Document Type : Fall 2025 Special Issue
Authors
1
Ph.D student, Department of Curriculum Studies and Instruction, Faculty of Educational Sciences and Psychology, Ferdowsi University of Mashhad, Mashhad, Iran.
2
Associate Professor, Department of Curriculum Studies and Instruction, Faculty of Educational Sciences and Psychology, Ferdowsi University of Mashhad, Mashhad, Iran.
3
Professor, Department of Curriculum Studies and Instruction, Faculty of Educational Sciences and Psychology, Ferdowsi University of Mashhad, Mashhad, Iran.
10.30473/t-edu.2025.75670.1322
Abstract
Purpose: The present study aimed to identify the dimensions and components of effective teaching with artificial intelligence (AI) within the framework of Technological Pedagogical Content Knowledge (TPACK), based on the experiences of university professors and educational experts.
Method: This research employed a qualitative approach using Grounded Theory with the Strauss and Corbin coding paradigm. Data were collected through semi-structured interviews with 19 professors and specialists in the field of education. The data were analyzed through open, axial, and selective coding.
Findings: The results revealed that the integration of AI in teaching redefines teachers’ knowledge domains, including Technological Knowledge (TK), Pedagogical Knowledge (PK), Content Knowledge (CK), and their intersections such as TPK, PCK, and TCK. Key components identified included personalized learning, enhanced instructional interaction, visualization of complex concepts, and the design of creative learning activities through human–machine collaboration. Moreover, ethical concerns such as overreliance on AI, the validity of generated content, and the necessity of preserving human interaction were highlighted.
Conclusion: The study concludes that the success of effective AI-based teaching depends on three fundamental conditions: (1) professional development and empowerment of teachers, (2) synergy between AI technologies and active learning approaches, and (3) establishment of transparent ethical frameworks and responsible policies. By expanding the TPACK framework in the context of AI, this research contributes both theoretically to the reconceptualization of teacher knowledge and practically to the design of teacher education programs and policy-making in smart learning ecosystems.
Keywords
