


































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 

36 

 

Original Paper 

The Application of Smart Course Construction Based On the 

COST Model in the Teaching of “Civil Engineering Materials” 

Wenting Hua
1*

, Hui Wang
1
, Aihong Qin

1
 & Fuli Wang

1
 

1
 Qingdao City University, Qingdao, China  

*
 Corresponding author: Wenting Hua, E-mail: wenting.hua@qdc.edu.cn 

 

Received: September 5, 2025    Accepted: September 26, 2025    Online Published: October 8, 2025 

doi:10.22158/grhe.v8n3p36                 URL:http://dx.doi.org/10.22158/grhe.v8n3p36 

 

Abstract 

The course “Civil Engineering Materials” adheres to a student-centered approach, aiming to cultivate 

“new engineering” applied talents with “practical ability engineering thinking, and craftsmanship 

spirit”. Through smart course construction, the COST model is used to realize the theoretical and 

practical path of integrating artificial intelligence into education and teaching, to build a 

comprehensive teaching system that includes knowledge imparting, ability training, ideological and 

political integration, and quality improvement. 

Keywords 

civil engineering materials, smart course, teaching reform 

 

1. Introduction 

Artificial intelligence technology is reshaping the global education landscape, and its applications have 

evolved from auxiliary teaching tools to core drivers of educational change. To cope with this 

educational revolution, extensive research has been conducted on the deep integration of artificial 

intelligence into education and teaching. Among them, smart education is the advanced stage of digital 

education development, and smart curriculum construction is an important means to improve teaching 

quality and efficiency. It can achieve the sharing of teaching resources, optimization of teaching 

processes, and improvement of student learning outcomes through information technology. 

In recent years, many scholars have been committed to developing teaching models based on smart 

curriculum platforms, by introducing virtual simulation experiments, online testing, multimedia 

courseware, and other means to enhance students’ learning interests and practical abilities. For example, 

Li Nianqiang (2025) proposed using artificial intelligence technology combined with the application of 

knowledge graphs to optimize teaching content, improve students’ learning efficiency, and explore the 



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construction of intelligent courses for professional basic courses. Zhao Zhiqiang (2025) proposed a 

method for constructing innovative classroom teaching models in the context of smart classrooms, and 

after practical testing, pointed out that this method has the advantages of high student participation and 

high teaching efficiency compared to traditional knowledge-based teaching models. In terms of 

combining traditional teaching methods with the construction of smart courses, Hu Hui’e (2023) 

proposed that the teaching system of professional basic courses should start from teaching effectiveness, 

decompose teaching content according to teaching objectives, reconstruct the teaching system, and 

adopt blended online and offline teaching to achieve the integration of content, technology, and 

teaching, so that students can transform from passive learning to active learning. Duan Enen (2024) 

proposed the teaching model of “flipped classroom+smart curriculum”, which significantly improves 

teaching effectiveness through the full process design of pre class preview, classroom interaction, and 

post class review. Domestic scholars have also conducted extensive research on the optimization and 

integration of teaching resources, particularly in areas such as virtual simulation experiments, 3D 

modeling, and animation demonstrations, achieving significant results. For example, Li Jiefeng (2024) 

developed a civil engineering experimental teaching system based on virtual simulation technology, 

which effectively compensates for the shortcomings of traditional experimental teaching by combining 

virtual experiments with actual experiments. 

The construction of smart courses has become a hot research area at present. Significant achievements 

have been made in the construction of smart course platforms, innovation of teaching modes, and 

optimization of teaching resources. However, further research is still needed in areas such as teaching 

evaluation and feedback mechanisms, personalized learning support, etc. 

This article is based on the COST model for instructional design, focusing on the construction of the 

“Civil Engineering Materials” smart course with “associative thinking, precise analysis, and cross 

integration”, which has important theoretical and practical significance. 

 

2. Teaching Ideas for the Course of Civil Engineering Materials 

The COST instructional design model integrates the four core contents of content, others, self, and 

tasks into the design of students’ learning experience, environment, and methods, helping students 

effectively establish internal connections between knowledge (Chen, 2025). Students can deepen their 

understanding of knowledge and develop advanced thinking abilities through interaction and dialogue 

with others. By engaging in self dialogue, students can enhance their ability to reflect and learn 

independently. With the assistance of information technology, students achieve the learning goal of 

solving problems or completing complex tasks, in order to develop higher-order thinking and 

problem-solving abilities. 

Based on the COST teaching design model, the smart course construction plan for Civil Engineering 

Materials is implemented from the following aspects, as shown in Table 1. 



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Table 1. Implementation of COST Teaching Design Model 

 

3. Innovative Methods and Approaches for the Smart Course of Civil Engineering Materials 

3.1 Enrich the Construction of Digital Teaching Resources on Course Platforms 

In the self built course of “Civil Engineering Materials” on the Fan Ya learning platform, there are 

diverse digital teaching resources, including courseware for various knowledge points, teaching design, 

self-made micro lesson videos, experimental operation videos, engineering case libraries, course 

ideological and political libraries, journal libraries, textbook libraries, expanded material libraries, 

including online question banks for various question types, etc. 

