Developing and Validating an AI-Literacy-Integrated Teaching Acceptance and Readiness Scale for Mathematics Teachers

The global shift toward cultivating students’ AI literacy requires teachers to reconceptualize curricula and pedagogical practices. However, research has focused primarily on teachers’ use of AI tools, overlooking their readiness to integrate AI literacy as a learning goal, particularly in mathematics education. In response, this study developed and validated the AI-Literacy-Integrated Teaching Acceptance and Readiness Scale for Mathematics Teachers (AILTAR-M). The instrument was theoretically organized around two domains: (1) Acceptance , comprising four constructs adapted from the Technology Acceptance Model (Perceived Usefulness, Perceived Ease of Use, Attitude toward Use, and Behavioral Intention); and (2) Readiness , encompassing Perceived AI Literacy as a self-reported cognitive dimension and Teaching Self-Efficacy as a motivational dimension. Psychometric evaluation with 549 mathematics teachers in China supported a 29-item, six-factor structure. Exploratory factor analysis ( n = 174) yielded a six-factor solution explaining 69.7% of the variance, and confirmatory factor analysis ( n = 375) demonstrated acceptable model fit (CFI = .938, TLI = .931, RMSEA = .063, SRMR = .038). The instrument exhibited strong internal consistency (α = .899– .943) alongside satisfactory convergent and discriminant validity. These findings provide initial psychometric evidence for using the AILTAR-M to examine mathematics teachers’ acceptance of and readiness for integrating AI literacy into mathematics instruction.