Artificial Intelligence Literacy and Its Implementation among University Students

Abstract

This research aims to overviewof the level of artificial intelligence (AI) literacy and to explore the practices of its implementation among university students. The method used was mixed methods, combining quantitative and qualitative approaches. Quantitative data were collected through a Likert-scale-based questionnaire adapted from the Multidimensional AI Literacy Scale (MAILS) instrument, while qualitative data were obtained through in-depth interviews. The research subjects consisted of 46 individuals, with 7 of them serving as interview respondents. The analysis results showed that the average score of students' artificial intelligence (AI) literacy was 66.83, which fell into the moderate category. A total of 30.43% of university students were in the high category, 58.70% in the moderate category, and 10.87% in the low category. The highest score was found in the eval_uation indicator (71.3%), followed by the ethics of AI use (67.61%), both of which were in the moderate category. The lowest scores were found in the AI usage indicator (65%) and AI detection (65.43%). The interview results revealed that the implementation of artificial intelligence (AI) literacy among university students was still not optimal. This was reflected in their shallow understanding, not optimal usage, low detection ability, eval_uation that was not conducted automatically, and ethical awareness that was situational and inconsistent. In conclusion, university students' artificial intelligence (AI) literacy needs to be comprehensively strengthened to align with the demands of current technological developments.