


































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

Vol. 8, No. 3, 2025 

www.scholink.org/ojs/index.php/grhe 

72 

 

Original Paper 

Research on Interdisciplinary Integration and Construction of 

the Smart Construction Professional Curriculum Cluster 

Lijuan Chen
1
 

1
 Qingdao City University, Qingdao, China 

 

Received: October 14, 2025    Accepted: November 2, 2025    Online Published: November 19, 2025 

doi:10.22158/grhe.v8n3p72                 URL:http://dx.doi.org/10.22158/grhe.v8n3p72 

 

Abstract 

As the core direction of digital and intelligent transformation in the construction industry, smart 

construction places heightened demands on the interdisciplinary integration of professional curriculum 

systems. Centered on the development of a smart construction curriculum cluster, this research 

explores innovations in the curriculum system within a multi-disciplinary context. Utilizing BIM-VR 

platforms, robotics engineering, intelligent equipment, and AI technologies as core supports, it 

facilitates the deep integration of disciplines such as civil engineering, computer science, and 

automation control. The study proposes curriculum innovation strategies based on the OBE and CDIO 

models, along with a modular curriculum framework, constructing a four-tiered curriculum cluster 

(Foundation-Core-Integration-Practice). Practical teaching is enhanced through industry-academia 

collaboration and the integration of production, education, and research. For curriculum cluster 

optimization, the study develops a smart construction competency matrix and a sustainable 

development framework, introducing a dynamic evaluation mechanism to improve the adaptability of 

the curriculum system and the quality of talent cultivation. The findings provide theoretical support for 

the reform of smart construction education, promote the development of smart construction programs 

in higher education institutions, and contribute to the high-quality development of the construction 

industry. 

Keywords 

Smart Construction, Interdisciplinary Integration, Curriculum Cluster Development, BIM-VR, 

Artificial Intelligence 

 

 

 

 



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As an important direction for the digital transformation of the construction industry, smart construction 

is driving the deep integration of construction industrialization, informatization, and intelligence. In 

recent years, national and local governments have successively introduced policies to support the 

development of the smart construction industry. As a pilot city, Qingdao has accumulated extensive 

experience in BIM technology, intelligent construction, and smart sites. However, the smart 

construction discipline still faces challenges such as difficulties in interdisciplinary integration, an 

incomplete curriculum system, insufficient practical teaching resources, and lagging industry-academia 

collaboration, which constrain the quality of talent cultivation. Therefore, constructing a scientific and 

rational smart construction curriculum system and promoting interdisciplinary integration and 

innovation in practical teaching have become urgent issues to address. This study focuses on the 

development of a smart construction curriculum cluster, analyzes industry trends, identifies key skill 

requirements, and proposes a comprehensive framework based on OBE, CDIO, and modular 

curriculum concepts, covering core courses such as smart construction technology, project management, 

data analysis, automation, and robotics. Simultaneously, the study emphasizes the importance of 

practical teaching, suggesting the use of innovative teaching methods such as BIM-VR, intelligent 

equipment, and AI technology, combined with laboratory practice, project-driven learning, and 

industry-academia collaboration to enhance students’ hands-on operational skills. Furthermore, the 

study explores mechanisms for curriculum cluster evaluation and optimization to ensure the 

synchronization of teaching content with industry needs. Ultimately, the research aims to establish a 

sustainable smart construction curriculum system that provides theoretical support and practical 

guidance for talent cultivation in higher education institutions, facilitating the digital transformation of 

the construction industry. 

 

1. Development of the Smart Construction Discipline and Teaching Innovation 

1.1 Overview of Smart Construction Discipline Development and Policy Orientation 

In recent years, national and local governments have placed great emphasis on the development of 

smart construction. Departments such as the Ministry of Housing and Urban-Rural Development and 

the Ministry of Education have successively introduced policies to promote the digital, industrial, and 

intelligent transformation of the construction industry. For example, the “14th Five-Year Plan for 

Construction Industry Development” highlights smart construction as a key lever for enhancing the 

industry’s core competitiveness and calls for accelerated integration and application of technologies 

such as BIM, artificial intelligence, and the Internet of Things. At the local level, Qingdao, as one of 

the first national pilot cities for smart construction, has released a series of guidance documents 

explicitly outlining goals for developing the smart construction industry and cultivating talent in this 

field. Against this backdrop, smart construction programs in higher education institutions should 

closely align with policy demands, optimize curriculum design, promote interdisciplinary integration, 



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and cultivate talent equipped with new technology application skills, innovative capabilities, and 

engineering practical abilities to meet the industry’s urgent need for interdisciplinary professionals. 