3.2 Constructing a “Quality Ability Knowledge” System Structure Based on Multivariate Graph 

By combining knowledge graphs with problem graphs, ability graphs, and ideological and political 

graphs, the construction of multiple graphs can help students better understand the hierarchical 

structure and correlation of knowledge. The course will use knowledge graph technology to structure 

COST Teaching 

Design 
Implementation Design Objectives 

Interactive learning 

with learning 

content（C） 

Construction of diversified 

online resources 

Construction of multivariate 

graph 

Effectively display multimedia learning 

materials 

Reduce students’ cognitive load 

Establish knowledge connections and 

construct a logical framework for 

learning content 

Interactive learning 

with others（O） 

Application of artificial 

intelligence technology 

Application of virtual digital 

human technology 

Collaborative learning among 

students 

Externalizing knowledge structure to 

promote team collaboration skills 

development 

Timely feedback and personalized 

coaching provided 

Self-talk learning

（S） 

Application of Artificial 

Intelligence Technology 

Knowledge visualization assisted 

personalized learning 

Personalized resource push to achieve 

precise teaching 

Task-based or 

practical learning

（T） 

Virtual simulation experimental 

platform 

Design of Complex Tasks Based 

on Problem Graph 

Developing teamwork and 

problem-  

Enhance practical skills in engineering 

projects 



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and visualize the core knowledge of civil engineering materials courses, helping students 

comprehensively understand the connections between various knowledge points. Through visualized 

knowledge graphs, students can quickly access relevant content and advanced knowledge, enhancing 

the systematicity and coherence of learning. The problem map helps students clarify the key and 

difficult points of knowledge, identify and solve problems by sorting out the core issues in the course 

of civil engineering materials. Building a competency map closely integrates knowledge points with 

ability points, enabling students to clearly identify corresponding ability requirements in the process of 

learning knowledge, which helps students transform knowledge into practical abilities. By combining 

knowledge and ideological and political elements to construct an ideological and political map, we 

guide students to understand the social value, ethical responsibility, and engineering mission of the 

course content, and promote their comprehensive development. 

3.3 Introducing Virtual Digital Human Technology 

We plan to introduce iFlytek’s virtual digital human technology, utilizing various artificial intelligence 

technologies such as speech synthesis, video synthesis, and virtual human image synthesis, to transform 

the original boring engineering case text materials or technical specifications of related building 

materials into teaching videos hosted and explained by virtual digital humans. While linking 

engineering cases with knowledge points, digital humans can also promptly answer students’ practical 

questions, making teaching interaction more vivid and effective. Efficient interaction can significantly 

improve students’ learning interest and learning outcomes. 

3.4 Introducing a Virtual Simulation Experimental Platform 

Based on the virtual simulation training platform, we plan to introduce a trial version of the virtual 

experiment platform, which covers the main experimental content of civil engineering materials as well 

as laboratory experiments that are not offered, such as asphalt material related experiments, so that 

students can conduct material performance testing in a virtual environment. Virtual experiments not 

only break the limitations of experimental resources, but also provide students with rich opportunities 

for practical operation, further enhancing their hands-on ability and innovative thinking. 

3.5 Utilizing Artificial Intelligence Technology to Support Innovative Curriculum Teaching 

The course will provide personalized learning services through AI technology driven intelligent agent 

systems. Intelligent agents will conduct real-time analysis based on students’ learning data and push the 

most suitable learning resources, helping students obtain customized content according to their learning 

situation, thereby improving learning efficiency and ensuring that every student can master course 

knowledge at an appropriate learning pace. At the same time, the course will guide students to engage 

in self-directed learning and knowledge application through a task driven teaching approach. By 

designing targeted learning tasks, students can solve practical problems in practice and cultivate 

innovative abilities. The task guided mode not only enhances students’ sense of participation, but also 

improves their learning motivation and practical ability. Each task will track learning progress through 



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the platform and adjust teaching content in real-time to meet the personalized needs of students. 

3.6 Innovation of Teaching Evaluation and Feedback Mechanism 

The course will adopt an intelligent evaluation mechanism, using big data and AI technology to collect 

students’ learning data in real time, analyze learning progress, test scores, etc., and generate learning 

reports. Based on students’ performance, generate feedback information, provide personalized learning 

suggestions, help students make up for their shortcomings, and improve learning outcomes. In addition, 

teachers can adjust teaching strategies based on the results of intelligent assessments to ensure that each 

student’s learning receives precise support. 

