1- PhD student, Department of Educational Management, Ga.C., Islamic Azad University, Garmsar, Iran
2- Department of Educational Management, Ga.C., Islamic Azad University, Garmsar, Iran , ahmadif@iau.ac.ir
3- Department of Educational Management, Ga.C., Islamic Azad University, Garmsar, Iran
Abstract: (40 Views)
Objective: This study aimed to design an intelligence-based academic governance model for Iran’s higher education system by identifying its key components and examining their causal relationships.
Methods: The research employed an applied, descriptive-correlational design. Structural equation modeling (SEM) using LISREL software was used to assess causal pathways among the variables. The statistical population included faculty members from public universities in Tehran in 2025. Data were gathered through a researcher-made questionnaire administered via stratified random sampling.
Results: The proposed model demonstrated an acceptable level of fit. The construct of intelligence-based academic governance had positive and significant effects on five dimensions: causal, contextual, intervening, strategic, and consequential factors. Path coefficients ranged from 0.68 to 0.83, with corresponding t-values greater than 1.96. The strongest effect was observed for the strategic dimension (β = 0.83, t = 11.86, p < 0.001), underscoring the central role of intelligence in guiding macro-level decisions and supporting forward-looking planning in higher education.
Conclusions: Achieving intelligent academic governance requires enhancing components such as institutional and academic autonomy, rule of law and transparency, stakeholder participation, intelligent management, knowledge governance, and universities’ social responsibility. The findings confirm that integrating intelligence into governance processes can significantly improve decision-making capacity and accountability, offering a technology-driven and participatory governance model for Iranian universities.
Type of Study:
Original |
Subject:
Educational Studies Received: 2025/05/21 | Accepted: 2025/08/11 | Published: 2025/12/1