Despite the growing presence of artificial intelligence (AI) productivity tools in education, there remains a lack of standardized instruments to assess teachers' readiness and engagement with such technologies. Addressing this gap, the present study developed and validated a comprehensive scale to measure teachers' knowledge, attitudes, and practices (KAP) related to AI productivity tools. Guided by the KAP framework, the study employed a sequential exploratory design. Initial items were generated through literature review and expert input, followed by content validation by AI and education specialists. The scale was pilot-tested and refined using data from a stratified convenience sample of 300 pre-service teachers in a state university in Central Visayas, Philippines. Exploratory and confirmatory factor analyses supported an 11-factor structure across the KAP domains. The finalized 58-item scale demonstrated strong psychometric properties, including high internal consistency and construct validity. By providing a valid and reliable tool, the study contributes to AI readiness assessment and intervention designs that promote responsible AI integration and use.
Citation: Joje Mar P. Sanchez, Gino G. Sumalinog, Janet A. Mananay, Charess E. Goles, Isidro Max V. Alejandro, Chery B. Fernandez. Scale development and validation of knowledge-attitudes-practices (KAP) on artificial intelligence (AI) productivity tools in education[J]. STEM Education, 2025, 5(6): 1022-1057. doi: 10.3934/steme.2025045
Despite the growing presence of artificial intelligence (AI) productivity tools in education, there remains a lack of standardized instruments to assess teachers' readiness and engagement with such technologies. Addressing this gap, the present study developed and validated a comprehensive scale to measure teachers' knowledge, attitudes, and practices (KAP) related to AI productivity tools. Guided by the KAP framework, the study employed a sequential exploratory design. Initial items were generated through literature review and expert input, followed by content validation by AI and education specialists. The scale was pilot-tested and refined using data from a stratified convenience sample of 300 pre-service teachers in a state university in Central Visayas, Philippines. Exploratory and confirmatory factor analyses supported an 11-factor structure across the KAP domains. The finalized 58-item scale demonstrated strong psychometric properties, including high internal consistency and construct validity. By providing a valid and reliable tool, the study contributes to AI readiness assessment and intervention designs that promote responsible AI integration and use.
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Figures(2) / Tables(14)
Joje Mar P. Sanchez, Gino G. Sumalinog, Janet A. Mananay, Charess E. Goles, Isidro Max V. Alejandro, Chery B. Fernandez. Scale development and validation of knowledge-attitudes-practices (KAP) on artificial intelligence (AI) productivity tools in education[J]. STEM Education, 2025, 5(6): 1022-1057. doi: 10.3934/steme.2025045
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