Designing and Validating a Qualitative Development Model for Higher Education Based on Artificial Intelligence

This study aimed to design and validate a qualitative development model for higher education based on artificial intelligence. Employing an applied-developmental approach and a sequential exploratory mixed-methods design, the research consisted of two phases. In the qualitative phase, a meta-synthesis of ۳۰ reputable international studies published between ۲۰۱۶ and ۲۰۲۵ was conducted, leading to the identification of nine core dimensions, ۲۶ components, and ۷۸ indicators. Content validity was confirmed by a panel of ۱۵ experts, and coding reliability was established through inter-coder agreement (Holsti's coefficient = ۰.۷۵۲). In the quantitative phase, a researcher-developed questionnaire based on the qualitative findings was administered to ۲۰۸ faculty members and higher education administrators. Data were analyzed using structural equation modeling and confirmatory factor analysis in SmartPLS. Model fit indices, including RMSEA = ۰.۰۵۸ and χ²/df = ۱.۷۱, confirmed the construct validity and reliability of the proposed model. The nine core dimensions of the model are intelligent teaching and learning, curriculum innovation, AI-driven assessment, digital management and governance, faculty development, ethics and responsibility, educational equity and inclusion, research and innovation, and student experience enhancement. The findings indicate that artificial intelligence serves not merely as a technological tool but as a driver of structural transformation in universities. The proposed model also provides a conceptual foundation for the development of AI-enabled digital educational platforms that support intelligent decision-making and personalized educational services in higher education.

کلیدواژه ها:

Artificial Intelligence: Higher Education ، Qualitative Development ، research synthesis ، structural equation modeling