ARTIFICIAL INTELLIGENCE (AI) APPROACHES IN HIGHER EDUCATION: A THEORETICAL FOUNDATION FOR THE AI-INTEGRATED TEACHING MANAGEMENT FRAMEWORK / CÁC TIẾP CẬN TRÍ TUỆ NHÂN TẠO (AI) TRONG GIÁO DỤC ĐẠI HỌC: NỀN TẢNG LÝ THUYẾT CHO KHUNG QUẢN LÝ DẠY HỌC TÍCH HỢP AI
Abstract
The rapid advancement of artificial intelligence (AI) is fundamentally transforming teaching, learning, and educational management in the context of digital transformation. This study employed a Systematic Literature Review (SLR) following the PRISMA guidelines to analyze 44 representative studies on AI in higher education published between 2011 and 2026. The findings identify and synthesize six major AI approaches in higher education and reveal their evolutionary progression from learning analytics, AI adoption, and AI governance toward AI literacy and the integration of AI into teaching and learning. Despite the rapid growth of AI research, existing studies have not yet established a comprehensive management framework that systematically integrates educational data, AI technologies, governance, and the entire teaching and learning process. To address this research gap, the study proposes the AI-Integrated Teaching Management Framework (AI-ITMF) based on a systems approach that integrates Systems Theory, the Plan - Do - Check - Act (PDCA) continuous improvement cycle. The proposed framework provides a theoretical foundation and a practical reference for implementing AI in higher education in an effective, responsible, and sustainable manner.
Sự phát triển nhanh chóng của trí tuệ nhân tạo (AI) đang tạo ra những chuyển biến căn bản đối với hoạt động dạy học, học tập và quản lý giáo dục trong bối cảnh chuyển đổi số. Nghiên cứu này sử dụng phương pháp tổng quan tài liệu có hệ thống (Systematic Literature Review - SLR) theo hướng dẫn PRISMA để phân tích 44 nghiên cứu tiêu biểu về AI trong giáo dục đại học được công bố trong giai đoạn 2011-2026. Kết quả nghiên cứu xác định và tổng hợp sáu cách tiếp cận chủ yếu đối với AI trong giáo dục đại học, đồng thời chỉ ra quá trình phát triển từ phân tích học tập, ứng dụng AI và quản trị AI, đến năng lực AI và tích hợp AI vào hoạt động dạy và học. Mặc dù các nghiên cứu về AI trong giáo dục đang gia tăng nhanh chóng, các nghiên cứu hiện có vẫn chưa xây dựng được một khung quản lý toàn diện, có khả năng tích hợp một cách có hệ thống dữ liệu giáo dục, công nghệ AI, quản trị và toàn bộ quá trình dạy học. Nhằm giải quyết khoảng trống nghiên cứu này, nghiên cứu đề xuất Khung Quản lý Dạy học Tích hợp AI (AI-Integrated Teaching Management Framework - AI-ITMF) dựa trên cách tiếp cận hệ thống, kết hợp Lý thuyết Hệ thống (Systems Theory) với chu trình cải tiến liên tục Plan - Do - Check - Act (PDCA). Khung đề xuất cung cấp nền tảng lý thuyết và cơ sở tham chiếu thực tiễn cho việc triển khai AI trong giáo dục đại học theo hướng hiệu quả, có trách nhiệm và bền vững.
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Alajmi, Q., Al-Sharafi, M. A., & Abuali, A. (2020). Smart learning gateways for Omani higher education institutions toward educational technology: Benefits, challenges and solutions. International Journal of Information Technology and Language Studies, 4(1), 12-17. Retrieved from https://www.researchgate.net/publication/341113145_Smart_Learning_Gateways_for_Omani_HEIs_Towards_Educational_Technology_Benefits_Challenges_and_solutions
Bacalso, F. D., Villamor, F. E., Paclipan, C. P., Orquia, C. J. B., Rendon, I. P., Albiso, A. T., & Himang, C. M. (2026). Institutional approaches to generative AI management in higher education: A systematic review. Frontiers in Education, 11. https://doi.org/10.3389/feduc.2026.1814426
Bischof, L., Schön, E. M., Rauschenberger, M., & Neumann, M. (2025). “We need to analyze students’ GenAI use”: Towards an AI adoption framework for higher education. In Proceedings of the 21st International Conference on Web Information Systems and Technologies (pp. 429-438). SciTePress. https://doi.org/10.5220/0013819000003985
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2024). Emergency to evolution: Higher education digital transformation and artificial intelligence adoption. Education Sciences 14(3). https://doi.org/10.3390/educsci14030258
Bùi, T. T., & Trịnh, T. P. D. (2025). Trí tuệ nhân tạo trong GDĐH: Tổng quan hệ thống về xu hướng ứng dụng và khoảng trống nghiên cứu. Tạp chí Giáo dục, 25 (Đặc biệt 9), 55-61.
