2026-10-29T23:34:04Zhttps://bayburt-rdlopen.rawdatalibrary.net/oai/request

oai:bayburt-rdlopen.rawdatalibrary.net:bayburt/110242026-10-29T19:41:16Zopenairecom_bayburt_10000col_bayburt_10001com_bayburt_10007col_bayburt_10218

A psychometric analysis of the artificial intelligence skills scale developed through chat gptGörgülü, DenizCoşkun, FatmaDemi̇r, MustafaSi̇pahi̇oğlu, MeteArtificial intelligenceChat GPTScale development with Chat GPTTeacher sampleThis study aims to examine the psychometric properties of a scale developed to measure teachers’ ability to use artificial intelligence tools in education. The scale was originally proposed as having 33 items across 5 sub-dimensions by Chat GPT-4, an AI system. To establish content validity, the scale form was submitted to expert review. An exploratory factor analysis (EFA) was then conducted on a sample of 347 teachers to determine if the 33-item, 5-subdimensional structure proposed by Chat GPT was confirmed by empirical data. The EFA results supported Chat GPT-4’s proposed structure. A confirmatory factor analysis (CFA) was applied to a new sample of 603 teachers to assess the scale’s validity in an independent sample. The CFA results did not fully support the structure consisting of 33 items and 5 subdimensions proposed by Chat GPT. Reliability was analyzed using Cronbach’s Alpha and test-retest methods.Springer2025Articlehttps://rdlopen.rawdatalibrary.net/r/bayburt/11024https://doi.org/10.1007/s10639-024-13294-71360-2357enEducation and Information Technologiesinfo:eu-repo/semantics/closedAccessinfo:eu-repo/semantics/articlehttps://bayburt-rdlopen.rawdatalibrary.net/tr/items/bayburt/11024