ArticleEuropean journal of pediatrics2025
Development of the generative artificial intelligence awareness scale for secondary school students in Türkiye.
Article in European journal of pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Nursing students' readiness for and acceptance of artificial intelligence technologies in clinical skills training: A cross-sectional study.International journal of nursing studies advances · 2026Article
- Metaphorical perceptions of secondary school students regarding the concept of generative artificial intelligence.European journal of pediatrics · 2026Article
- Prevalence, outcomes, and effective interventions for anxiety disorders in children and adolescents.Discover mental health · 2026Article
- Role reconstruction among double-qualified nursing educators in the generative AI era: a qualitative study.Frontiers in medicine · 2026Article
- The adaptive ecological trap: a grounded theory study of adolescent AI dependency.Frontiers in psychology · 2026Article
- Article
- The relationship between dependence on artificial intelligence and creative thinking dispositions among graduate students in sport sciences.Frontiers in psychology · 2026Article
- Understanding secondary school students' intentions to learn artificial intelligence: a multigroup structural equation modeling analysis.Frontiers in psychology · 2026Article
- Article
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Authors and funding
4 authors.
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Abstract
The widespread adoption of generative artificial intelligence (AI) in education and daily life necessitates a deeper understanding of students' awareness and attitudes. However, there is a lack of appropriate and psychometrically validated tools to assess these constructs reliably. This study aimed to examine the validity and reliability of a newly developed scale measuring secondary school students' awareness of generative artificial intelligence in the Turkish context. This methodological study employed a cross-sectional, descriptive, and correlational design. The research was conducted with 444 secondary school students aged 14-18. Data were collected using a Demographic Information Form and the Generative Artificial Intelligence Awareness Scale. The study followed a three-stage process in line with the STROBE checklist: (1) item development, (2) expert evaluation for content validity, and (3) construct validity and reliability testing. Construct validity was assessed using Exploratory and Confirmatory Factor Analyses. Reliability was examined through Cronbach's alpha, corrected item-total correlations, and split-half reliability analysis. EFA revealed a three-factor structure: Basic Knowledge of Generative Artificial Intelligence, Positive Attitudes Toward Generative Artificial Intelligence, and Concerns About the Impacts of Generative Artificial Intelligence, explaining 54.29% of the total variance. CFA supported the model, yielding acceptable fit indices (χ
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.