Artificial Intelligence Literacy Structure and the Factors Influencing Student Attitudes and Readiness in Central Europe Universities

This study examines the structure of artificial intelligence (AI) literacy and factors influencing students’ attitudes, readiness, and perceived relevance of AI in higher education at Central European universities. The research, based on data from 1,195 students enrolled in various study programs between 2022 and 2024, examines how variables such as gender, academic discipline, and year of study influence perceptions related to AI. A validated questionnaire targeting constructs including satisfaction, readiness, and relevance of AI was used. Non-parametric statistical methods were used to identify significant differences between groups, including Kruskal-Wallis and Mann-Whitney tests with Dunn-Bonferroni post hoc analysis. The findings reveal consistent differences across genders and disciplines, with males and IT students demonstrating significantly higher readiness and satisfaction with AI. Furthermore, satisfaction levels fluctuated over time, peaking in 2023 – likely influenced by the widespread adoption of tools like ChatGPT. Correlation analysis further highlighted the subtle interrelationships between constructs across different subgroups. The study underscores the importance of tailored AI education strategies and calls for targeted interventions to ensure equitable engagement with AI across diverse student populations.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3573575
Citations
6
Primary Topic
Educational Innovations and Challenges
Type
article
Field-Weighted Citation Impact
19.48

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article

Artificial Intelligence Literacy Structure and the Factors Influencing Student Attitudes and Readiness in Central Europe Universities

Eugenia Smyrnova‐Trybulska, Małgorzata Przybyła‐Kasperek, Cyril Klimeš, Ján Skalka et al.
6 citations
IEEE Access
Educational Innovations and Challenges
19.48
article

Artificial Intelligence Literacy Structure and the Factors Influencing Student Attitudes and Readiness in Central Europe Universities

Eugenia Smyrnova‐Trybulska, Małgorzata Przybyła‐Kasperek, Cyril Klimeš, Ján Skalka, Vladimiras Dolgopolovas, Radim Farana, Valentina Dagien
article en
6 citations

Abstract

This study examines the structure of artificial intelligence (AI) literacy and factors influencing students’ attitudes, readiness, and perceived relevance of AI in higher education at Central European universities. The research, based on data from 1,195 students enrolled in various study programs between 2022 and 2024, examines how variables such as gender, academic discipline, and year of study influence perceptions related to AI. A validated questionnaire targeting constructs including satisfaction, readiness, and relevance of AI was used. Non-parametric statistical methods were used to identify significant differences between groups, including Kruskal-Wallis and Mann-Whitney tests with Dunn-Bonferroni post hoc analysis. The findings reveal consistent differences across genders and disciplines, with males and IT students demonstrating significantly higher readiness and satisfaction with AI. Furthermore, satisfaction levels fluctuated over time, peaking in 2023 – likely influenced by the widespread adoption of tools like ChatGPT. Correlation analysis further highlighted the subtle interrelationships between constructs across different subgroups. The study underscores the importance of tailored AI education strategies and calls for targeted interventions to ensure equitable engagement with AI across diverse student populations.

IEEE AccessVol. 13
Vilnius University (LT), Constantine the Philosopher University in Nitra (SK), Academy of Fine Arts in Katowice (PL), Mendel University in Brno (CZ), University of Silesia in Katowice (PL)
Vedecká Grantová Agentúra MŠVVaŠ SR a SAV, Erasmus+
Quality Education
Openalex Percentile: Top 1%
Educational Innovations and Challenges
19.48
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