Toward next‐generation engineering education: A case study of an engineering capstone project based on BIM technology in MEP systems

Zhang, Jingxiao; Zhang, Zhiyue; Philbin, Simon P.; Huijser, Henk; Wang, Qian; Jin, Ruoming

doi:10.1002/cae.22448

Cited by 11 publications

(9 citation statements)

References 49 publications

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“…Smart construction systems have huge potential to improve the efficiency of construction industry [ 5 ]. Specifically, they empower the engineering production system and promote the interconnection of engineering construction processes, including online and offline integration, resource, and element collaboration [ 6 , 7 ]. In this context, the 21st century engineers and architects must be able to deal with the rapid pace of technological change and successfully navigate the highly interconnected world of industry [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…The quantity of digital linguistic landscapes in the education environment of engineering students is far from enough. This not only serves to weaken the influence of the language environment itself on the cultivation of engineering students' consciousness, thinking, and cultural heritage [ 7 ] but also installs certain obstacles to the cognitive ability of such students [ 22 ]. This affects their learning ability and also decreases the significance of the digital information platform on the education of students suitable for smart construction through difficulties adapting to the rapid changes in the era of digitalization and information technology.…”

Section: Introductionmentioning

confidence: 99%

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Testing the Effects of the Digital Linguistic Landscape on Engineering Education for Smart Construction

Lin

Zhang

Yin

et al. 2022

Computational Intelligence and Neuroscience

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This study investigates the mechanism of digital linguistic landscapes in enabling engineering education for smart construction according to the educational dimensions of A (ability), S (skill), and K (knowledge). A questionnaire survey was conducted based on the core concepts of the informative dimension and symbolic dimension in digital language landscape as well as the ability dimension, knowledge dimension, and skill dimension in engineering education. Structural equation modeling (SEM) was used as the test method. The results of the research demonstrate that the informative dimension and symbolic dimension are two main aspects of DLL in education of engineering students for smart construction. Additionally, DLL has a significant positive impact on the ability, knowledge, and skill education of engineering students for smart construction. The research has theoretical and practical significance, as it not only enriches research on the relationship between DLL and engineering education for smart construction but also expands the theoretical understanding of engineering education from the perspective of linguistics. Furthermore, the study explores the path of the practical application of digital language landscape to engineering education for smart construction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Testing the Effects of the Digital Linguistic Landscape on Engineering Education for Smart Construction

Lin

Zhang

Yin

et al. 2022

Computational Intelligence and Neuroscience

Self Cite

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“…High levels of motivation were observed in the students in the face of a specific goal linked to the academic purpose of the subject. The university-business collaborative learning environment proposed has motivating factors common to other studies [54][55][56][57][58][59][60]. As other studies denote [61,62], the inclusion of a real and competitive challenge, posed in collaboration with a business environment, was more effective than working on a fictitious case, and it is an important component of engineering education.…”

Section: Discussionmentioning

confidence: 93%

BIM for the Realization of Sustainable Digital Models in a University-Business Collaborative Learning Environment: Assessment of Use and Students’ Perception

et al. 2022

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This paper develops an assessment of an academic implementation of building information modeling (BIM) carried out in an expert project subject of a School of Industrial Engineering. The objectives were for the students discover sustainable industrial during the design process and the students understand and participate in a real process of the implementation of industrial projects through real collaboration between academic and business contexts. The outcomes of this academic initiative were evaluated using academic results as well as students’ perceptions. Academic results were analyzed using the FUZZY VIKOR method. An analysis of variance (ANOVA) was performed to determine whether the use of BIM, the proposed university-enterprise environment and the sustainability proposal rate of the students’ projects had statistically significant effects on the results. Students´ perception evaluation was based on a Likert survey with five levels, and the results were interpreted using fuzzy k-means clustering and classification tree analysis. The results show that 77.8% of students consider that for learning, it is more effective to carry out a project related to an existing company, with the realization of the project with BIM methodology being of great value. The sustainability aspects were applied more easily thanks to the proposed methodology, and they were positively valued by the company.

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“…In training and education, educators transform the GI ethical concepts based on the country, society, and class to the educated by means of certain means and methods. To meet the requirements of GI engineering ethical literacy, training education is an inevitable measure of GI EEE (Zhang et al, 2022 ). Training education is an inevitable measure of GI EEE.…”

Section: Core Mechanism and Evaluation Systemmentioning

confidence: 99%

Enhancing engineering ethics education (EEE) for green intelligent manufacturing: Implementation performance evaluation of core mechanism of green intelligence EEE

Yin

Zhang

2022

Front. Psychol.

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The characteristics of green intelligent (GI) engineering ethics emphasize the necessity of GI engineering ethics education (EEE). The ethics education of GI engineering is in the development stage, and it is urgent to fully understand the significance of evaluating the development of GI EEE. Only based on the GI manufacturing situation system to understand the implementation status of the core education of EEE can we objectively grasp the improvement space of GI EEE. In this study, the corresponding indicators were selected from three dimensions of cultivation education, collaborative education, and situational education to form the element community of evaluation indicators. The fuzzy analytic hierarchy process and the fuzzy comprehensive evaluation method were used to empirically evaluate the implementation of the key mechanism of GI EEE. The results are as follows. (1) The key education of GI EEE includes cultivation education of micro dimension, collaborative education of medium dimension, and situational education of macro dimension. (2) The most important education is to strengthen the ethics education of GI engineering in the training process of college students. The coordination of GI EEE is becoming more and more important, and the integration and construction are the important pursuit of GI EEE. (3) The cultivation education, collaborative education, and situational education of GI EEE are all at a general level. (4) There is not only a gap between theory and practice in GI EEE but also insufficient attention to localization and coordination issues. The willingness of the government to participate in the ethical education of GI engineering is very insufficient. The optimized space of training education includes teaching cases and full-cycle ethical education.

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Toward next‐generation engineering education: A case study of an engineering capstone project based on BIM technology in MEP systems

Cited by 11 publications

References 49 publications

Testing the Effects of the Digital Linguistic Landscape on Engineering Education for Smart Construction

Testing the Effects of the Digital Linguistic Landscape on Engineering Education for Smart Construction

BIM for the Realization of Sustainable Digital Models in a University-Business Collaborative Learning Environment: Assessment of Use and Students’ Perception

Enhancing engineering ethics education (EEE) for green intelligent manufacturing: Implementation performance evaluation of core mechanism of green intelligence EEE

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