Evaluating the variation characteristics of ecological resilience along expressways in developing countries: the case of the Phnom Penh-Sihanoukville Expressway in Cambodia.

Expressway construction has caused a significant threat to the ecological environment in developing countries, and therefore the variation characteristics of ecological resilience along the expressway in developing countries are of major importance. This empirical study focuses on a typical area within a 2-km range of the Phnom Penh-Sihanoukville Expressway in Cambodia and uses remote sensing and geographic information systems (GIS) technology to analyze the variation characteristics of ecological resilience along the expressway. The results of the study reveal that due to the construction of expressways, the land use types transferred into or out of the land use types increase and furthermore the land use types show a trend of decreasing natural attributes and increasing human attributes. It is found that expressway construction has an observed effect on the transfer rate of the center of gravity of land use type, and the direction of the center of gravity shifts in the direction of expressway construction. The impact of construction on the ecological resilience of the western region with higher vegetation coverage was higher than that of the eastern region with higher urbanization. The research develops a theoretical evaluation model based on land use type of the variation characteristics of ecological resilience along the expressway, which can be used to enable the sustainability of expressway construction and maintain the regional ecological environment.

Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students.

This study aims to explore the role of digital education in the development of skills and employability for engineering students through researching the role of big data analytics courses. The empirical study proposes the hypothesis that both soft and hard skills have positive effects on human capital, individual attributes, and the career development dimensions of engineering students. This is achieved through constructing a framework of three dimensions of engineering students' employability and two competency development dimensions of big data analytics courses. A questionnaire survey was conducted with 155 college engineering students and a structural equation model (SEM) was used to test the hypotheses. The results found that courses on big data analytics have a positive impact on engineering students' abilities in both hard skills (p < 0.01) and soft skills (p < 0.001) dimensions, while soft skills have a more significant impact on engineering students' employability. The study has practical and theoretical implications that further enriches the knowledge base on engineering education and broadens our understanding of the role of digitalization in enhancing the skills and employability of engineering students.

The Moderating Effect of Learning Experience on Learning Motivation and Learning Outcomes of International Students.

With the increasing level of internationalization in higher education, the number of international students in mainland China is rapidly increasing. However, limited research has considered that student results may be affected by a reduced motivation to learn. Therefore, the aim of this research is to explore the effect of the learning motivation on the learning outcomes of international students and the moderating role of learning experience. A sample of 130 international students from 23 countries studying in mainland China was analyzed. The study found a significant correlation between the learning motivations and international students' learning outcomes. It was also determined that learning experience has significantly enhances the relationship between learning motivation and the learning outcomes of international students. This study contributes to the higher education literature on learning motivation by students and learning outcomes.

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

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.

Evaluating the impact of highway construction projects on landscape ecological risks in high altitude plateaus.

In China and other countries, many highway projects are built in extensive and high-altitude flat areas called plateaus. However, research on how the materialisation of these projects produce a series of ecological risks in the landscape is very limited. In this research, a landscape ecological risk analysis model for high-altitude plateaus is proposed. This model is based on the pattern of land uses of the surrounding area. Our study includes buffer analysis, spatial analysis, and geostatistical analysis. We apply the model to the Qumei to Gangba highway, a highway section located in the southeast city of Shigatse at the Chinese Tibet autonomous region. Through global and local spatial autocorrelation analysis, the spatial clustering distribution of ecological risks is also explored. Overall, our study reveals the spatial heterogeneity of ecological risks and how to better mitigate them. According to a comparison of the risk changes in two stages (before and after the highway construction), the impact of highway construction on the ecological environment can be comprehensively quantified. This research will be of interest to construction practitioners seeking to minimize the impact of highway construction projects on the ecological environment. It will also inform future empirical studies in the area of environmental engineering with potential affection to the landscape in high-altitude plateaus.

Understanding the role of peer pressure on engineering students' learning behavior: A TPB perspective.

Introduction: With the advent of the digital age, the gradually increasing demands of the engineering job market make it inevitable that engineering students face the pressures that arise from academic life with their peers. To address this issue, this study aims to explore the influence of engineering students' peer pressure on learning behavior based on the theory of planned behavior (TPB). Methods: In addition to attitudes, subjective norms, and perceived behavioral controls inherent in TPB, two new dimensions-gender difference and peer academic ability-were incorporated to construct a framework of the dimensions of peer pressure as affecting engineering students as well as an expanded model of TPB. A questionnaire survey was conducted with 160 college engineering students and a structural equation model (SEM) was used to test the hypotheses. Results: The result showed that positive peer pressure can increase engineering students' learning intention and thus promote learning behavior. It was also determined that the TPB model can effectively explain the effect of peer pressure on learning behavior, in addition to expanding and reshaping the relationship between the attitudinal dimension in the TPB model. Discussion: From the results, it is clear that positive attitudes toward learning can trigger positive peer pressure. Good group norms can induce peer pressure through rewards and punishments as a way to motivate students' learning intention and learning behaviors. When peer pressure is perceived, students mobilize positive emotions toward learning. Meanwhile, both male and female engineering students are also significantly motivated by high peer achievement, and high-performing female students motivate their male peers, which leads to higher graduation rates.

Corrigendum: The moderating effect of learning experience on learning motivation and learning outcomes of international students.

[This corrects the article DOI: 10.3389/fpsyg.2022.913982.].