From proficiency to pedagogy: A mixed-methods study of in-service teachers’ TPACK-GenAI and the mediating role of pedagogical knowledge

In today's digital era, Generative AI (GenAI) tools and technologies offer immense potential to transform education (Guler et al., 2024). These innovations can help teachers to diagnose specific learning challenges and deliver tailored interventions, making learning more efficient and effective (Li et al., 2023). For instance, Wei (2023) revealed that GenAI tools can help educators identify where students are struggling and provide tailored support to address those difficulties (Wang & Wang, 2022). Research has also shown that GenAI tools positively influence how students learn and how they feel about using technology (Nazari et al., 2021; Utami et al., 2023). Regardless of these promising benefits, scholars have raised valid concerns about the accuracy of AI-generated content in certain subject areas and the risk of students becoming too dependent on these tools (Matzakos et al., 2023). This reflects that GenAI should be seen as a helpful supplement that enhances teaching rather than something that replaces traditional instruction. Successfully integrating GenAI into classroom practice requires teachers to have more than just technical skills; they need to understand how to effectively blend this technology with their teaching strategies and subject knowledge, which is captured in the TPACK (Technological Pedagogical Content Knowledge) framework. When in-service teachers lack confidence in their TPACK-GenAI abilities, they often struggle to effectively incorporate GenAI technologies into their lessons (Dasari et al., 2024). This emphasizes why it is so imperative to examine how in-service teachers view their TPACK-GenAI confidence and in what way their perceptions affect their classroom use of GenAI tools. Understanding teachers' confidence levels and integration practices is crucial for identifying what is holding them back and for creating professional development programs that truly address their needs (Getenet, 2024). Despite the growing interest in TPACK frameworks, studies focusing specifically on in-service teachers' TPACK in GenAI contexts remain limited, highlighting a gap in empirical research (Chai et al., 2013; Voogt et al., 2015). Most existing literature emphasizes pre-service teacher training or general TPACK development, indicating that the unique challenges and professional growth of in-service teachers in integrating technology are still underexplored (Angeli & Valanides, 2009). However, there is still inadequate research examining in-service teachers' TPACK-GenAI confidence and how they are using AI tools in real classroom settings (Yadav et al., 2026). While existing studies highlight the importance of professional development in helping teachers adopt new technologies (Daher et al., 2021), there is a clear need for research that explores the connection between teachers’ TPACK-GenAI confidence and their actual implementation of GenAI in their classrooms.