Learning to Teach AI: Design and Validation of a Questionnaire on Artificial Intelligence Training for Teachers
Open accessAbstract
This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.
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The impact of emotional distress can be added to the impact of consequential validity.
“Therefore, the impact of emotional distress can be added to the impact of consequential validity [5, 41].”
From The impact of generative artificial intelligence tools on assessment equity for non-native English-speaking medical students: a systematic review (2026) · cites this paper as [41]
The ‘Need for Validation of a Questionnaire’ and ‘Validation of the Questionnaire’ sections discuss measuring perceptions of AI in education and the questionnaire’s validity. Neither addresses emotional distress or consequential validity; searches for those terms and their relationship found no relevant passage in our copy. (LLM, conf=0.76)
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- Authors
- Reina-Parrado, M., Román-Graván, P., & Hervás-Gómez, C.
- Affiliations
- Universidad de Sevilla (ES)
- Venue
- European Journal of Educational Research
- Published
- 2025-01-08
- Volume
- 14
- Issue
- 1
- Pages
- 249-265
- ISSN
- 2165-8714 (ISSN-L)
- OpenAlex
- W4406154631
- Cited by
- 13
- References
- 53
- Citations by year
- 2026: 8 · 2025: 5
- FWCI
- 13.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- European Journal of Educational Research (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence in education, teacher professional development, AI literacy, questionnaire design, instrument validation, teacher perceptions, personalized learning, teacher attitudes toward AI, training evaluation
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