Factors affecting university students’ generative AI literacy: Evidence and evaluation in the UK and Hong Kong contexts

Generative AI (GenAI) has become popular with many university students since late 2022 and is incorporated in their daily life. To use GenAI tools effectively and equitably, and also to meet industry expectations, students should be supported to develop GenAI literacy skills during their time at university. Even though some universities have provided AI literacy training courses to students, the courses are not yet widely available to students across the higher education sector. Besides, there has been a shortage of GenAI literacy courses in particular. And more importantly, it is unclear what knowledge and skills that need to be included relating to GenAI literacy, from the student perspective. Building a strong understanding of student perceptions in this area is critical, because it will help enhance appropriateness and content relevance and promote student engagement. Adopting the four-dimensional AI literacy framework as the theoretical foundation, this paper aims to address the gaps. It explores the perceptions of university students on GenAI literacy in the UK and Hong Kong contexts. Survey data from 234 students were collected and analyzed using the descriptive analysis and Kruskal–Wallis test. The results show that factors such as country of studies and prior learning about AI greatly impacted GenAI literacy. However, factors such as age and educational level do not have a significant effect. Built upon the findings and the theoretical foundation, this paper proposes a new GenAI literacy framework. This framework is a revised version of the four-dimensional AI literacy framework and proposes the essential GenAI knowledge and skills for university students. The new framework also acknowledges the impact of the macro, meso, and micro factors on student GenAI literacy development.