1.2 Interdisciplinary Integration in Smart Construction Curricula  

Interdisciplinary integration is the core of the smart construction curriculum system, involving multiple 

fields such as civil engineering, computer science, automation control, and artificial intelligence. 

Currently, domestic smart construction curriculum systems in higher education institutions mainly 

follow three models: first, expanding smart construction direction courses based on civil engineering 

programs; second, strengthening construction industry application courses based on computer science 

or intelligent manufacturing programs; and third, establishing independent smart construction 

disciplines to form a complete interdisciplinary training system. To achieve interdisciplinary 

integration, the smart construction curriculum cluster should adopt a four-tier structure of “Foundation 

+ Core + Integration + Practice,” maintaining the rigor of traditional engineering courses while 

enhancing the teaching of new technologies such as information technology, intelligent construction, 

and digital twins. By integrating multidisciplinary resources and optimizing teaching models, the smart 

construction curriculum system can effectively improve students’ comprehensive abilities and provide 

high-quality talent support for the intelligent development of the construction industry (Crawford, A., 

& Stephan, A., 2021, p. 103942). 

1.3 Interdisciplinary Curriculum Innovation 

Interdisciplinary curriculum innovation in the smart construction discipline is primarily reflected in 

areas such as BIM-VR platforms, robotics engineering, intelligent equipment, and AI technology 

applications. Courses on BIM-VR platforms enhance students’ understanding of Building Information 

Modeling and improve their capabilities in visual management through 3D modeling and virtual reality 

technologies. Robotics engineering courses cover automated construction, intelligent inspection, drone 

surveying, and other content, cultivating students’ ability to apply intelligent construction technologies. 

Courses on intelligent equipment focus on technologies such as smart site management, structural 

health monitoring, and IoT sensors, enhancing students’ skills in intelligent building management. 

Courses on computer technology and AI applications integrate machine learning, computer vision, big 

data analytics, and other topics to explore the use of AI in construction scheduling, quality inspection, 

and safety management. Through these curriculum innovations, the smart construction discipline can 

cultivate interdisciplinary talent capable of meeting the future demands of the construction industry. 

1.3.1 BIM-VR Platform  

BIM (Building Information Modeling) technology is a core supporting technology for smart 

construction, and the introduction of VR (Virtual Reality) technology further enhances the visualization 

of architectural design, construction management, and operation and maintenance processes. The 

development of BIM-VR platform courses aims to cultivate students’ capabilities in data modeling, 

virtual simulation, and intelligent analysis throughout the entire building lifecycle. Course content 



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includes fundamental BIM modeling and optimization, BIM applications in construction management, 

VR immersive experience technology, and integrated BIM-VR applications. Students will learn 

software such as Revit, Navisworks, and Unreal Engine, and simulate engineering cases through virtual 

construction environments to improve their construction planning and safety management skills. The 

course adopts a teaching model of “theoretical instruction + software practice + case studies + 

simulation training,” combined with the application scenarios of BIM-VR technology, enabling 

students to intuitively understand complex engineering problems and enhance their practical 

engineering abilities. Through the application of the BIM-VR platform, students can master digital 

building technologies, providing technical support for the innovative development of the future smart 

construction industry. 

1.3.2 Robotics Engineering  

The application of robotics engineering in the field of smart construction is gradually deepening, 

offering new approaches for automation and intelligence in construction. This course covers the 

fundamental theories, programming control, construction applications, and intelligent monitoring of 

construction robotics technology. Students will learn about cutting-edge technologies such as 

bricklaying robots, concrete 3D printing, and drone inspection, and master skills in ROS (Robot 

Operating System), Python programming, and intelligent sensor applications. The course employs a 

model of “theoretical teaching + experimental training + engineering case analysis,” combined with 

construction robotics simulation platforms and real engineering cases, to enhance students’ hands-on 

skills and understanding of intelligent construction. Upon completion, students will possess the ability 

to apply construction robotics, enabling them to utilize smart construction equipment in future 

engineering practice, thereby improving construction quality and efficiency, and cultivating 

interdisciplinary talent with a cross-disciplinary background for the industry’s development. 

