Understanding pre-service teachers’ needs for integrating AI-based tools in instruction through intelligent TPACK framework

As Artificial Intelligence in Education (AIEd) transforms teaching and learning with accompanying technological, pedagogical, and ethical challenges, understanding pre-service teachers’ AI perceptions and ensuring their adequate preparation is crucial for effective AIEd implementation. While previous research has examined pre-service teachers’ AI competencies and perspectives using either quantitative or qualitative methods, a critical gap remains in understanding their specific needs for AI-based instructional tools and relevant training through an integrated theoretical lens. This mixed-methods study addresses this gap by investigating 49 pre-service teachers’ needs under the Intelligent-TPACK framework. Statistical and thematic analyses revealed pre-service teachers’ ambivalent attitudes toward AI-based tools and associated training. Participants expressed needs for technological, pedagogical, content, and ethical knowledge related to AI in education, along with concerns about AI-based tools. While individual requirements for AI-relevant knowledge varied, participants consistently demonstrated high demand for training specifically in AI ethics. Overall, this study revealed pre-service teachers’ unpreparedness regarding AIEd, furtherly uncovering critical gaps between their knowledge demands and existing teacher training programs. The findings call for an integrated approach combining AI-technical expertise with hands-on pedagogical practices within teacher education programs. This research contributes to the field by validating the Intelligent TPACK framework and providing recommendations for educational program designers to create effective training for AI-based tools.