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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F25%3A43927072" target="_blank" >RIV/62156489:43110/25:43927072 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/ACCESS.2025.3573575" target="_blank" >https://doi.org/10.1109/ACCESS.2025.3573575</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2025.3573575" target="_blank" >10.1109/ACCESS.2025.3573575</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

This study examines the structure of artificial intelligence (AI) literacy and factors influencing students&apos; 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.

Název v anglickém jazyce

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

Popis výsledku anglicky

This study examines the structure of artificial intelligence (AI) literacy and factors influencing students&apos; 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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20202 - Communication engineering and systems

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

2169-3536

Svazek periodika

13

Číslo periodika v rámci svazku

26 May

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

24

Strana od-do

93235-93258

Kód UT WoS článku

001502494300002

EID výsledku v databázi Scopus

2-s2.0-105006706458