1.3.3 Intelligent Equipment  

The application of intelligent equipment in smart construction spans automated construction, intelligent 

monitoring, and smart site management. This course primarily introduces key technologies such as 

construction intelligent sensors, automated construction machinery, and intelligent monitoring systems, 

aiming to equip students with the skills to operate and apply smart construction equipment. Course 

content includes intelligent monitoring devices (e.g., IoT sensors, laser scanners), automated 

construction equipment (e.g., unmanned construction machinery, intelligent tower cranes), and smart 

site management systems (e.g., BIM+GIS integrated platforms). Through a model of “classroom 

teaching + equipment operation + case studies + field training,” students will learn how to use 

intelligent equipment to enhance the safety, precision, and automation level of construction. The design 

of this course helps cultivate students’ comprehensive application abilities in intelligent construction 

and operation management, providing technical support for the digital upgrade of the smart 

construction industry. 



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1.3.4 Computer Technology and AI Applications  

The application of artificial intelligence and computer technology in smart construction is becoming 

increasingly widespread, driving the construction industry towards greater intelligence and data-driven 

practices. This course mainly covers AI intelligent recognition, computer vision, big data analysis, and 

intelligent scheduling optimization technologies, aiming to develop students’ ability to apply AI in the 

construction industry. Course content includes construction data analysis and big data technology, 

machine learning and computer vision, intelligent scheduling algorithms, and integrated BIM+AI 

applications. Students will learn technologies such as Python, TensorFlow, and OpenCV, and master 

the application of AI in construction schedule optimization, quality inspection, and automated 

monitoring. The course adopts a model of “programming practice + case analysis + industry 

application practice,” encouraging students to engage in algorithm development based on smart 

construction cases, thereby improving their data analysis and intelligent optimization capabilities and 

fostering innovative technical talent for the future smart construction industry (Sacks, R., Girolami, M., 

& Brilakis, I., 2020, p. 100011). 

 

2. Interdisciplinary Smart Construction Curriculum Cluster Development 

2.1 Curriculum System Innovation Directions: OBE, CDIO, and Modular Curriculum 

In developing the smart construction curriculum cluster, innovating the curriculum system is key to 

enhancing the quality of talent cultivation. Adopting Outcome-Based Education (OBE), the CDIO 

engineering education model, and a modular curriculum structure can effectively meet the rapidly 

evolving demands of smart construction and strengthen the development of students’ comprehensive 

abilities. The OBE model focuses on student learning outcomes and competency development. By 

establishing clear learning objectives and evaluation systems, it ensures close alignment between 

curriculum content and industry needs, guaranteeing that students acquire knowledge and skills directly 

relevant to engineering practice. The CDIO model emphasizes cultivating students’ engineering 

practical ability and innovation skills, highlighting the four stages of “Conceive, Design, Implement, 

Operate” to enhance their project management and problem-solving capabilities. The modular 

curriculum system involves the scientific division and integration of knowledge in the smart 

construction field, creating distinct modules at different levels—such as foundational, core, integrated, 

and practical courses. This ensures students progressively enhance their skills and deepen their 

understanding and application abilities in smart construction at different stages. By integrating these 

three educational concepts, the smart construction curriculum system achieves both systematic 

structure and flexibility. It ensures students possess the necessary theoretical foundation, technical 

skills, and innovative awareness, preparing them to become interdisciplinary and innovative 

professionals for the industry. 

