Volume 5 • Issue 2 • PP: 4 3– 47 • 2026
How Should Higher Education respond when AI enters the Classroom?
Open Access & Copyright
© 2026 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
View PDF Abstract
Driven by the global informatization wave, AI technology is leading a profound change in education, and the traditional higher education model is facing unprecedented opportunities and challenges. Firstly, the advantages of the comprehensive integration of “AI+ Education” are sorted out from the two aspects of students and teachers. Secondly, it analyzes the transformation of teachers from classroom manager to learning ecological designer from three aspects: education personalization and fairness, man-machine teaching collaboration and interdisciplinary scene innovation. Next, the construction of student evaluation system is discussed from four dimensions of thinking visualization. Finally, the author expounds the characteristics of the teaching profession that cannot be replaced by AI.
Keywords
References
[1]. Lehlohonolo Kurata, Musa Adekunle Ayanwale, Rethabile Rosemary Molefi, & Tajudeen Sanni. (2025). Teaching religious studies with artificial intelligence: A qualitative analysis of Lesotho secondary schools teachers’ perceptions. International Journal of Educational Research Open, 8, 100417.
[2]. Attila Kovari. (2025). A systematic review of AIpowered collaborative learning in higher education: Trends and outcomes from the last decade. Social Sciences & Humanities Open, 11, 101335.
[3]. Torbjorn Netland, Oliver von Dzengelevski, Katalin Tesch, & Daniel Kwasnitschka. (2025). Comparing human-made and AI-generated teaching videos: An experimental study on learning effects. Computers & Education, 224, 104164.
[4]. Aiping Shao, Zhi Lu, Bu Zhong, Stephanie Q. Liu, & Wei Lu. (2025). Human touch vs. AI tech: Under- standing user preferences in the future of education. Computers in Human Behavior, 164, 108492.
[5]. Feng Hsu Wang. (2022). A feasible study of a deep learning model supporting human–machine collaborative learning of object-oriented programming. IEEE Transactions on Learning Technologies, 17, 413–427.
[6]. LiuJie Xu, Jing Wu, JingDong Zhu, & Ling Chen. (2025). Effects of AI-assisted dance skills teaching, evaluation and visual feedback on dance students’ learning performance, motivation and self-efficacy. International Journal of Human-Computer Studies, 195, 103410.
[7]. Clare Baek, Amara Tate, & Mark Warschauer. (2024). “ChatGPT seems too good to be true”: College students’ use and perceptions of generative AI. Computers and Education: Artificial Intelligence, 7, 100294.
[8]. Can ZhaoJian & Tong Yu. (2024). Relationship between teacher’s ability model and students’ behavior based on emotion-behavior relevance theory and artificial intelligence technology under the background of curriculum ideological and political education. Learning and Motivation, 88, 102040.
[9]. Charlotte Haugland Sundkvist & Ellen M. Kulset. (2024). Teaching accounting in the era of ChatGPT – The student perspective. Journal of Accounting Education, 69, 100932.
[10]. Rachel Moylan, Jillianne Code, & Heather O’Brien. (2025). Teaching and AI in the postdigital age: Learning from teachers’ perspectives. Teaching and Teacher Education, 153, 104851.
[11]. Michael J. Reiss. (2021). The use of AI in education: Practicalities and ethical considerations. London Review of Education, 19(1), 1–14.
[12]. YuFen Yang, Christine Chifen Tseng, & SiaoCing Lai. (2024). Enhancing teachers’ self-efficacy beliefs in AIbased technology integration into English speaking teaching through a professional development program. Teaching and Teacher Education, 144, 104582.
[13]. Cecilia Ka Yuk Chan & Louisa H. Y. Tsi. (2024). Will generative AI replace teachers in higher education? A study of teacher and student perceptions. Studies in Educational Evaluation, 83, 101395.
[14]. Lihang Guan, Yue Zhang, & Mingyue Michelle Gu. (2025). Pre-service teachers’ preparedness for AIintegrated education: An investigation from perceptions, capabilities, and teachers’ identity changes. Computers and Education: Artificial Intelligence, 8, 100341.
[15]. Adrian John Davis. (2024). AI rising in higher education: Opportunities, risks and limitations. Asian Education and Development Studies, 13(4), 307–319.
[16]. Judit Martinez-Moreno & Petko D. (2024). What motivates future teachers? The influence of artificial intelligence on student teachers’ career choice. Computers and Education: Artificial Intelligence, 7, 100296.
Cite This Article
Choose your preferred format
Publisher's Note
The statements, opinions, and data presented in this article are solely those of the author(s) and do not necessarily represent those of ASPG, the journal, or its editors. ASPG and the editors disclaim responsibility for any harm arising from the use of any ideas, methods, instructions, or products described in this article, to the fullest extent permitted by applicable law.