Constructing and Validating the AIPACK Scale: Measuring Teachers' AI Pedagogical Content Knowledge

ABSTRACT This study developed and validated the Artificial Intelligence Pedagogical Content Knowledge (AIPACK) scale to assess the AI‐related instructional knowledge of primary and secondary school teachers in Taiwan. The scale includes four dimensions: AI Knowledge (AIK), AI Content Knowledge (AICK), AI Pedagogical Knowledge (AIPK), and AI Pedagogical Content Knowledge (AIPACK). Valid responses from 200 participants were analysed using confirmatory factor analysis (CFA), resulting in a finalised 26‐item scale with a four‐factor structure. The CFA results indicated good model fit. All factor loadings exceeded 0.60, and both the average variance extracted (AVE) and composite reliability (CR) met the recommended thresholds, indicating strong construct validity and internal consistency. Measurement invariance was established across gender and teaching roles (preservice vs. in‐service), enabling valid cross‐group comparisons. The findings support the AIPACK scale's reliability and validity as a tool for evaluating teachers' AI‐related instructional knowledge and offer a foundation for future research, training, and policy.