Giving the Teacher AI Self Efficacy Measure a Psychometric Tune Up: Revalidating in the Pakistani Context
作者
Maimoona Naeem,Ayman Sahar,Kashaf Amjad
标识
DOI:10.59075/17zjs216
摘要
The study intended to revalidate an instrument of the Teacher AI Self-Efficacy consisting of 31 items under six dimensions. The dimensions included AI Knowledge, AI Pedagogy, AI Assessment, AI Ethics, Human-Centred Education, and Professional Engagement. The sample of piloting the instrument comprised 313 female secondary school teachers selected through stratified random sampling from public girls' secondary schools in Central Punjab (districts including Lahore, Faisalabad, Gujranwala, Sahiwal, and Sargodha). The instrument was revalidated in the local context of Punjab, Pakistan, through content validity, construct validity, and reliability procedures. The content validity yielded a Scale-Level Content Validity Index (S-CVI) of 0.78. The construct validity through Exploratory confirmatory factor analysis (CFA) demonstrated factor loadings ranging from .58 to .82 across all 31 items, with all loadings exceeding the acceptable threshold of .50. Reliability was assessed using the Cronbach's alpha coefficient, which was 0.76. The study concluded that the Teacher Self-Efficacy in Artificial Intelligence Competence Scale (TSAICS) is a psychometrically sound instrument for measuring teachers' self-efficacy in AI competence, and that continuous professional training and institutional support are essential for improving teachers' AI competence in secondary schools.