The AI Wave Is Coming: How Should University Classrooms Be

Reimagined?

Juan Chen1,*

1 School of Resources, Environment and Safety Engineering, Hunan University of Science and Technology, Hunan Pro, Xiangtan

411201, China

Received: July 02, 2026 Revised: August 04, 2026 A c ⋆c e Cptoerdr:e spAoungduinstg au2t0h, or2026

ABSTRACT

Artificial intelligence (AI) technology is rapidly penetrating higher education, bringing profound transformations

to university classroom instruction. However, existing research has paid limited attention to practical implementation

pathways within real teaching contexts, leaving frontline educators without systematic operational guidance.

Grounded in daily classroom practices, this paper aims to provide teachers with replicable and scalable strategies for

Human-AI collaborative teaching, along with practical guidelines for applying AI tools. The study first outlines the

contemporary context and driving forces behind integrating AI into university classrooms. It then systematically

analyzes core challenges in current teaching practices—such as rigid teaching models, limited educational resources,

inefficient classroom interaction, monotonous assessment methods, and excessive workloads for instructors. Finally,

it proposes a comprehensive reform framework and implementation pathway for AI-enhanced university teaching,

focusing on six key areas: reconfiguring teaching models, building intelligent resource-sharing systems, fostering

student agency, establishing dynamic, whole-process evaluation mechanisms, supporting teachers in reducing workload

and improving efficiency, and mitigating ethical risks associated with AI applications. Emphasizing practicality

and feasibility, this paper offers frontline educators actionable solutions to navigate the transition toward intelligent

education.

Keywords: Human-AI Co-teaching Precision Teaching Dynamic Evaluation Reimagined

1. INTRODUCTION

1.1 Research Background

Over the past decade, the pace and depth at which artificial intelligence

(AI) has entered the field of higher education have

exceeded the expectations of most people. From intelligent

tutoring systems and learning analytics technologies, to the

emergence of ChatGPT in late 2022, AI has gradually moved

from being an “add-on” to teaching to becoming an integral

part of university lesson planning, teaching, assignments, and

exams. In a systematic review published by Crompton and

Burke [1] in 2023, they summarized 138 empirical studies

conducted between 2016 and 2022, finding that the number

of AI education research papers increased by two to three

times between 2021 and 2022, with undergraduate students

becoming the main research subject group. This growth rate

itself indicates one thing: university teaching is standing

at an unavoidable crossroads. Bond et al. [2] conducted a

more thorough study in 2024, conducting a meta-systematic

review of 66 existing reviews, and concluded that the deficiency

in this field is not the number of papers, but rather

“ethical awareness, interdisciplinary collaboration, and academic

rigor”, with most studies focusing on the description

of technical functions and providing far insufficient attention