Fostering preservice science teachers' AI-Tpack competence and reflections through an AI-focused pedagogical learning course

Abstract

The rapid emergence of artificial intelligence (AI) in education underscores the imperative to equip future educators with the competencies needed to meaningfully integrate AI into instruction. Hence, this study aimed to effectively cultivate Technological Pedagogical Content Knowledge for AI (AI-TPACK) competence among preservice science teachers (PSSTs) through the implementation of an AI-focused pedagogical learning course. Anchored on social constructivist principles, the course integrated structured instruction, hands-on activities, collaborative lesson design, and reflective practices to enhance both PSSTs’ understanding and practical application of AI in science education. A pre-experimental one-group pretest-posttest design was employed with 84 PSSTs enrolled in a state university in the Philippines. Quantitative data were collected using an adapted AI-TPACK scale, while qualitative insights were gathered through structured interviews. Non-parametric analysis using the Wilcoxon Signed-Ranks Test revealed statistically significant improvements across all dimensions of AI-TPACK, namely technological knowledge, pedagogical applications, ethical considerations, and integrated competence (z = -6.900, p < .001, r = 0.76), indicating a large effect size. Thematic analysis of PSSTs’ reflections identified key affordances such as enhanced pedagogical design, improved AI literacy, and increased student engagement, alongside constraints related to tool limitations, ethical dilemmas, and contextual barriers. The findings highlight the potential of strategically designed teacher education interventions in fostering AI-TPACK competence. The study contributes empirical evidence and pedagogical insights for advancing AI integration in pre- and in-service teacher training, reinforcing the need for intentional design, policy alignment, and continued research on equitable and context-sensitive AI adaption in science education.