 



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2.2 Curriculum Cluster Development Strategy: Four-Tier Structure 

(Foundational-Core-Integrated-Practical) 

The development strategy for the smart construction curriculum cluster should follow a four-tier 

structural model consisting of “Foundational Courses, Core Courses, Integrated Courses, and Practical 

Courses.” This ensures the curriculum content covers the entire spectrum from fundamental knowledge 

to practical application, fostering students’ comprehensive abilities. The Foundational Courses tier 

primarily covers traditional fundamentals of civil engineering and architecture, such as《Structural 

Mechanics》, 《Architectural Drawing》, and 《Civil Engineering Materials》, providing students with 

a solid disciplinary base. The Core Courses tier focuses on the key technologies of smart construction, 

including Building Information Modeling (BIM), intelligent construction techniques, robotics 

applications, and the integrated use of AI in construction. These courses ensure students develop 

professional technical competencies in smart construction and cultivate their ability to devise solutions 

for complex engineering projects. The Integrated Courses tier involves interdisciplinary technological 

integration, such as combining BIM with VR, or integrating robotics engineering with intelligent 

construction equipment. This promotes knowledge transfer and cross-application across multiple 

disciplines, enhancing students’ innovation capabilities and engineering application skills. The 

Practical Courses tier employs project-driven learning and industry-academia collaboration to immerse 

students in real engineering environments. Through practical training in areas like project design, 

construction management, and intelligent technology application, this tier ensures students can 

effectively translate theoretical knowledge into practical engineering competence. Through this 

four-tiered curriculum design, students can progressively master the knowledge and skills required for 

smart construction, enhance their overall quality, and meet the industry’s demand for interdisciplinary 

talent. The development strategy for the four-tier structure of the smart construction curriculum cluster 

is illustrated in Figure 1 below. 

 

Curriculum System of Civil Engineering Specialty under the Background of Intelligent Construction Innovative Practice

Group of Integrated Courses

General Education Courses
Humanities General 

Education Courses

General Education Courses of This 

Major

General Education Courses of 

Other Majors

Group of 

Mathematics and 

Physics Foundation 

Courses

Group of Digital 

Engineering Design 

Courses

Group of Integrated Courses 

for Information, Mechanical-

Electrical, and Civil 

Engineering

Group of 

Comprehensive 

Courses on Intelligent 

Construction

Starting with 

information 

perception, 

taking 

transmission 

as the vein, 

and ending 

with 

feedback

Run through 

the whole 

process 

closed loop 

of 

engineering 

practice

Group of Core Courses

Figure 1. Construction Strategy for the Four-Tier Structure of the Intelligent Construction 

Professional Course Group 



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2.3 Curriculum Cluster Optimization and Competency Matrix Development 

The optimization of curriculum clusters and the development of competency matrices are pivotal 

measures for enhancing the teaching quality in smart construction programs. Through rational 

curriculum optimization and well-designed competency matrices, academic programs can better align 

with industry needs, ensuring students comprehensively develop their technical capabilities, innovative 

thinking, and practical skills during their learning process. Curriculum optimization requires timely 

updates and adjustments to course content in response to the rapid advancement of smart construction 

technologies and evolving market demands. This includes strengthening instruction on emerging 

technologies such as BIM, VR, and artificial intelligence, optimizing the overall course structure, and 

incorporating interdisciplinary curriculum modules. Simultaneously, curriculum design should avoid 

single-discipline teaching models, instead fostering forward-looking, practical, and innovative course 

content through cross-disciplinary collaboration. The competency matrix development involves 

establishing clear correlations between specific courses and targeted competencies based on the 

educational objectives of the smart construction program. This process defines precise capability 

indicators that each course should achieve. The competency matrix enables scientific assessment of 

students’ learning progress and knowledge acquisition while providing data-driven support for 

curriculum adjustment and refinement. This approach not only facilitates progressive competency 

development throughout different learning stages but also ensures graduates possess the comprehensive 

capabilities required by the smart construction industry, thereby meeting the construction sector’s 

demand for interdisciplinary and innovative professionals. 

2.4 Integration of Industry, Education, and Research: Industry-Academia Collaboration and Practical 

Teaching Base Development 

The integration of industry, education, and research constitutes a crucial component in the development 

of the smart construction curriculum cluster. Through industry-academia collaboration and the 

establishment of practical teaching bases, classroom learning can be closely aligned with actual 

engineering requirements, thereby enhancing students’ practical abilities and innovative capacities. 

Industry-academia collaboration provides students with diverse practical platforms, enabling their 

participation in real engineering projects where they learn to translate theoretical knowledge into 

operational skills. By partnering with leading construction enterprises and smart construction 

technology companies, academic institutions can stay abreast of the latest industry developments and 

technological needs, ensuring the forward-looking nature and practical relevance of the curriculum. 

