This study aims to develop a conceptual and empirical framework for assessing digital maturity in Iran’s higher education system. Given the transformative role of digitalization in enhancing quality, effectiveness, and institutional responsiveness to societal needs—as well as the imperative to align with global trends in emerging technologies—it is essential to evaluate the readiness and digital maturity of academic institutions through a rigorous, systematic, and evidence-based approach. A thorough examination of relevant indicators and components can offer deeper insights into the current state and help chart pathways for improvement and development. By integrating qualitative and quantitative methodologies, this research seeks to propose a comprehensive and practical model for evaluating digital maturity, one that can inform national educational policymaking, data-driven decision-making, and strategic planning. Ultimately, the goal is to identify the key dimensions of digital maturity and design a scientifically valid, locally adapted assessment tool that enables continuous monitoring, comparative analysis, progress tracking, and the formulation of transformative strategies. This framework is intended to support performance enhancement, promote transparency, and improve institutional accountability in navigating digital transitions across the higher education landscape. In doing so, it contributes to the broader discourse on digital transformation in education and provides a replicable model for similar contexts in other developing countries.
Research Methodology
This study was conducted using a mixed-methods design, comprising both qualitative and quantitative phases.
In the qualitative phase, the research followed a content analysis approach. Based on the principle of theoretical saturation, twelve informed and expert participants in the fields of higher education and information technology were selected through criterion-based purposive sampling. Data were collected using a semi-structured interview protocol, carefully designed and implemented. To ensure the validity of the qualitative data, multiple strategies were employed, including dual coding review, expert validation by non-participant scholars, and member checking with interviewees. The data were analyzed through several stages of open and axial coding, following Strauss and Corbin’s model, leading to the extraction of core categories.
In the quantitative phase, a descriptive-survey method was adopted. The statistical population consisted of all subject-matter experts in higher education and information technology, from which 200 individuals were selected using convenience sampling. Data collection in this phase was carried out using a researcher-developed questionnaire, designed based on the findings of the qualitative phase. Content validity was confirmed by six experts using the Content Validity Ratio (CVR), and face validity was approved by a group of respondents. The reliability of the instrument was estimated using Cronbach’s alpha coefficient, which exceeded 0.70, indicating acceptable internal consistency. Quantitative data were analyzed at both descriptive and inferential levels using SPSS and AMOS software packages.
Analysis and Conclusion
The qualitative findings led to the development of a three-dimensional model encompassing eleven overarching categories. These dimensions include:
• Digital Adoption (digital culture, digital infrastructure, digital policy, digital sustainability)
• Digital Development (digital operationalization, digital security, digital skills)
• Digital Knowledge Management (digital quality, digital assessment, digital support, digital credibility)
This model aims to systematically and measurably conceptualize the multifaceted nature of digital maturity.
Quantitative data analysis confirmed the model’s strong goodness-of-fit, indicating its validity as a reliable framework for assessing digital maturity within Iran’s higher education system. The results further revealed that within the digital adoption dimension, digital sustainability had the highest mean score; within digital development, digital skills emerged as the most prominent component; and within digital knowledge management, digital assessment received the highest average.
These findings underscore the importance of addressing various aspects of digital maturity in national educational planning and policymaking. The proposed model offers a strategic tool for evaluating current conditions, identifying strengths and weaknesses, and guiding the digital transformation trajectory of universities.