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The aim of this study is to understand the effect of class configurations in an active learning classroom (ALC) on students' self-perception of experiences and learning outcomes, namely participation, performance, motivation and creativity.

A self-administered survey (N = 131) was conducted in seven classes from the varied disciplines of communication, interior design and architecture. During the first half of the semester, all selected courses were conducted in traditional classrooms, whereas those in the second half were conducted in an ALC. ALC was designed to be used with several furniture configurations which could be easily set up by members of the learning community themselves. The survey was conducted at the end of semester before final exams, when students have a clear idea of the experiences in both the traditional and the new (ALC) classrooms, having spent equal time in each of these learning environments.

The main finding of the study is that students were eager to have future classes in the ALC rather than in traditional settings since the students experienced better learning outcomes in the ALC. During the second half of the semester, students who were in classes conducted following active learning (AL) pedagogies, with its supportive spatial configurations, were more aware of the learning outcomes facilitated by the physical environment. Further, the authors found that the increase in the number of furniture configurations has a statistically significant positive impact on learning outcomes.

AL pedagogy is often studied as a way of teaching and rarely with its associated classroom environments. In most of the existing studies, the configuration of furniture has often been overlooked within an AL environment by a learning community. This study fills the gap in emphasising the spatial aspects of the ALC by focusing on the specific pedagogy being followed.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

This research examined the direct and indirect effect of university social responsibility (USR) on student loyalty through the mediation of service quality and university image.

The sample includes 35 students from Universitas Sarjanawiyata Tamansiswa, a private university, and 74 respondents from Universitas Sebelas Maret Surakarta, a state university, totaling 109 respondents. The data were obtained by sending a questionnaire in the form of Google Docs through the student WhatsApp groups at the universities. Furthermore, the four variable constructs were tested with loading factors to determine reliability, and Cronbach’s alpha was used to determine the construct validity. The research hypotheses were tested via path analysis using the WarpPLS 8.0 statistical tool.

The results showed that the image of the university mediates the relationship between USR and student loyalty. Meanwhile, service quality does not mediate the relationship. The USR had a direct relationship with service quality, university image and student loyalty. The image of the university also had a direct effect on student loyalty, while service quality had an insignificant effect on student loyalty. Therefore, based on the coefficient value, the indirect effect between USR and student loyalty through the image of the university is stronger than the direct effect between USR and student loyalty.

Several previous models examined the relationship between corporate social responsibility (CSR) and consumer loyalty in general, but this research has applications in the education sector with a different concept, namely USR with different measurements.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

At present, teaching methods based on 2D drawings are still commonly used for educating students on the location of steel reinforcement bars in concrete. However, traditional teaching methods have limitations as students can find it difficult to understand 2D drawings. This study aims to develop an interactive and collaborative augmented reality environment (ICARE) using augmented reality (AR) technology to improve students' engagement in learning.

This study develops an ICARE prototype, which is organized into two stages: (1) The augmented teaching environment comprising of models and interactive components; (2) The AR collaborative application which uses Photon Unity Networking (PUN) plugin and Azure spatial anchors cloud service. The AR-based teaching environment runs with Universal Windows Platform (UWP) to enable development in the HoloLens 2 through Microsoft Visual Studio.

An experimental study was conducted, where 60 students were divided into three groups employing Drawings-based, building information modeling (BIM)-based and AR-based methods for teaching. After the test, the three groups of students were requested to complete a questionnaire. According to the analysis of the experimental results, the ICARE can improve students' comprehension, memory of learned materials and their ability to read and understand steel reinforcement drawings improving the quality of teaching, especially interactivity and engagement.

As illustrated in the experiments, the developed ICARE has outstanding performance over conventional approaches in civil engineering courses that can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings. This study provides empirical evidence that AR is a promising technology that can be integrated with traditional classroom instruction and can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings.

Concrete-filled double skin tube (CFDST) columns are considered one of the most effective steel-concrete composite sections owing to the higher load carrying capacity as compared to its counterpart concrete-filled tube (CFT) columns. This paper aims to numerically investigate the performance of axially loaded, circular CFDST short columns, with the innovative strengthening technique of providing stiffeners in outer tubes. Circular steel hollow sections have been adopted for inner as well as outer tubes, while varying the length of rectangular steel stiffeners, fixed inside the outer tubes only, to check the effect of stiffeners in partially and full-length stiffened CFDST columns.

The behaviour of these CFDST columns is investigated numerically by using a verified finite element analysis (FEA) model from the ABAQUS. The behaviour of 20-unstiffened, 80-partially stiffened and 20-full-length stiffened CFDST columns is studied, while varying the strength of steel (f_yo = 250–750 MPa) and concrete (30–90 MPa).

The FEA results are verified by comparing them with the previous test results. FEA study has exhibited that, there is a 7%–25% and 39%–49% increase in peak-loads in partially stiffened and full-length stiffened CFDST columns, respectively, compared to unstiffened CFDST columns.

Enhanced strength has been observed in partially stiffened and full-length stiffened CFDST columns as compared to unstiffened CFDST columns. Also, a significant effect of strength of concrete has not been observed as compared to the strength of steel.

This study analyzes the effect of the techniques of active teaching and learning as a way of delivery on the outcomes of quality learning. Focusing on the courses of architectural science taught in a nontraditional method using various active learning strategies, the study takes the case study of the course Building Illumination and Acoustics (BIA) delivered in the academic year 2019–2020 at the University of Sharjah (UoS)'s Architectural Engineering Department (AED).

Utilizing both quantitative and qualitative research approaches, the study applied a case study and survey as methods. A questionnaire was designed and performed to assess the level of students' satisfaction with the implemented active teaching method.

The vibrant learning setting made the students actively engaged and more motivated and enthusiastic. The active learning practices used, including employing senses as in sight and hearing, reasoning rationally and intuitively, reflecting and acting, working steadily and in fits and starts, creating mathematical models, visualizing and memorizing and drawing analogies, were efficient in boosting their ability to comprehend theoretical concepts more effectively. The delivery style effectively enhances quality learning when various active techniques are used pedagogically beyond being merely a utilitarian instrument to prepare novice students of architectural engineering to fulfill practical challenges.

This article focuses specifically on a theoretical, scientific non-studio course in a particular program of architectural engineering in a particular semester before the dramatic changes in styles of teaching delivery that happened due to the COVID-19 pandemic. Future research could further highlight its results by comparing them to statistical evidence of the development of the course, especially for the duration of online teaching during the pandemic and the hybrid teaching period after it.

This article contributes to the development of teaching and learning of architectural engineering in the local Emirati context by putting original theories of teaching into practice. This paper further contributes to the field of architectural pedagogy in terms of the effect of active learning in the architecture field in the non-studio courses in higher education in the United Arab Emirates.

The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

In this chapter, the authors envision a new framework for technology-enabled local engagement. This framework would exploit web-based collaboration technology in order to create local engagement panels that represent a cross section of ordinary residents. For concreteness, the authors illustrate the framework in a proposed study called “Clearing the Air” would enable residents in the areas of Southern California that are most impacted by the logistics industry to have substantive and constructive opportunities to engage local officials on the complex economic and environmental matters related to logistics and emissions in the Southern California region. The authors propose methods to evaluate best practices in the use of collaboration technology, in particular, to learn whether the technology enables and empowers the engagement panels to participate in air quality governance at a high level and helps local officials better understand the considered opinions of residents on these important matters. If successful, this framework would integrate the policy views of individual residents alongside those of organized stakeholders, experts, and agency officials in the policy process.