Integrating Artificial Intelligence and Blended Learning within the PCK Framework for English Language Teaching

This study presents a rigorously conceptualized and empirically validated instructional model that synthesizes artificial intelligence and blended learning within the pedagogical content knowledge framework to elevate the sophistication and impact of English language teaching. Addressing the global demand for pedagogically grounded yet technologically responsive instructional approaches, the model positions teacher knowledge as the structural core through which intelligent technologies and blended modalities are meaningfully orchestrated. The study seeks to examine the extent to which systematic alignment among pedagogical content knowledge domains, artificial intelligence–driven tools, and blended learning structures can generate deeper instructional coherence, refine pedagogical judgment, and enhance the quality of learning experiences. Utilizing a mixed-method design that incorporates model formulation, expert scrutiny, staged classroom implementation, and comprehensive learner performance analysis, the study reveals that the integrated model significantly expands teachers’ capacity to enact adaptive, data-informed, and learner-centered instruction. The findings further indicate that artificial intelligence facilitates dynamic personalization and real-time instructional support, while blended learning environments reinforce continuity, autonomy, and multidimensional engagement. Overall, the model demonstrates strong potential to function as a transformative framework capable of guiding innovative, scalable, and pedagogically robust practices in English language education across diverse global contexts.

کلیدواژه ها:

Artificial intelligence ، blended learning ، pedagogical content knowledge ، instructional innovation ، English language teaching