Exploring digital competence and AI literacy at the tertiary level

This explanatory sequential mixed-method study examined students' Artificial Intelligence (AI) literacy at one of the top universities in Turkey and whether or not their AI literacy levels may significantly correlate with their digital competence. Students' levels of digital competence and AI literacy, and how students' AI usage vary based on their digital competence and AI literacy scorers were investigated. Quantitative data were collected through the Self-Assessment Tool for Digital Competence (DigCompSAT), the Scale for the Assessment of Non-experts' AI Literacy (SNAIL), and a demographic questionnaire. Data from both scales were used to form four case groups, which were identified based on Digital Competence and AI Literacy levels. The students from all departments at the university were invited. 338 students participated in the study. Qualitative data were collected through semi-structured interviews, and 15 students were interviewed. The DigComp Framework and UNESCO AI Competency Framework for Students were used to analyze the qualitative data. The results indicated a significant and positive correlation between students' digital competence and AI literacy levels. The findings showed the dimensions of DigComp seem to be transformed from a system where individuals perform several tasks using digital tools to a structure where AI performs targeted tasks. The findings showed that AI tools can directly perform tasks individuals need to complete or want to perform for daily and academic purposes.