University Teaching in the Era of Digital Intelligence: A Review and Outlook
DOI:
https://doi.org/10.62051/jedss.v1n3.07Keywords:
Digital Intelligence Era, Artificial Intelligence, University teaching, Digital intelligence technologyAbstract
The contemporary world is in an era of deep integration of digital intelligence. A new wave of digital intelligence technologies, represented by generative artificial intelligence, is accelerating, exerting a profound impact on the logic and form of higher education: on the one hand, the deep empowerment of digital intelligence technologies has transformed the educational logic of universities; on the other hand, data has become a new educational resource, and intelligent algorithms as well as generative models are continuously permeating key dimensions such as knowledge acquisition, learning process management, and educational evaluation, thereby reshaping the fundamental approaches to university teaching. This paper aims to review domestic and international theories and practices concerning university teaching in the era of digital intelligence. On this basis, it outlines potential directions for future development, providing theoretical support and path references for the reform of university teaching.
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[1] Eshet, Y. (2004). Digital literacy: A conceptual framework for survival skills in the digital era. Journal of Educational Multimedia and Hypermedia, 13(1), 93–106.
[2] Schneider, P., Walters, W. P., Plowright, A. T., et al. (2020). Rethinking drug design in the artificial intelligence era. Nature Reviews Drug Discovery, 19(5), 353–364.
[3] Foresti, R., Rossi, S., Magnani, M., et al. (2020). Smart society and artificial intelligence: big data scheduling and the global standard method applied to smart maintenance. Engineering, 6(7), 835–846.
[4] UNESCO P. (2021) Reimagining our futures together: A new social contract for education[M]. Paris, France: Educational and Cultural Organization of the United Nations.
[5] Smith, M. D. (2023). The abundant university: remaking higher education for a digital world. MIT Press.
[6] Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22.
[7] Zhou, Q., & Wen, X. Y. (2020). Practical Forms of "AI+Teacher" Collaborative Teaching in the Age of Intelligence. Journal of Distance Education, 38(2), 37–45.
[8] Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., et al. (2022). The impact of a virtual teaching assistant (chatbot) on students' learning in Ghanaian higher education. International Journal of Educational Technology in Higher Education, 19(1), 57.
[9] Stanyon, R., Martello, E., Kainth, M., et al. (2022). Demo of Graide: AI powered assistive grading engine. In Proceedings of the Ninth ACM Conference on Learning@ Scale (pp. 466–468).
[10] Hussain, A. (2024). Ada and FirstPass, Bolton College's digital assistants for students, teachers and campus support teams [Master’s thesis]. University of Bolton.
[11] Demszky, D., Liu, J., Hill, H. C., et al. (2023). Improving Teachers' Questioning Quality through Automated Feedback: A Mixed-Methods Randomized Controlled Trial in Brick-and-Mortar Classrooms (EdWorkingPaper No. 23-875). Annenberg Institute for School Reform at Brown University.
[12] Owoc, M. L., Sawicka, A., & Weichbroth, P. (2019). Artificial intelligence technologies in education: benefits, challenges and strategies of implementation. In IFIP international workshop on artificial intelligence for knowledge management (pp. 37–58). Springer International Publishing.
[13] Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review (Online).
[14] Zhou, Y. R. (2019). The Dual Dilemmas and Solutions of University Teaching Evaluation Criteria. Higher Education Research, 40(10), 75–81.
[15] Yang, Y., Hu, S. S., Xing, H. G., et al. (2018). Reference and Reflection: The Application of Learning Analytics in Foreign Higher Education Fields. Modern Educational Technology, 28(2), 107–112.
[16] Arnold, K. E., & Pistilli, M. D. (2012). Course signals at Purdue: Using learning analytics to increase student success. In Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 267–270).
[17] Papamitsiou, Z., & Economides, A. A. (2014). Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence. Journal of Educational Technology & Society, 17(4), 49–64.
[18] Jia, J. Y., Le, H. X., Zhang, Y. Y., et al. (2023). Design of an Intelligent Evaluation and Tutoring System Based on Big Data Mining. China Educational Technology, (3), 112–119.
[19] Hussin, A. A. (2018). Education 4.0 made simple: Ideas for teaching. International Journal of Education and Literacy Studies, 6(3), 92–98.
[20] Chaka, C. (2022). Is Education 4.0 a sufficient innovative, and disruptive educational trend to promote sustainable open education for higher education institutions? A review of literature trends. In Frontiers in Education (Vol. 7, Article 824976). Frontiers Media SA.
[21] Ji, B., Zhang, Y. F., Lv, W., et al. (2019). Characteristics and Implications of the "Student-Centered" New Talent Cultivation Model in the United States: An Analysis Based on Olin, Minerva, and Stanford 2025. Research on Educational Development, 39(23), 71–77.
[22] Chai, L. Q. (2025). Empowering Higher Education through Digital Transformation: Exploration and Experience of Deakin University in Australia. Higher Education Exploration, (4), 92–100.
[23] Xie, J., & He, J. (2022). The Transformation Landscape of Teaching and Research Offices in the 'Smart+' Era: Virtual Teaching and Research Offices - Taking the Virtual Teaching and Research Office for the 'Principles of Electric Circuits' Course at Tsinghua University as an Example. Modern Educational Technology, 32(5), 102–109.
[24] Biesta, G. J. J. (2015). Good education in an age of measurement: Ethics, politics, democracy. Routledge.
[25] Bearman, M., Ryan, J., & Ajjawi, R. (2023). Discourses of artificial intelligence in higher education: A critical literature review. Higher Education, 86(2), 369–385.
[26] Zhang, C. L., & Li, A. (2025). The Logic and Path of Data Element Empowerment for University Teaching from the Perspective of Digitalization and Intelligentization. Journal of Chinese University Teaching, (8), 38–46.
[27] Yang, Q. W., & Tang, Q. (2025). Generative Artificial Intelligence Empowers Graduate Education: Theoretical Logic, Legal Risks, and Governance Paths. Journal of Graduate Education Research, (2), 26–33.
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