Developing AI-TPACK: A Framework for Mathematics Teachers’ Technological, Pedagogical, and Content Knowledge in the Artificial Intelligence Era

This study examined mathematics teachers’ AI-TPACK competency, perceptions of AI-driven tools, pedagogical assessment practices, and experiences in integrating artificial intelligence in instruction within the Schools Division of Siargao. An explanatory sequential mixed-methods design was employed involving 247 mathematics teachers and 12 key informants. Data were gathered using a researcher-made questionnaire and semi-structured interviews and analyzed through descriptive and inferential statistics alongside thematic analysis.
Findings indicated that teachers are in a transitional stage of AI integration, characterized by developing AI-TPACK competency, moderate technical proficiency, frequent yet routine use of AI tools, and generally favorable perceptions of usefulness with moderate ease of use. Teachers showed strong engagement in formative AI-assisted assessment; however, the integration of AI-generated outputs into grading and instructional decision-making remained limited. Quantitative results revealed significant relationships between TPACK competency and both perceived usefulness and ease of use, with TPACK emerging as the strongest predictor of AI competency. Qualitative findings further highlighted AI as an instructional support tool while identifying challenges such as the digital divide, literacy gaps, student overdependence, and infrastructural constraints. Based on the integrated results, an AI-TPACK Capacity-Building Framework for Mathematics Teachers was developed to enhance competencies, pedagogical integration, and sustainability of AI adoption in mathematics education.

AI-TPACK, artificial intelligence in education

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