The Digital Frontier: AI-Enabled Transformations in Higher Education Management
The study examines the current state of AI infrastructure in Uzbekistan, global best practices in AI implementation in higher education management, and presents case studies of AI adoption within Uzbekistan's educational institutions. Using a mixed-methods approach encompassing document analysi...
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Published in | Indonesian Journal of Educational Research and Technology Vol. 4; no. 1; pp. 71 - 88 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Universitas Pendidikan Indonesia
01.03.2024
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Subjects | |
Online Access | Get full text |
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Summary: | The study examines the current state of AI infrastructure in Uzbekistan, global best practices in AI implementation in higher education management, and presents case studies of AI adoption within Uzbekistan's educational institutions. Using a mixed-methods approach encompassing document analysis, interviews, and case studies, the research provides an in-depth understanding of the opportunities and challenges associated with AI integration in higher education management. Findings reveal that while AI infrastructure is in a nascent stage in Uzbekistan, governmental commitment, early AI applications across sectors, and increasing investment in digital infrastructure show promise for the future. However, challenges such as a lack of skilled personnel, the need for substantial infrastructural investments, and issues of data privacy persist. The paper concludes with recommendations for enhancing AI adoption in higher education institutions in Uzbekistan, including policy formulation, investment in digital infrastructure, capacity building, and stakeholder collaboration. The study adds to the growing body of research on AI in higher education, providing insights specific to the context of Uzbekistan. It serves as a guide for policymakers, educators, and administrators looking to navigate the digital revolution in higher education management. |
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ISSN: | 2775-8419 2775-8427 |
DOI: | 10.17509/ijert.v4i1.60367 |