


































Global Research in Higher Education 
ISSN 2576-196X (Print) ISSN 2576-1951 (Online) 

Vol. 8, No. 3, 2025 

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1 

 

Original Paper 

Research on Teaching Reform in Higher Education under the 

Perspective of Digital Transformation 

Xinpeng Xu
1
, Yankai Fu

2
 & Xiaolei Qian

1 

1
 School of International Finance and Trade, Sichuan International Studies University, Chongqing, 

China 

2
 Chongqing College of Humanities, Science & Technology, Chongqing, China 

 

Received: July 10, 2025         Accepted: July 30, 2025        Online Published: August 16, 2025 

doi:10.22158/grhe.v8n3p1                    URL:http://dx.doi.org/10.22158/grhe.v8n3p1 

 

Abstract 

Against the backdrop of the global digital wave and the national innovation-driven strategy, Higher 

education teaching system is faced with the demand of profound transformation. Basing on the 

multi-dimensional perspective of policy guidance, industrial transformation and the intrinsic driving 

force of education, this research systematically dissects the urgency of teaching reform in higher 

education and the existing major contradiction from the perspective on digital transformation. The 

research finds that value cognition bias, institutional and mechanism deficiencies, and the gap in 

practical ability constitute the core obstacles. Through constructing a four-dimensional collaborative 

framework of “value-subject-tool-system”, proposing the reshape of teaching objectives, energize 

teachers’ development. Optimizing the Implementation Pathways of Governance Mechanisms. This 

research highlights the principle of being student-centered and technology-empowered in optimizing 

governance mechanisms. It proposes advancing the digital competence of faculty, upgrading intelligent 

infrastructure, and ensuring institutional innovation to support this transformation. The goal is to 

facilitate a shift in teaching practices from passive adaptation to proactive leadership. Ultimately, the 

study aims to provide both theoretical reference and practical guidance for building a high-quality 

education system that supports Chinese-style modernization. 

Keywords 

higher education, digital transformation, teaching reform, digital literacy, governance system 

 

 

 



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This paper is a research outcome of the Chongqing Municipal Education Commission’s teaching 

reform project: Research on Teaching Reform in Higher Education under the Perspective of Digital 

Transformation (Project No. 233306). Research on the Construction of a Systematic Training Model 

for Master’s Degree Programs in International Business under the New Liberal Arts Perspective 

(yjsjg202209). 

 

The global digital technology revolution is profoundly reshaping industrial structures, knowledge 

systems, and the educational ecosystem. In July 2024, the Third Plenary Session of the 20th Central 

Committee of the Communist Party of China adopted the Decision of the CPC Central Committee on 

Further Deepening Reform Comprehensively to Advance Chinese Modernization. For the first time, it 

identified the “coordinated reform of systems and mechanisms for education, science and technology, 

and talent” as a national strategy. It clearly outlined key tasks such as deepening reforms in talent 

cultivation approaches, school operation models, governance systems, and support mechanisms, and 

called for the “extraordinary development of urgently needed disciplines and specialties.” This strategic 

initiative is driven by a compelling practical necessity. As the world’s largest industrial nation, 

contributing 30.7% of global manufacturing value added, China still faces technological bottlenecks in 

35 key areas such as chip manufacturing and bio pharmaceuticals, along with a talent gap of 12 million 

in strategic emerging industries. Meanwhile, the digital-intelligent revolution is transforming 

“algorithms and data” into new forms of labor, challenging the traditional discipline-based academic 

system with a knowledge production paradigm driven by “intelligent agents.” As the primary base for 

cultivating innovative talent, higher education institutions are urgently confronted with outdated 

academic structures and rigid teaching models. Against this backdrop, exploring how digital 

transformation can drive structural reforms in higher education teaching holds significant theoretical 

and practical value for meeting national strategic needs and building an independent and robust talent 

development system. 

 

1. The Urgency of Teaching Reform in Higher Education from the Perspective of Digital 

Transformation  

The digital transformation of higher education has evolved from a developmental option to a strategic 

necessity at the national level. Its urgency arises from systemic pressures formed by three interrelated 

dimensions: the imperative of international competition, the drive of national strategies, and the 

internal demands of education itself. 

