Policymakers’ Accessibility Model for the Development of Metaverse Universities and Development of an Artificial Intelligence-Based Protocol

Document Type : Original Article

Author

Associate Professor, Department of Educational Administration, Mahallat. C, Islamic Azad University, Mahallat, Iran.

Abstract
The main gap currently is the lack of a comprehensive AI-based policymakers’ accessibility model that can provide key information to decision-making institutions in a transparent and real-time manner. Hence, the fundamental question is how to design an AI-based model for policymakers’ accessibility to enable the sustainable and effective development of metaverse universities? The research method was a mixed qualitative research (synthesis research and conversation with GPT chat), the research field included all articles published in the period 2020-2025), as well as the information domain of artificial intelligence and the method of purposive sampling to the point of data saturation, respectively, 33 articles and 23 conversations with artificial intelligence were selected for the study by screening. The method of collecting information was by referring to reputable scientific databases and conversation with GPT chat. Data analysis was based on the classification of open concepts, subcategories and main categories. The triangulation method was used to ensure the validity and validation of the data. In general, the results showed that the accessibility model of policymakers based on artificial intelligence for the sustainable and effective development of metaverse universities consists of five dimensions: "providing infrastructure", "strategic planning", "empowering university presidents", "monitoring education quality", and "information processing". The final protocol based on artificial intelligence includes 5 sections: "needs identification", "resource improvement", "decision support", "trend prediction", and "continuous monitoring".

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Volume 1, Issue 2
Spring 2025
Pages 38-53

  • Receive Date 23 August 2024
  • Revise Date 20 November 2024
  • Accept Date 20 April 2025