Table · dataset · 2026
Data Sheet 1_Integrating generative artificial intelligence in education: perspectives of in-service and pre-service educators in the Belgrade metropolitan area.pdf
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<p>This study examined the perceptions of in-service and pre-service educators regarding the opportunities and challenges associated with the integration of generative artificial intelligence (GAI) in education.
Description
A cross-sectional survey was conducted with a diverse sample of 797 participants (20.8% men, 79.2% women) from the Belgrade metropolitan area, Serbia, including preschool and school teachers, university professors, and pre-service educators (students enrolled in faculties of education).
An author-developed questionnaire was used to assess reported use of GAI tools, perceived contributions to teaching and learning, ethical considerations, and professional readiness. While 39% of participants reported using GAI tools, the majority reported no use of specific GAI tools in their educational practice. The highest-rated aspect of GAI concerned the need for clearly defined ethical guidelines, whereas perceived relevance for supporting students socio-emotional development and critical thinking was comparatively low.
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Overall perceptions of GAI across the domains covered by the questionnaire were moderate (M = 2.97), reflecting cautious openness among in-service and pre-service educators. Perceptions varied significantly across socio-demographic characteristics, with more favorable evaluations reported by participants with fewer than 10 years of professional experience and by university-based educators and students. The findings highlight the central role of ethical governance and professional readiness in shaping in-service and pre-service educators’ evaluations of GAI and point to the importance of targeted professional development and institutional support for context-appropriate integration of GAI in educational practice.</p>
Links
Where it is published
- DOI doi.org/10.3389/feduc.2026.1914446.s002 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
- From keywords
- Astronomy & Astrophysics · Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Applied computing 73%
Related
Provenance · 1 source records, 17 field assertions
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|---|---|---|---|
| figshare | oai:figshare.com:article/33949111 | 9 d ago | JSON v1 |
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| concepts[field].local:field:social-science | mapping · figshare com | connector:figshare_com@1.0.0 | |
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| title | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/title |