Akademik Veri Yönetim Sistemi
EUROPEAN JOURNAL OF EDUCATION, cilt.61, sa.3, 2026 (SSCI, Scopus)
This study examined the development of a scale to measure pre-service teachers' attitudes towards outdoor learning activities and the role of ChatGPT in this process. Although the literature has highlighted the potential of artificial intelligence (AI) tools to accelerate and support research, their use in labor-intensive processes such as scale development remains relatively new. In this study, we first reviewed the concepts of attitude, out-of-school learning environments, and AI-assisted scale development. We then designed a scale development process in which items were generated with the assistance of ChatGPT (GPT-4o) and subsequently evaluated through expert review. Expert evaluations and preliminary applications reduced the initial 63-item draft to 53 items, which was then further reduced to 25 items by removing highly overlapping items. Exploratory factor analysis (EFA) supported a unidimensional structure, while second-order confirmatory factor analysis (CFA) also supported the theorized cognitive, affective and behavioural organization of the construct. The scale demonstrated high internal consistency, and criterion-related validity findings were supportive. In addition, the scale was shortened to a four-item short form using a genetic algorithm to improve ease of use. Overall, the findings suggest that ChatGPT assisted scale development may yield psychometrically useful results when combined with expert review and conventional validation procedures.