Promoting Teaching and Learning through the Application of Artificial Intelligence Technology in Higher Education Management in the Dimension of Local Cultural Development
Abstract
The application of artificial intelligence (AI) in higher education management in local cultural development improves efficiency by automating administrative tasks, improving resource allocation, and improving student support systems. It also enables informed decision-making, ensuring personalized learning experiences and better academic performance. Therefore, this study aimed to study the promotion of teaching and learning by applying AI technology in higher education management in the dimension of local cultural development. This study examined academic literature on AI that can be applied to learning management and education management in the dimension of local cultural development. The results of the study found that the use of AI in education is transforming the learning system by emphasizing privacy and flexibility through adaptive learning platforms, intelligent tutoring systems, and student data analytics, which help students receive content that is appropriate for their abilities and needs. AI is also being used in education management, such as automated grading systems, student support via chatbots, and resource allocation within universities, resulting in greater efficiency, reduced teacher workload, and easier access for students to information. However, the challenges of AI in education include ethical issues, data privacy, and algorithmic bias, which may lead to inequities in access to education. Strict governance and transparent and fair AI system design are needed to ensure that the benefits of technology are universal and sustainable. In addition, through digitization, individualized learning systems, and cultural diversity, artificial intelligence (AI) in higher education plays a vital role in preserving and advancing local cultures by improving community engagement and addressing ethical issues to ensure sustainable and equitable technological integration. In conclusion, AI in education can improve personalized learning and enhance administrative efficiency through automation, but it still faces ethical challenges and equity in access to information, which requires appropriate governance measures.
Downloads
Article Details
How to Cite
Section
Research Articles
Copyright & License
Copyright (c) 2025 Arts and Culture Journal of the Lower Moon River
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All articles published open access under the CC BY-NC-ND 4.0 license will be immediately and permanently free for everyone to read, download, copy, distribute, print, search, or link to articles free of charge. Use of the articles is permitted for non-commercial purposes only and without modifications. Access does not require prior permission from the publisher or the author, provided that the original publication is appropriately and adequately cited.
References
Akinwalere, S. N., & Ivanov, V. (2022). Artificial Intelligence in Higher Education : Challenges and Opportunities. Border Crossing, 12(1), 1–15. https://doi.org/10.33182/bc.v12i1.2015.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People - An Ethical Framework for a Good AI Society : Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689 – 707. https://doi.org/10.1007/s11023-018-9482-5.
Hsu, Y. C., Huang, T. H. ‘K.,’ Verma, H., Mauri, A., Nourbakhsh, I., & Bozzon, A. (2022). Empowering Local Communities Using Artificial Intelligence. Patterns, 3(3), 100449. https://doi.org/10.1016/j.patter.2022.100449.
Huang, R., Spector, J. M., & Yang, J. (2019). Educational Technology : A Primer for the 21st Century. Springer Singapore. https://doi.org/10.1007/978-981-13-6643-7.
Kezar, A. J., & Holcombe, E. M. (2017). Shared Leadership in Higher Education : Important Lessons from Research and Practice. American Council on Education. https://www.acenet.edu/Documents/Shared-Leadership-in-Higher-Education.pdf.
Long, P. D., & Siemens, G. (2014). Penetrating the Fog : Analytics in Learning and Education. TD Tecnologie Didattiche, 22(3), 132 - 137. https://doi.org/10.17471/2499-4324/195. (In Italiano)
Marginson, S. (2016). The Dream Is Over : The Crisis of Clark Kerr’s California Idea of Higher Education. University of California Press. https://doi.org/10.1525/luminos.17.
Patton, S. (2024). AI Meets Archives : The Future of Machine Learning in Cultural Heritage. Council on Library and Information Resources. https://www.clir.org/2024/10/ai-meets-archives-the-future-of-machine-learning-in-cultural-heritage.
Robert, J. (2024). The Future of AI in Higher Education. https://www.educause.edu/ecar/research-publications/2024/2024-educause-ai-landscape-study/the-future-of-ai-in-higher-education.
Taşkın, M. (2025). Artificial Intelligence in Personalized Education : Enhancing Learning Outcomes Through Adaptive Technologies and Data-Driven Insights. Human Computer Interaction, 8(1), 173. https://doi.org/10.62802/ygye0506.
The Culture Factor. (n.d.). Does Artificial Intelligence Have a Culture Problem?. https://news.theculturefactor.com/news/does-artificial-intelligence-have-a-culture-problem.
VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic Review of Research on Artificial Intelligence Applications in Higher Education - Where are the Educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0.
