Navigating the future of higher education in Saudi Arabia: implementing AI, machine learning, and big data for sustainable university development

被引:0
|
作者
Muhammad Adnan Khan [1 ]
Abdur Rehman [2 ]
Asghar Ali Shah [3 ]
Sagheer Abbas [4 ]
Meshal Alharbi [5 ]
Munir Ahmad [6 ]
Taher M. Ghazal [7 ]
机构
[1] Skyline University College,School of Computing
[2] Riphah International University,Riphah School of Computing & Innovation, Faculty of Computing
[3] Gachon University,Department of Software, Faculty of Artificial Intelligence and Software
[4] Chitkara University,Chitkara University Institute of Engineering and Technology
[5] Applied Science Private University,Applied Science Research Center
[6] National College of Business Administration and Economics,Department of Computer Sciences
[7] Kateb University,Department of Computer Science
[8] Prince Mohammad Bin Fahd University,Department of Computer Science
[9] Prince Sattam Bin Abdulaziz University,College of Computer Engineering and Sciences
[10] University College,Department of Networks and Cybersecurity, Hourani Center for Applied Scientific Research
[11] Korea University,undefined
[12] Al-Ahliyya Amman University,undefined
来源
Discover Sustainability | / 6卷 / 1期
关键词
Big data; Artificial intelligence; Sustainability; Higher education; Educational policy;
D O I
10.1007/s43621-025-01388-2
中图分类号
学科分类号
摘要
Higher education in the Gulf Cooperation Council (GCC) is going through big changes as universities try to meet the needs of 21st-century students and society. New technologies give both opportunities and challenges for Arab region universities to develop sustainably. This paper looks at ways to successfully use artificial intelligence (AI) and big data analytics in Saudi higher education while supporting long-term growth. First, it analyzes current trends in Saudi university enrollment, programs, and facilities to identify areas for improvement. It then explores the potential benefits of AI and big data, like personalized learning, better campus operations, and data-driven decision-making. However, there are also risks like high costs, privacy concerns, and lack of qualified people that need to be addressed. Recommendations are given for overcoming barriers to adopting these technologies including getting stakeholders involved, developing customized AI solutions, and starting tech-focused academic programs. The paper also discusses long-term impacts on faculty roles, student experiences, and financial sustainability. In the end, carefully implemented AI and big data can improve learning, and student services, and cut costs but require careful change management. By balancing cutting-edge tech with local needs, GCC universities can provide innovative education while upholding traditions and values. This study explores how AI, Machine Learning, and Big Data can enhance sustainability and effectiveness in Saudi higher education, aligning with relevant UN Sustainable Development Goals. Results highlight AI-driven insights that improve institutional decision-making and educational equity. Results indicate that among the predictive models tested, Random Forest achieved the highest accuracy in student performance prediction, with an R2 score of 0.85.
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