Artificial Intelligence Literacy and Critical Thinking Among University Students: Moving Beyond Basic Tool Usage

This research explores not only the frequency with which students are using AI tools but also their understanding, evaluation, and critical use of the AI tools within the framework of students' AI literacy in the context of students at the University of Malte-Islamabad, Pakistan. A quantitative, correlational research design is used in the study, and samples consisting of around 300 students of undergraduate and postgraduate studies from three institutions (Air University, PMAS-Arid Agriculture University (AAUR), and Allama Iqbal Open University (AIOU)) were randomly selected using the stratified sampling method. The data were collected through a three-part questionnaire instrument: a five-point Likert AI Literacy Scale to assess the level of AI Knowledge, technical understanding, evaluation, and ethical awareness, and an adapted Critical Thinking Scale to measure analysis, evaluation, inference, and interpretation. The content validity was assessed by experts and a pilot study, and internal consistency was measured by Cronbach's alpha. The data were tested for mediation of AI literacy between the usage of AI traces and critical thinking by descriptive statistical analysis, Pearson product-moment correlation, multiple regression, and mediation analysis in SPSS. The illustrative results presented here indicate that the students in the university have moderate-high levels of AI literacy and that a moderate-high correlation can be found between their AI literacy scores and their critical thinking scores, which means that the influence of the AI literacy scores is twice as strong as the influence of the frequency of using AI tools on the critical thinking scores. Literacy is a key variable in the study, not the use of, or access to, AI.The patterns do not strengthen the argument of the study, which is that literacy is a driver of higher-order thinking outcomes, but not the use of, or access to, AI. It offers evidence from a higher education context that is not adequately reflected in the literature and implications for curriculum designers, faculty, and policymakers who are interested in responsibly incorporating AI in the higher education context. Prospects for building skills in AI include embedding AI-literacy courses, ethics training, and AI-thinking activities into curricula of higher education institutions.