Artificial Intelligence Competence Teachers’ Assessment Scale (AICTS): Development and Validation

Abstract

The rapid development in artificial intelligence (AI) is transforming the education system
globally. It is pertinent to assess the competence level and teachers’ willingness to integrate
AI into their professional teaching practice. Although the potential of AI literacy is
increasing, the current tools are rather limited in scope and tend to focus on the student
population or the general public, disregarding a specific cognitive, attitudinal, and
professional skills focus which are required for teachers. This research overcomes this
limitation by developing and validating the Artificial Intelligence Competence Teachers
Assessment Scale (AICTAS), which is multidimensional in structure and was conceptually
designed over three core domains, including Cognitive Competence, Attitudinal Competence,
and Professional Competence. The initial scale consisted of 84 Items, which were reduced to
75 after constructing content validity. The 75-item scale was administered to a sample of 390
teachers of various academic disciplines form public and private universities. Exploratory
factor analysis (EFA) supported a 13-factor structure, retaining 67 Items that explained
69.54% of the total variance. The structure was confirmed by confirmatory factor analysis
(CFA) that provided acceptable fit indices (df: 2; 2.39; RMSEA = 0.060; CFI = 0.818).
AITCAS showed great internal consistency (alpha = 0.832), indicative of a reliable
instrument. It is recommended to use this validated scale to assess AI competence among
teachers, to design interventions accordingly.