The rapid advancement of digital technology, particularly artificial intelligence (AI), has reshaped teacher education by requiring the integration of technological, pedagogical, and content knowledge in instructional design. The AI-TPACK (artificial intelligence–technological pedagogical content knowledge) framework offers a structured foundation to support such integration in science education. This study aims to analyze the effectiveness of AI-TPACK-based learning in strengthening pre-service science teachers’ competencies in designing innovative lesson plans. A quantitative approach with a pre-experimental one-group pretest–posttest design was implemented with three class group of undergraduate science education students at Universitas Negeri Semarang. The intervention addressed seven dimensions: content knowledge, pedagogical knowledge, AI technological knowledge, pedagogical content knowledge, AI technological content knowledge, AI technological pedagogical knowledge, and integrated AI-TPACK. Data were collected through a validated rubric and analyzed using descriptive statistics, gain scores, and paired comparison tests. The results of the study indicate a significant improvement in integration skills across all dimensions, with the greatest achievement in the integration of AI technological knowledge and pedagogical content knowledge within the students lesson plans. Consistent progress across class groups confirms the effectiveness of the AI-TPACK-based model in enhancing technological proficiency and meaningful pedagogy–content integration. The study concludes that systematic adoption of AI-TPACK in teacher education can improve professional readiness, nurture critical, creative, and collaborative skills, and contribute to Sustainable Development Goal 4 on quality education.
Dewi et al. (Tue,) studied this question.