1.1 The Profound Transformation of Global Education Paradigms Creates an External Forcing 

Mechanism  

The strategic restructuring of international competition patterns is compelling higher education to 

accelerate its transformation. The World Economic Forum’s Schools of the Future Report established 



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the Education 4.0 framework, identifying adaptive learning systems, human-machine collaboration 

capabilities, and digital ethics literacy as the core competency matrix for future talent, marking the 

entry of global education into a new intelligent phase. UNESCO’s Global Declaration on Digital 

Learning Transformation further promotes the construction of an “inclusive digital education 

ecosystem,” requiring member states to formulate national strategies. Developed countries have already 

launched systematic plans: the EU’s “Digital Education Action Plan 2021-2027” invests €6.2 billion to 

build a digital resilience system for education, while the U.S. CHIPS and Science Act allocates special 

funds to train 65,000 advanced manufacturing engineers. This strategic competition exerts dual 

pressure on China: on one hand, key technology sectors face restrictions on talent mobility, such as the 

U.S. “Sensitive Fields Research Restriction Plan,” which hinders the return of overseas high-level 

talent; on the other hand, developed countries are competing for educational discourse power through 

technical standards like IEEE’s Ethical Standards for Educational AI and the EU’s Digital Education 

Content Certification Framework. Universities lacking in-depth digital transformation will continue to 

be marginalized in global academic resource allocation and talent competition. 

1.2 Systematic National Strategic Deployment Imposes Binding Imperatives for Digital Transformation 

China has positioned digitalization as the core engine for modernizing its education system. The 

Outline for Building a Strong Education Nation (2024-2035) issued by the CPC Central Committee and 

the State Council for the first time listed “AI-powered educational transformation” as a key project in 

the new educational infrastructure, setting a clear goal to establish a comprehensive digital education 

system covering all academic stages by 2030. The Ministry of Education’s Three-Year Action Plan for 

Digital Transformation in Education further proposed the “three universal coverage” objectives: 

teaching applications for all teachers, learning applications for all students, and digital campuses for all 

schools. Supporting initiatives include: the National Development and Reform Commission’s “New 

Educational Infrastructure” project focusing on 5G+smart education, the Ministry of Science and 

Technology’s 2.36 billion yuan “Smart Education” R&D dedicated to educational large-scale models, 

and the Ministry of Industry and Information Technology’s “Smart Educational Equipment” action 

plan. This top-level design not only reflects policy direction but also translates into mandatory resource 

allocation constraints—the success of digital transformation directly impacts universities' ability to 

secure national funding and development opportunities. 

1.3 The Tension between Educational Scale Expansion and Quality Enhancement Drives Endogenous 

Momentum 

The fundamental confronting the connotative development of higher education urgently requires digital 

solutions. With China’s gross higher education enrollment rate reaching 62.7% and 48 universities 

exceeding one million students, traditional teaching models face severe challenges: 68.3% of classes 

are large-format lectures, while an 18:1 student-faculty ratio severely limits personalized guidance. The 

fivefold disparity in per-student digital resource investment between eastern and western universities 



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(4,200 yuan/year at 985 institutions vs. 800 yuan/year at local colleges) exacerbates educational 

inequality. More critically, structural misalignment exists between talent supply and industry demand: 

while the integrated circuit industry faces a 250,000 talent shortage, related majors graduate only 

80,000 students annually, and smart manufacturing job remains below 50%. As McKinsey research 

confirms that 45% of traditional industry workers require digital skills upgrading, universities must 

reconstruct teaching content and methods through digital transformation to resolve the dual of 

mass-scale cultivation versus personalized empowerment, and knowledge delivery versus competency 

development. 

 

2. Major Challenges of Teaching Reform in Higher Education under the Perspective of Digital 

Transformation 

2.1 Systemic Deviations in Value Perception Restrict the Direction of Transformation 

Cognitive dissonance characterized by strategic misalignment and the absence of ethical risk 

management constitutes a primary barrier to effective transformation. A prevailing misconception 

among institutional administrators equates digital transformation with hardware procurement. 

According to a survey by the Ministry of Education, only 32% of higher education institutions have 

integrated digital literacy into their curricula, and over 70% of these offer it solely as elective courses. 

Moreover, a disproportionate share of digitalization budgets is allocated to equipment purchases, while 

investment in faculty training remains minimal. At a deeper level, the misidentification of actors 

exacerbates the issue: a considerable proportion of educators exhibit “technological replacement 

anxiety,” fearing the erosion of pedagogical authority by artificial intelligence. The lack of ethical 

governance mechanisms—evident in the widespread absence of algorithm ethics committees—has led 

to recurrent incidents of data misuse. These contradictions reflect a fundamental disjunction between 

educational purpose and technological tools, and the absence of a shared educational philosophy 

grounded in “human-machine collaboration.” 

2.2 Structural Deficiencies in Institutional Mechanisms Impede Systemic Advancement 

Fragmented data governance and outdated evaluation systems have become institutional bottlenecks. 

