Teachers’ Perceptions of Generative Artificial Intelligence in Early Childhood and Primary Education: Barriers, Ethical Concerns, and Perceived Impacts
The growing integration of Generative Artificial Intelligence (GAI) into education has intensified the need to understand teachers’ perceptions of its implementation in the early stages of schooling. This study aimed to examine the barriers, ethical concerns, and perceived impact of GAI among Early Childhood and Primary Education teachers in Spain. An interpretive qualitative design was adopted using an open-ended questionnaire completed by 183 teachers from 15 Spanish autonomous communities. Data were analyzed through thematic content analysis in NVivo 14, resulting in a coding framework comprising three metacategories, 27 categories, and 98 subcategories. The findings indicate that insufficient training and limited digital competence constitute the main barriers to GAI integration, while ethical concerns focus primarily on the potential decline in students’ critical thinking, irresponsible use, data privacy, and the reliability of AI-generated information. Although teachers recognize the potential of GAI to support learning, they express greater concern about its possible negative effects on creativity, effort, and autonomous knowledge construction. Moreover, they consistently emphasize that its educational impact depends on teacher training, pedagogical mediation, and the context in which it is implemented. These findings highlight that the successful integration of GAI in Early Childhood and Primary Education requires strengthening teachers’ AI literacy and promoting pedagogically grounded and ethically responsible implementation strategies.
Authors
- María Cruz Sánchez Gómez (ORCID: https://orcid.org/0000-0003-4726-7143)
- Desirée Ayuso del Puerto (ORCID: https://orcid.org/0000-0002-6290-7391)
- Juan Luis Cabanillas-García (ORCID: https://orcid.org/0000-0001-8458-3546)
Institutions
- Universidad de Salamanca (ES)
- Universidad de Extremadura (ES)
Publication Details
- Journal
- Applied Sciences
- Published
- 2026-10-07
- DOI
- https://doi.org/10.3390/app16199907
- Primary Topic
- Artificial Intelligence in Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00