Identification and Validation of Factors Influencing Digital Transformation in Higher Education

Abstract

Digital transformation in higher education is one of the most significant contemporary issues, and identifying the factors influencing it can greatly contribute to the improvement of educational processes. This study was conducted with the aim of identifying and validating the factors influencing digital transformation in higher education. In the qualitative phase, through a systematic review of the literature and a detailed content analysis of Persian and English scientific articles extracted from reputable databases such as Scopus, ScienceDirect, Emerald, and Noor, the initial dimensions and components of a conceptual model for digital education based on artificial intelligence were identified and categorized. In the quantitative phase, in order to validate these factors and examine the structural relationships between them, the Interpretive Structural Modeling (ISM) technique was applied. The statistical population included university professors, educational managers, and postgraduate students in fields related to educational technology, educational management, education sciences, computer engineering, and artificial intelligence, who were selected through purposive and snowball sampling methods. A researcher-developed questionnaire was initially distributed among 30 participants, of which 22 valid questionnaires were ultimately analyzed. In data analysis, the adapted reachability matrix was first developed, and then the levels of factors were determined based on input and output relationships. The results indicated that criterion D7 was identified as the most fundamental factor, while criterion D5 emerged as the most dependent factor at the highest level, with other criteria positioned at intermediate levels. This hierarchical structure provided a clearer understanding of the role and importance of each factor in the digital transformation process, enabling prioritization and the design of targeted strategies. The findings serve as a valuable guide for higher education administrators and policymakers to accelerate and improve the digital transformation process.