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

作者：Xu Lin, Jingxiao Zhang, Yin Nan Yuan, Junwei Zheng, Simon P. Philbin, Brian H.W. Guo, Ruoyu Jin · 发表于：Computational Intelligence and Neuroscience · 年份：2022 · DOI：10.1155/2022/4077516 · 被引用次数：4 · 研究领域：Innovations in Education and Learning Technologies、Foreign Language Teaching Methods、Educational Innovations and Challenges

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.