On average, universities operate more than ten isolated digital systems, with data interoperability 

between departments below 30%. Critical systems for teaching and research management still rely on 

manually exported Excel spreadsheets, consuming substantial administrative resources annually. The 

lack of standardized data frameworks results in incomplete recording of basic information such as 

student IDs and names, with high redundancy in student data entry. Evaluation systems remain mired 

in path dependency, emphasizing quantitative metrics such as publication counts and research funding 

while neglecting core indicators of transformation—such as smart classroom utilization and learning 

analytics. This misalignment in resource allocation manifests in underutilization of digital 

infrastructure; for instance, in some institutions, virtual simulation laboratories operate at under 20% 



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capacity due to the absence of performance-based incentives. Consequently, investments in digital 

transformation fail to yield commensurate improvements in educational effectiveness. 

2.3 Capability Gaps at the Operational Level Undermine the Effectiveness of Transformation 

Superficial pedagogical reforms and faculty capacity deficits hinder the practical efficacy of digital 

transformation. Technological applications remain at a rudimentary stage: utilization rates of intelligent 

grouping systems and real-time learning diagnostics are low. In many institutions, “smart classrooms” 

are limited to upgraded projection equipment, with over 70% of renovated classrooms used primarily 

for PowerPoint presentations. Pedagogical innovation lags even further behind, with minimal adoption 

of new instructional models such as problem-based learning (PBL) and flipped classrooms. At the root 

lies a systemic deficiency in teachers’ digital competence. Nationwide, digital training for university 

faculty is insufficient in both breadth and depth. Approximately 75% of training content is limited to 

tool operation, lacking integration with pedagogical practices—resulting in a widespread phenomenon 

of “can use but cannot teach.” The absence of incentive mechanisms further stifles motivation: for 

example, the development of VR-based teaching resources, which may require 200 hours of effort, is 

credited with merely 0.5 teaching workload units, and digital teaching skills are often excluded from 

criteria for academic promotion. 

2.4 Risk Spillover Effects Threaten Sustainable Development 

Emerging risks—namely educational equity disparities and cultural heritage erosion—pose systemic 

threats to the sustainability of digital transformation. Disparities in household access to digital devices 

exacerbate academic performance gaps, while the accessibility rate of digital resources for visually 

impaired students remains below 30%. Braille e-textbook updates are delayed by as much as nine 

months, further marginalizing vulnerable groups. More critically, the marginalization of humanities 

education signals a crisis of cultural continuity: digital adaptation rates for literature, history, and 

philosophy courses remain below 30%. For instance, shifting classical Chinese literature to online 

self-study formats has resulted in a 70% reduction in teacher-student discussion time. Overreliance on 

technological rationality—particularly intelligent grading systems—has eroded students’ critical 

thinking capacities, leading to formulaic writing and a measurable decline in argumentative depth 

among humanities students. These risks underscore the urgent need for an inclusive digital 

transformation framework that avoids falling into the trap of efficiency absolutism. 

 

 

 

 

 

 

 



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3. Pathways for Higher Education Teaching Reform from the Perspective of Digital 

Transformation 

3.1 Establishing a Three-Dimensional Digital Literacy Framework and Implementation Principles 

Construct an educational objective system integrating “tool application—thinking methodology—value 

ethics.” The foundational layer focuses on cultivating operational skills in intelligent tools and data 

analysis, embedding Python, MATLAB, and similar tools into general foundational courses. The 

methodological layer emphasizes computational thinking and information discernment, enhancing 

decision-making rationality through algorithmic logic courses. The ethical layer fosters digital 

citizenship responsibility, incorporating mandatory modules on technology philosophy to address 

issues such as algorithmic bias and data ownership. Implementation should adhere to three core 

principles: human-centered education, ensuring technology serves holistic development; technology 

empowerment, leveraging AI and big data for precision teaching and personalized growth; and 

systemic synergy, promoting coordinated reforms in teaching, management, and evaluation systems. A 

tiered strategy should be adopted for undergraduate and graduate students: undergraduates should focus 

on “intelligent+” disciplinary integration, while graduate students should prioritize data-driven research 

training, alongside establishing a closed-loop system for monitoring industry demands and tracing 

talent quality. 

