Structure of AI Knowledge and Determinants Shaping Student Preparedness and Perceptions in Central European Higher Education

Abstract

This study investigates the framework of artificial intelligence (AI) literacy and the determinants affecting students' attitudes, preparedness, and perceived significance of AI in higher education at Central European universities. The study looks at how factors like gender, academic discipline, and year of study affect how students think about AI. It is based on data from 1,195 students who were enrolled in different study programs between 2022 and 2024. A validated questionnaire assessing constructs such as satisfaction, readiness, and relevance of AI was utilised. We used non-parametric statistical methods, like the Kruskal-Wallis and Mann-Whitney tests with Dunn-Bonferroni post hoc analysis, to find big differences between groups. The results show that there are consistent differences between genders and fields of study. For example, males and IT students are much more ready and happy with AI. Additionally, levels of satisfaction changed over time, reaching their highest point in 2023, probably because more people started using tools like ChatGPT. Correlation analysis further illuminated the nuanced interrelationships among constructs across various subgroups. The study highlights the necessity of customised AI educational strategies and advocates for specific interventions to guarantee equitable interaction with AI among varied student demographics.

Ähnliche Arbeiten