I am an Assistant Professor in computer science education and educational technology, with an established research background in quantitative methods, including survey-based studies, scale development, and validation related to AI, digital literacy, and computational thinking. My published work includes the development and empirical validation of attitudinal and awareness measures, as well as large-sample analyses examining learners’ and teachers’ perceptions of emerging educational technologies. Building on this quantitative foundation, my recent research has expanded toward conceptual and qualitative inquiries into how AI systems reshape teachers’ professional judgement, responsibility, and decision-making in practice. Across both strands, my work aims to connect robust measurement and empirical evidence with theoretically grounded interpretations of human–AI interaction in educational contexts. I am particularly interested in international collaborations that integrate quantitative instruments, cross-cultural validation, and practice-based analysis to advance theory-informed research in AI-supported education.