3.2 Developing a Digital Competency Framework for Faculty 

Innovate a tripartite faculty development model integrating “competency standards—training 

pathways—incentive mechanisms.” First, establish a three-dimensional competency standard 

encompassing “intelligent tool application—data-informed instructional design—human-machine 

collaborative organization,” covering 22 core competency indicators. Second, design systematic 

training pathways: create a national-level digital literacy training platform offering core courses such as 

educational big data analysis and intelligent instructional design; implement a three-tier “Smart 

Education Instructor” certification, with certified faculty receiving priority in promotion evaluations; 

and introduce an industry-academia “dual-appointment” system, enabling faculty to participate in 

corporate R&D to enhance teaching. Crucially, reshape incentive mechanisms by incorporating digital 

teaching achievements as key promotion criteria, equating digital course development with 

provincial-level teaching reform projects, and establishing an automated digital growth portfolio 

system to record faculty innovation contributions. 

3.3 Building Intelligent Educational Governance Infrastructure 

Develop an “educational neural network system” comprising a data hub and intelligent core. Integrate 

12 operational systems—including academic affairs, student services, and research management—into 

a unified university-wide data hub, adopting standardized coding protocols to eliminate data silos and 

ensure “one-source, multi-use” data flow. Construct four intelligent cores: (1) a teaching core 

employing learning behavior analytics for real-time academic diagnostics and automated intervention 



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recommendations; (2) a resource core using demand-prediction models to dynamically allocate 

classrooms, equipment, and faculty; (3) an evaluation core establishing multi-dimensional assessment 

models for academic progress and innovation capability; and (4) a service core deploying AI chatbots 

to handle 85% of routine inquiries. Concurrently, integrate cutting-edge technologies such as 

blockchain and digital twins: use blockchain for immutable academic credentialing and virtual campus 

simulations to optimize emergency decision-making. 

3.4 Innovating Governance Systems and Risk Mitigation Mechanisms 

Establish a four-dimensional institutional framework encompassing “standards—organizational 

coordination—security safeguards—ethical review.” Publish an Educational Data Governance White 

Paper defining 218 data standards and certify model institutions for data governance. At the 

organizational level, form a university-wide Data Governance Committee (30% faculty, 20% student 

representation) to ensure multi-stakeholder decision-making. Deploy a cybersecurity framework 

meeting China’s *Classified Protection 2.0 Level-3* standards, with an AI security hub to neutralize 

cyber threats in real time. Ethical governance is pivotal: convene an Algorithmic Ethics Committee to 

review high-risk applications, issue Educational AI Ethics Review Guidelines mandating dual 

“technical safety + ethical compliance” certification for AI systems, and incorporate digital ethics into 

faculty and student evaluations. Continuously optimize systems using a four-dimensional efficacy 

metric (decision accuracy, resource utilization, response timeliness, stakeholder satisfaction). 

3.5 Constructing a Student Digital Competency Development System 

Enhance students’ digital learning literacy through a tripartite framework of “foundational 

skills—advanced thinking—ethical accountability.” Foundational training emphasizes intelligent tool 

usage and data acquisition, embedding Python programming and data analytics into general courses 

while modularizing skills like information retrieval and visualization. Advanced thinking cultivates 

computational and innovative thinking via algorithmic logic analysis and interdisciplinary digital 

projects in major courses. Ethical education instills digital citizenship through mandatory technology 

ethics modules examining data ownership and algorithmic bias. Implementation relies on intelligent 

learning platforms generating personalized digital profiles to dynamically allocate resources, while 

evaluation adopts a four-dimensional model (tool proficiency, information processing efficiency, 

digital creativity, and ethical decision-making). This forms a closed-loop ecosystem of curricular 

integration, platform support, and evaluative guidance, laying the foundation for lifelong learning in the 

digital era. 

 

 

 

 

 



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4. Conclusion 

The digital transformation of higher education teaching is an imperative response to national strategic 

demands and competency reconfiguration in the intelligent era. This study reveals that transformation 

urgency stems from triple pressures—global competition, national strategy, and endogenous 

educational needs—while barriers include value cognition gaps, institutional flaws, capability deficits, 

and risk propagation. The solution lies in a “goal-actor-technology-institution” quadripartite framework: 

guiding education via three-dimensional digital literacy goals, activating reform through faculty 

competency building, underpinning technology with intelligent governance infrastructure, and 

safeguarding progress via ethical governance and efficacy evaluation. This pathway embodies a 

dialectical unity of technological empowerment and institutional innovation, propelling higher 

education from experiential to data-driven governance and from scale expansion to connotative 

development. Future efforts must deepen strategic synergy between educational and industrial 

digitization, breaking talent bottlenecks in critical fields like integrated circuits and quantum 

information, ultimately supporting Chinese modernization with high-quality human capital. 

 

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