An Analysis of AI Literacy Levels and Educational Needs of University Freshmen

This study aims to empirically examine the AI literacy levels and educational needs of university freshmen in response to the increasing importance of AI competencies in an era marked by the widespread adoption of generative artificial intelligence. AI literacy was conceptualized as a multidimensional construct comprising attitudes, knowledge, and skills, and further defined by seven subcomponents: ethics, evaluation, identification, understanding, usage, application, and creation. Based on this framework, a survey instrument was developed and administered to 169 first-year students at University A. The results indicated that students’ overall AI literacy was above average, with particularly high levels in AI usage and application, while AI creation—which includes advanced abilities such as model design and programming—was notably low. Significant differences in AI creation literacy were observed across academic disciplines, with humanities students exhibiting lower levels than students in AI-related majors. Analysis of students’ educational experiences and needs revealed that most participants had prior AI learning experiences but identified insufficient coding and basic computer knowledge as major challenges. There was also strong demand for general education courses for non-majors and for applied courses focusing on generative AI utilization. Based on these findings, this study suggests the need for a balanced framework in university general education that integrates both user-oriented and producer-oriented AI literacy, reinforces attitude-based competencies such as AI ethics and evaluation, and provides discipline-specific instructional approaches.