Perceived Digital Competence and Basic AI Understanding in Relation to Academic Use Among Teacher Education Students

Abstract

Artificial intelligence has become increasingly present in education, offering tools that can support teaching and learning while also raising concerns regarding their effective, ethical, and responsible use. This study examined primary teacher education students' perceived digital competence and basic understanding of artificial intelligence, their reported use of artificial intelligence tools for studying, and the relationship between these constructs. The research was conducted using an anonymous online survey with 82 students enrolled in primary teacher education programs in Serbia. Exploratory factor analysis supported a two-factor structure comprising Perceived Digital Competence and Basic Artificial Intelligence Understanding and Use of Artificial Intelligence Tools in Studying, which together explained 54.46% of the total variance. Both factors demonstrated satisfactory internal consistency, with Cronbach's alpha coefficients of 0.884 and 0.874, respectively. Participants reported relatively high perceived digital competence and basic artificial intelligence understanding (𝑀 = 6.24, 𝑆𝐷 = 1.18) but lower use of artificial intelligence tools in studying (𝑀 = 3.59, 𝑆𝐷 = 1.83) on an eight-point Likert-type scale. No statistically significant differences were found across years of study for either factor (𝜌 = 0.850 and 0.104, respectively), and the association between the first factor and tool use was weak and not statistically significant (𝜌 = 0.162, 𝑝 = 0.145). These findings indicate that perceived digital competence and basic artificial intelligence understanding should be considered separately from academic use and suggest that primary teacher education programs should provide structured opportunities for future primary teachers to apply artificial intelligence tools critically, ethically, and pedagogically in authentic academic and teaching-related activities.