Cross-sectional study reveals a valid 39-item scale measuring artificial intelligence attitudes in preservice teachers, providing a robust instrument for teacher education assessment.
Key Points
To develop and psychometrically validate a standardized measurement scale assessing preservice teachers' attitudes toward artificial intelligence technology.
Sampled 672 preservice teachers across departments and grade levels at a state university education faculty using convenience sampling in a quantitative cross-sectional design.
Generated an initial 70-item Likert-type pool informed by literature, refined via field-expert evaluation and feedback from 15 preservice teachers.
Conducted exploratory factor analysis in 315 participants and confirmatory factor analysis in an independent group of 357 participants, along with convergent and discriminant validity testing.
Exploratory factor analysis established a 39-item, three-factor structure accounting for 53.23% of the total variance.
Acceptable convergent and discriminant validity alongside a high Cronbach's alpha confirmed scale reliability across 28 positively worded and 11 negatively worded items.