Chan, M. M., Amado-Salvatierra, H. R., Hernandez-Rizzardini, R., & De La Roca, M. (2023). The potential role of AI-based chatbots in engineering education: Experiences from a teaching perspective. In Frontiers in Education Conference Proceedings (pp. 1-5). https://doi.org/10.1109/FIE58773.2023.10343296
Chu, H., Tu, Y., & Yang, K. (2022). The role and research trends of artificial intelligence in higher education: A systematic review of the 50 most cited papers. Australasian Journal of Educational Technology, 38(3), 22-42. https://doi.org/10.14742/ajet.7526
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, 22. https://doi.org/10.1186/s41239-023-00392-8
Crompton, H., & Song, D. (2021). The potential of artificial intelligence in higher education. Revista Virtual Universidad Católica del Norte, 62, 1-4. https://doi.org/10.35575/rvuen.n62a1
Daniel, S. J. (2024). AI, higher education and institutional leadership. International Review of Education, 6(2). https://doi.org/10.1007/s11159-024-10045-9
Dolah, J., Kharauddin, A., & Amir, N. (2025). A systematic review of artificial intelligence adoption in higher education LMS: Readiness and acceptance (2020-2025).
Dotan, R., Parker, L. S., & Radzilowicz, J. G. (2024). Responsible adoption of generative AI in higher education: Developing a "Points to Consider" approach based on faculty perspectives. arXiv. https://doi.org/10.48550/arXiv.2406.01930
Fütterer, T., Fischer, C., Aleven, V., & Scheiter, K. (2024). Artificial intelligence in education: A systematic review of adoption and implementation in higher education. Computers & Education: Artificial Intelligence, volume 6, https://doi.org/10.1016/j.caeai.2024.100211
García-Peñalvo, F. J. (2023). The digital transformation of universities: Challenges and opportunities of artificial intelligence. Education in the Knowledge Society 8(5). https://doi.org/10.14201/eks.31234
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education. Chief Operating and Strategy Officer, The International Society for Technology in Education (ISTE). https://doi.org/10.58863/20.500.12424/4276068
Hou, Y. (2025). What do we mean by “AI integration”? Toward a typology of integrating artificial intelligence in higher education. Higher Education (2025). https://doi.org/10.1007/s10734-025-01603-z
Ifenthaler, D., & Yau, J. Y. K. (2020). Utilising learning analytics to support study success in higher education. Educational Technology Research and Development, (68). https://doi.org/10.1007/s11423-020-09788-z
Kasneci, E., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103. https://doi.org/10.1016/j.lindif.2023.102274
Katsamakas, E., Pavlov, O. V., & Saklad, R. (2024). Artificial intelligence and the transformation of higher education institutions: A systems approach. Sustainability, 16(14), 6118. https://doi.org/10.3390/su16146118
Khalil, M., Prinsloo, P., & Slade, S. (2024). Responsible learning analytics and AI in higher education: Governance, ethics and decision-making. British Journal of Educational Technology 55(4). https://doi.org/10.1111/bjet.13479
Kitchenham, B., & Charters, S. (2007). Guidelines for Performing Systematic Literature Reviews in Software Engineering. EBSE Technical Report. https://doi.org/reference/ReferencesPapers?ReferenceID=1555797
Liew, Y. Z., Tan, A. H. P., Yap, E. H., Lim, C. S., Abdul Majeed, A. P. P., Zhu, Y., Chen, W., Chen, S.-H., & Lo, J. Y. T. (2024). Systems thinking on artificial intelligence integration into higher education: Causal loops. In Artificial Intelligence - Emerging Trends and Applications. IntechOpen. https://doi.org/10.5772/intechopen.1008246
Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. UCL Institute of Education Press. https://doi.org/10.14324/111.9781800084209
Mah, D. K., & Groß, N. (2024). Artificial intelligence in higher education: Exploring faculty use, self-efficacy, distinct profiles, and professional development needs. International Journal of Educational Technology in Higher Education, 21(58). https://doi.org/10.1186/s41239-024-00490-1
McDonald, N., Johri, A., Ali, A., & Hingle, A. (2024). Generative AI in higher education: A global perspective of institutional adoption policies and guidelines. Computers and Education: Artificial Intelligence, vol 8. https://doi.org/10.1016/j.caeai.2024.100348
