significantly, creating a need for their integration in education. AI literacy is being studied within frameworks similar to those of its predecessors, requiring conceptualization and differentiation from related literacy concepts. As of 2025, teacher education regarding AI literacy has been identified as an under-researched area. This article examines AI literacy through the lens of pre-service teachers’ literacy competencies that will shape the literacy practices of future generations. During their own schooling, the current generation of prospective teachers encountered information, digital, and media literacy, as well as computational thinking; these are analyzed here as predictors of AI literacy, measured using the scale for the assessment of non-experts’ artificial intelligence literacy (SNAIL) instrument. Personality traits and mindset are also investigated as predictors of the prospective teachers’ professional competence. The study was conducted in 2024/25 with a sample of pre-service teachers. The research questions are: What is the structure of AI literacy in the sample? To what extent can AI literacy be predicted by components of information literacy? How much of AI literacy can be explained by various established technology-related literacies? To what extent do personality and mindset contribute to predicting AI literacy? The findings confirmed a two-factor solution for SNAIL, comprising technical understanding and critical application. Student perception of information literacy skills proved accurate in predicting the critical application of AI. In addition to information literacy, predictors included the media production subscale of media literacy and mindset. Technical understanding of AI was predicted by the media production subscale, the computational thinking subscales algorithmic thinking and cooperativity, and the personality trait of agreeableness. Establishing AI literacy as an essential teacher competency requires thorough research into AI’s educational impacts and strict alignment with pedagogical goals. Navigating the ethical and moral dimensions of AI usage provides the necessary foundation for this literacy. Consequently, training programs can intentionally foster AI competence by merging specialized literacy modules with algorithmic thinking, media production, and growth-mindset interventions.
Keywords: pre-service teachers, artificial intelligence literacy, information literacy, media literacy, computational thinking, personality traits, growth mindset

CITATION (APA)

Istenič, A., Lekan Kraševec, T., Turk, Ž., & Lebeničnik, M. (2026). Pre-service teachers’ AI literacy: An exploratory study of predecessor literacies and personal characteristics predictors. Contemporary Educational Technology, 18(4), ep702. https://doi.org/10.30935/cedtech/19641

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