Lifelong learning predicting artificial intelligence literacy: A hierarchical multiple linear regression analysis

Authors : Aylin Kirişçi Sarıkaya

Pages : 455-482

View : 36 | Download : 56

Publication Date : 2025-10-01

Article Type : Research Paper

Abstract :This study investigated the relationship between preservice teachers’ lifelong learning (LLL) tendencies and their artificial intelligence (AI) literacy. It aimed to understand whether a more substantial commitment to LLL contributes to developing essential AI competencies among future educators. A total of 318 preservice teachers from various universities and departments in Turkiye, selected through convenience sampling, participated in the study. The results revealed significant positive correlations between LLL tendencies and overall AI literacy, as well as with each AI literacy subdimension, namely awareness, usage, evaluation, and ethics. The results suggested that preservice teachers with higher LLL tendencies tend to be more AI literate. Hierarchical multiple linear regression analysis was utilized to investigate whether demographic variables- gender, year of study, ICT competency, and AI tool usage- and LLL tendencies predicted AI literacy. ICT competency was found to be a significant predictor in the first model, and in the second model, LLL significantly improved the predictive power. As a result, ICT competency and LLL showed statistically significant predictive effects on preservice teachers’ AI literacy. These findings indicate the importance of improving preservice teachers’ LLL tendency to enhance AI literacy in their professional learning.
Keywords : Mesleki öğrenme, Yapay zekâ, Yaşam boyu öğrenme, Hizmet öncesi öğretmenler

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