Furthermore, such collaboration facilitates talent development and technological research cooperation 

between enterprises and universities, creating more employment opportunities and career development 

pathways for students. The development of practical teaching bases—including smart construction 

laboratories and intelligent construction site simulation centers—provides students with realistic and 

highly interactive learning environments. Through these industry-academia jointly built bases, students 



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can engage in practical activities such as real engineering data analysis, construction simulation, and 

intelligent equipment operation, thereby cultivating their problem-solving skills and innovative 

thinking in engineering contexts. This integration not only enhances students’ professional 

competencies but also fosters a virtuous cycle between smart construction education and industry 

development, cultivating high-quality talent to support the digital and intelligent transformation of the 

construction industry. 

 

3. Curriculum Cluster Evaluation and Sustainable Development Framework 

3.1 Continuous Optimization Framework for Curriculum Cluster Development (Smart Construction 

Talent Training Model) 

The continuous optimization framework for the smart construction curriculum cluster should be 

dynamically adjusted based on technological advancements and evolving industry demands to ensure 

close alignment between teaching content and practical applications. First, course materials must be 

regularly updated to incorporate emerging technologies and market needs in smart construction, 

particularly in areas such as BIM, artificial intelligence, and the Internet of Things. Second, teaching 

methodologies should shift from traditional lecture-based approaches to student-centered, 

practice-oriented models, emphasizing project-driven learning and problem-solving to enhance 

students’ innovative thinking and practical skills. Additionally, the optimization framework should 

integrate a dynamic feedback mechanism, systematically gathering input from students, enterprises, 

and industry stakeholders to inform data-driven adjustments to curriculum design and content. This 

approach ensures the curriculum cluster remains technologically current while fostering students’ 

professional competence and lifelong learning capabilities, ultimately cultivating highly skilled, 

interdisciplinary talent for the smart construction industry. The continuous optimization framework for 

the smart construction curriculum cluster is illustrated in Figure 2 below. 

 



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 Semester 8

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 Semester 1

Introduction to 
Engineering 
Management

Cognition of 

Engineering 

Machinery

Python

Programming 

Design

Introduction to 
Intelligent 

Construction

 Semester 2

Architectural 
Drawing 

Reading and 
BIM Modeling

Engineering 

Mechanics

Intelligent 
Construction 
Technology 

and Equipment

 Semester 3

Equipment 
Drawing 

Reading and 
BIM Modeling

Building 

Architecture 

Intelligent 

Surveying and 

Mapping

Big Data and 

Cloud 

Computing

Professional 

Basic Courses

 Semester 4

Principles and 
Practice of 

Engineering 
Quota

Market-
Oriented 

Pricing and 
Quota 

Principles

Engineering 

Structure

IoT in 

Construction 

Engineering

IoT 

Application 

Practice

Professional 

Compulsory 

Courses

 Semester 5

Engineering 

Intelligent 

Construction 

Practice of 
Engineering 
Intelligent 

Construction

Prefabricated 

Technology

Application of 
Artificial 

Intelligence 
Technology in 
Architecture 

Professional 

Practice

 Semester 6

Whole- 

Process Cost 

Management

Practice of 
Whole-Process 

Cost 
Management

Engineering 
Bidding and 

Contract 
Management

BIM Bidding 

and Contract 

Management

Application of 
Intelligent 

Robots

Intelligent 
Robot 

Application 
Training

 Semester 7

Intelligent 
Management 

of Engineering 
Projects

Practice of 
Intelligent 

Management 
of Engineering 

Projects

Intelligent 
Operation and 
Maintenance 

and 
Management

Comprehensive 
Training on 
BIM Smart 

Construction 
Site

Figure 2. Framework of Interdisciplinary Curriculum Group Construction System 

 

3.2 Curriculum Cluster Evaluation System and Improvement Mechanism 

The optimization of the curriculum cluster requires guidance from an effective evaluation system to 

enhance teaching quality. The evaluation framework should encompass four key dimensions: student 

assessments, faculty feedback, industry needs, and technological trends. Student evaluations should not 

only reflect knowledge acquisition but also assess practical skills, teamwork, and innovative 

capabilities. Faculty feedback should focus on the innovativeness of course design and the 

effectiveness of teaching methods. Industry input helps evaluate students’ performance in real-world 

work environments, ensuring the curriculum remains aligned with sector demands. Meanwhile, regular 

industry surveys keep the curriculum adaptive to future technological developments. Based on these 

multidimensional insights, an improvement mechanism enables timely adjustments to course content 

and teaching methodologies, enhancing the integration and practicality of the curriculum system. This 

process ensures that graduates possess sufficient engineering competence and technological innovation 

skills to meet the growing talent demands of the smart construction industry. 

