Preparing Teachers for AI-Enhanced Education: Integrating Digital Competence, AI Literacy, and Personalized Learning Pedagogy

The rapid integration of artificial intelligence (AI) into educational systems is reshaping conventional approaches to teaching, learning, and assessment. AI-enhanced educational technologies such as adaptive learning platforms, automated feedback systems, and learning analytics offer significant opportunities for personalized instruction and increased instructional efficiency. However, the educational value of these technologies largely depends on teachers' professional knowledge, judgment, and ethical awareness. This paper examines the evolving landscape of teacher education in an era increasingly influenced by AI and argues for a reconceptualization of teacher preparation beyond traditional digital literacy toward a more comprehensive framework of AI literacy. This framework encompasses technical understanding, ethical reasoning, data literacy, and pedagogical decision-making. Using a qualitative conceptual methodology, the study synthesizes findings from scholarly literature, theoretical frameworks, and international policy documents published between ۲۰۱۷ and ۲۰۲۵. The analysis focuses on three core dimensions: (۱) digital competence frameworks such as DigCompEdu, (۲) emerging models of AI literacy for educators, and (۳) pedagogical implications of AI-supported personalized learning. The findings indicate that while AI systems can dynamically adapt instruction, teachers remain indispensable in interpreting algorithmic recommendations, ensuring equity, and embedding personalization within coherent pedagogical designs. The paper concludes that preparing teachers for AI-mediated education requires a holistic approach integrating digital competence, AI literacy, and pedagogical capacity to design human-centered hybrid learning environments.

کلیدواژه ها:

Artificial Intelligence ، AI Literacy ، Digital Competence ، Personalized Learning ، Teacher ، Education