Neumann, M., Bischof, L., Rauschenberger, M., & Schön, E.-M. (2026). A systematic AI adoption framework for higher education: From student GenAI usage to institutional integration. arXiv. https://doi.org/10.48550/arXiv.2604.22030
OECD. (2021). OECD digital education outlook 2021: Pushing the frontiers with artificial intelligence, blockchain and robots. OECD Publishing. https://doi.org/10.1787/589b283f-en
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011–2020. Education and Information Technologies, 27, 7893-7925. https://doi.org/10.1007/s10639-022-10925-9
Page, M. J., McKenzie, J. E., Bossuyt, P. M., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Perera, P., Kulathunga, V. K., Perera, N. N., Gunarathna, A., Jayasinghe, P. S. K., & Rajamanthri, L. (2026). Adoption of ChatGPT in higher education: A systematic literature review of lecturers’ perspective based on UTAUT2. Asian Education and Development Studies, 15(1), 89-113. https://doi.org/10.1108/AEDS-11-2024-0275
Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(22), 1-13. https://doi.org/10.1186/s41039-017-0062-8
QS. (2025). AI Capability Framework. QS Higher Education. https://www.aicapability.org
Rizki, I. A., & Daoud, R. (2025). Generative artificial intelligence in higher education: Review of institutional policies and practices across New Zealand. New Zealand Journal of Educational Studies. https://doi.org/10.1007/s40841-025-00417-y
Robert, J., & McCormack, M. (2024). 2024 EDUCAUSE Action Plan: AI Policies and Guidelines. EDUCAUSE. Retrieved from https://www.educause.edu/research/2024/2024-educause-action-plan-ai-policies-and-guidelines
Rojas, M. P., & Chiappe, A. (2024). Artificial intelligence and digital ecosystems in education: A review. TechTrends and Knowledge Learning, 29, 2153-2170. https://doi.org/10.1007/s10758-024-09732-7
Salas-Pilco, S., & Yang, Y. (2022). Artificial intelligence applications in higher education in Latin America: A systematic review. International Journal of Educational Technology in Higher Education, 19(21), 1-20. https://doi.org/10.1186/S41239-022-00326-W
Sánchez-Prieto, J. C., Olmos-Migueláñez, S., & García-Peñalvo, F. J. (2024). Smart universities and artificial intelligence: Institutional transformation models. Education and Information Technologies, 6(4). https://doi.org/10.1007/s10639-024-12678-3
Selwyn, N., Hillman, T., Eynon, R., Ferreira, G., Knox, J., Macgilchrist, F., & Sancho-Gil, J. M. (2023). Artificial intelligence and the future of higher education. Centre for Research in Digital Education, University of Edinburgh. Retrieved from https://www.research.ed.ac.uk/en/publications/artificial-intelligence-and-the-future-of-higher-education
Shailendra, S., Kadel, R., & Sharma, A. (2024). Framework for adoption of generative artificial intelligence (GenAI) in education. IEEE Transactions on Education, 67(5), 777-785. https://doi.org/10.1109/TE.2024.3432101
Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30-40. https://er.educause.edu/articles/2011/9/penetrating-the-fog-analytics-in-learning-and-education
Southworth, J., Migliaccio, K., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4. https://doi.org/10.1016/j.caeai.2023.100127
Tlili, A., et al. (2023). What if the devil is my guardian angel? ChatGPT as a case study of generative artificial intelligence in education. Smart Learning Environments, 10. https://doi.org/10.1186/s40561-023-00237-x
UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO. Retrieved from https://www.unesco.org/en/articles/ai-and-education-guidance-policy-makers
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. Retrieved from https://unesdoc.unesco.org/ark:/48223/pf0000386693
Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223-235. https://doi.org/10.1080/17439884.2020.1798995
Wu, C., Zhang, H., & Carroll, J. M. (2024). AI governance in higher education: Case studies of guidance at Big Ten universities. arXiv. https://doi.org/10.48550/arXiv.2409.02017
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(39), 1-27. https://doi.org/10.1186/s41239-019-0171-0
DOI: http://dx.doi.org/10.46827/ejes.v13i8.6967
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