 

4. Course Innovation Effect 

Under the background of “new engineering” and “Internet plus” education, the course of Civil 

Engineering Materials closely adheres to “student development as the center”, combines the vision of 

the school and talent training goals, proposes a “practice and inquiry” hybrid teaching mode, and 

adopts multi-dimensional interaction, independent learning and other methods to improve the learning 

effect of the course. 

4.1 Personalized Learning Support and Intelligent Resource Provision 

In response to the diverse learning foundations and differentiated needs of student groups, the course 

will provide personalized learning support through a smart platform. Using artificial intelligence 

technology, course content will be dynamically adjusted based on students’ learning progress and weak 

areas. AI teaching assistants will accurately analyze students’ learning behavior and grades, generate 

personalized learning suggestions and recommended resources, ensuring that each student can master 

the course content at an appropriate learning pace. 

4.2 Knowledge Graph Driven Teaching System 

The course combines the knowledge graph of “Civil Engineering Materials” to integrate the course 

content into a structured and visual knowledge network, helping students better understand the inherent 

connections between knowledge points and achieve associative thinking. By constructing a 

three-dimensional structure of “quality ability knowledge”, the knowledge graph clearly displays the 

relationship and application scenarios of each knowledge module, helping students build a complete 

knowledge framework. In addition, knowledge graphs can be combined with artificial intelligence 

technology to dynamically adjust learning paths and recommend relevant learning resources, enabling 

students to more efficiently grasp course content and gradually achieve cross disciplinary integration. 

4.3 Practice Oriented Teaching Mode Combining Blended Learning and Virtual Experiments 

By combining online and offline blended learning modes, the course provides flexible learning 

methods. The online section includes micro lesson videos, online tests, interactive discussions, etc., to 

enhance students’ self-learning ability; The offline part enhances students’ practical operation ability 

and problem-solving skills through classroom interaction, virtual digital human interaction, Q&A and 



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discussion. The course will also utilize virtual experiments and simulation platforms to make up for the 

lack of experimental projects. Students will be able to conduct material experiments and application 

simulations in a virtual environment, enhancing their practical skills and engineering experience. 

4.4 Intelligent Teaching Management and Precise Teaching 

Through an integrated intelligent teaching platform, the course can not only track students’ learning 

progress and status in real time, but also automatically adjust teaching content and methods based on 

students’ learning data, implementing precise teaching. This management model not only improves the 

teaching efficiency of teachers, but also ensures that each student can receive timely and effective 

learning support according to their individual needs, thereby optimizing teaching resources and 

enhancing overall learning outcomes. 

 

5. Conclusion 

Civil engineering materials, as a core foundational course in civil engineering and related majors, aims 

to cultivate innovative talents in the course construction. It aligns with the national “Golden Course” 

inspection standard of “one degree for both sexes” and continuously optimizes the course construction 

through various teaching reform methods such as comprehensive application of practical exploration 

mixed teaching, engineering case teaching, and information technology teaching. Currently, this course 

has initially formed a course feature with the goal of cultivating innovative applied talents. In 

subsequent teaching, teachers should teach according to their aptitude, innovate and innovate at the 

same time, and cultivate more innovative applied talents for the region and industry. 

 

Funding 

This paper sponsored by Teaching Research Project of Qingdao City University. Research on the 

construction of smart courses based on the COST model using “associative thinking, precise analysis, 

and cross fusion”-taking the course “Civil Engineering Materials” as an example. Project Number: 

2025015B. 

 

References 

Chen, J. J. (2025). Model of Domain Learning-Based Integration of Artificial Intelligence into 

Instruction—A Case Study of a Course by a National Distinguished Teacher on the “ZJU-Great 

Master”. Research in Higher Education of Engineering, 04, 27-35. 

Duan, E. E. (2024). Research on the Integration Strategy of Flipped Classroom and Smart Classroom 

under the POA Theory System: Taking the “Management Information System” Course as an 

Example. China Internet Week, 14, 61-63. 

Hu, H. E. (2023). Reconstruction of Professional Basic Course Teaching System Based on Smart 

Education: Taking Engineering Materials Course as an Example. University Education, 06, 11-14. 



www.scholink.org/ojs/index.php/grhe            Global Research in Higher Education                  Vol. 8, No. 3, 2025 

42 
Published by SCHOLINK INC. 

 

Li, J. F. (2024). Construction of Experimental Teaching System for Civil Engineering Major Based on 

Virtual Simulation Technology. New Curriculum Research, 24, 29-32. 

Li, N. Q. (2025). Exploration of Intelligent Innovation Curriculum Combining Artificial Intelligence 

and Knowledge Graph: Taking Electromagnetic Field and Electromagnetic Wave Course as an 

Example. Journal of Higher Education, 11, 76-79.  

Zhao, Z. Q. (2025). Construction of innovative teaching mode in vocational colleges under the 

background of smart classroom: Taking “Measurement and Pricing of Construction Engineering” 

as an example. Stone, 05, 103-105.  

 

 