 

 

 



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3.3 Future Prospects (AI + Smart Construction Education, Smart Construction, and Metaverse-Based 

Teaching) 

Looking ahead, smart construction education will deeply integrate with cutting-edge technologies, 

particularly artificial intelligence (AI), smart construction, and the metaverse. The incorporation of AI 

into smart construction education will advance teaching in areas such as data analysis, construction 

optimization, and quality control in architectural engineering, cultivating students’ intelligent thinking 

and technical application skills. The adoption of smart construction technologies will accelerate the 

automation and intellectualization of site management, leading to an increased emphasis in the 

curriculum on the practical application of IoT, smart sensors, and big data analytics in construction 

processes. Metaverse-based teaching, utilizing virtual reality (VR) and augmented reality (AR) 

technologies, will offer immersive learning experiences, allowing students to engage in design, 

construction, and management practices within virtual environments. This will strengthen their spatial 

awareness and engineering application abilities. The introduction of these emerging technologies will 

break the of traditional teaching approaches, providing students with more flexible and innovative 

learning experiences. Such advancements will further promote the integration of smart construction 

education and industry development, supplying highly skilled talent to support the intelligent 

transformation of the future construction industry (Zhou, Y., Zhang, J., & Li, H., 2022, p. 04022001). 

 

4. Conclusion 

This study has focused on the interdisciplinary integration and development of a curriculum cluster for 

the smart construction major. It proposes a curriculum system design based on OBE, CDIO, and a 

modular course structure, while optimizing course content and a competency matrix in line with 

industry demands. By strengthening the instruction of core technologies such as BIM, robotics 

engineering, intelligent equipment, and artificial intelligence, a systematic yet flexible curriculum 

cluster has been constructed, aiming to cultivate interdisciplinary talent with innovative capabilities and 

comprehensive practical skills. The research demonstrates that the innovation and integration of 

interdisciplinary courses can effectively enhance students’ comprehensive abilities. Furthermore, the 

combination of industry, academia, and research provides a practical platform for curriculum 

implementation, enhancing its applicability and forward-looking nature. With the rapid development of 

the smart construction industry, future educational models will increasingly integrate cutting-edge 

technologies such as artificial intelligence, smart construction, and the metaverse, driving the 

continuous optimization and upgrading of the curriculum system. The development of the smart 

construction curriculum cluster not only provides high-quality talent support for the industry but also 

offers theoretical and practical guidance for the reform of higher education. It contributes to the 

intelligent and digital transformation of the construction industry, supporting its high-quality 

development. 



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Funding 

[Fund Projects] 2024 Annual Research Project of Qingdao City’s 14th Five-Year Plan for Educational 

Science “Research on the Construction of an Interdisciplinary Intelligent Construction Curriculum 

Cluster System under the Context of Industry-University Cooperation in Higher Education” 

(QJK2024E053). 

 

References 

Crawford, A., & Stephan, A. (2021). The role of digital twins in the construction industry: A review of 

practices and prospects. Automation in Construction, 132, 103942. 

https://doi.org/10.1016/j.autcon.2021.103942 

Sacks, R., Girolami, M., & Brilakis, I. (2020). Building Information Modeling, Artificial Intelligence 

and Construction Tech. Developments in the Built Environment, 4, 100011. 

https://doi.org/10.1016/j.dibe.2020.100011 

Zhou, Y., Zhang, J., & Li, H. (2022). Integrating VR Technology into Construction Education: A 

Project-Based Learning Approach. Journal of Civil Engineering Education, 148(2), 04022001.  

 

 

 

https://doi.org/10.1016/j.autcon.2021.103942
https://doi.org/10.1016/j.dibe.2020.100011

