Cloud-Powered Higher Education: AI-Driven Student Success and Digital Learning Transformatio
University of South Florida, USA.
Review
Open Access Research Journal of Engineering and Technology, 2025, 08(02), 056-072.
Article DOI: 10.53022/oarjet.2025.8.2.0049
Publication history:
Received on 18 March 2025; revised on 26 April 2025; accepted on 29 April 2025
Abstract:
Cloud-powered higher education is undergoing a transformative evolution through the integration of artificial intelligence technologies. This comprehensive article examines how the AI-powered Higher Education Model (AHEM) enhances educational experiences through four interconnected layers: Personalized Adaptive Learning, Predictive Academic Success Models, Automated Student Support Services, and AI-driven Course Management. Unlike existing educational technology frameworks that focus primarily on classroom applications or faculty competencies, AHEM provides a novel, integrated approach for conceptualizing and implementing AI across the entire educational enterprise, addressing both technological and organizational dimensions of institutional transformation. The article investigates how leading institutions have implemented these technologies to improve student success metrics and address persistent challenges in education. It analyzes critical considerations regarding cybersecurity and data privacy, including regulatory compliance requirements, security architecture best practices, and ethical AI governance frameworks. Despite promising outcomes, institutions face significant implementation challenges related to technical infrastructure limitations, faculty adaptation, and algorithmic bias concerns. Looking toward the future, the article examines emerging capabilities such as immersive learning environments, cross-institutional collaboration platforms, and lifelong learning ecosystems that will further transform higher education. Throughout, the focus remains on balancing technological innovation with ethical responsibility to enhance educational access and effectiveness.
Keywords:
AI-Powered Education; Cloud Computing; Personalized Learning; Predictive Analytics; Educational Technology
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Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0