Cross-National Survey Data on Student Attitudes Toward Artificial Intelligence

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F25%3A43927417" target="_blank" >RIV/62156489:43110/25:43927417 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.dib.2025.112022" target="_blank" >https://doi.org/10.1016/j.dib.2025.112022</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.dib.2025.112022" target="_blank" >10.1016/j.dib.2025.112022</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cross-National Survey Data on Student Attitudes Toward Artificial Intelligence

Popis výsledku v původním jazyce

This data article presents responses from a comprehensive, multi-year survey conducted between 2022 and 2024 at several universities in Central and Eastern Europe, focusing on students&apos; artificial intelligence (AI) literacy, attitudes, and readiness. The data collection was part of a longitudinal project within the FITPED consortium, which built upon previous EU-funded initiatives to support digital education. A total of 1,146 university students participated, representing a diverse range of study programs, academic years, and countries, including Slovakia, Poland, the Czech Republic, Lithuania, Indonesia, Turkey, France, and Ukraine. The structured questionnaire was based on validated instruments and included constructs such as AI literacy, AI readiness, AI anxiety, behavioural intention, satisfaction, confidence, perceived relevance of AI, and social goods. Items were rated on a 5-point Likert scale, and demographic information, including gender, age, year of study, field of study, and previous experience with AI-related courses, was collected. The survey was administered anonymously via Google Forms and the Moodle LMS in multiple languages, ensuring accessibility across disciplines. The dataset supports cross-disciplines and longitudinal comparisons and is suitable for quantitative analytical methods such as factor analysis and structural equation modeling. This openly shared dataset provides a foundation for tracking trends in AI readiness and perceptions in higher education. It allows for its reuse for comparative international research, curriculum development, and targeted educational interventions that promote inclusive and context-aware AI literacy.

Název v anglickém jazyce

Cross-National Survey Data on Student Attitudes Toward Artificial Intelligence

Popis výsledku anglicky

This data article presents responses from a comprehensive, multi-year survey conducted between 2022 and 2024 at several universities in Central and Eastern Europe, focusing on students&apos; artificial intelligence (AI) literacy, attitudes, and readiness. The data collection was part of a longitudinal project within the FITPED consortium, which built upon previous EU-funded initiatives to support digital education. A total of 1,146 university students participated, representing a diverse range of study programs, academic years, and countries, including Slovakia, Poland, the Czech Republic, Lithuania, Indonesia, Turkey, France, and Ukraine. The structured questionnaire was based on validated instruments and included constructs such as AI literacy, AI readiness, AI anxiety, behavioural intention, satisfaction, confidence, perceived relevance of AI, and social goods. Items were rated on a 5-point Likert scale, and demographic information, including gender, age, year of study, field of study, and previous experience with AI-related courses, was collected. The survey was administered anonymously via Google Forms and the Moodle LMS in multiple languages, ensuring accessibility across disciplines. The dataset supports cross-disciplines and longitudinal comparisons and is suitable for quantitative analytical methods such as factor analysis and structural equation modeling. This openly shared dataset provides a foundation for tracking trends in AI readiness and perceptions in higher education. It allows for its reuse for comparative international research, curriculum development, and targeted educational interventions that promote inclusive and context-aware AI literacy.

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

Data in Brief

ISSN

2352-3409

e-ISSN

2352-3409

Svazek periodika

62

Číslo periodika v rámci svazku

October

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

112022

Kód UT WoS článku

001573770100006

EID výsledku v databázi Scopus

2-s2.0-105015302264