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Lean construction (LC) is an innovative approach in the construction industry that has shown significant success in developed countries. Although LC has potential in the construction sector of Pakistan, it has not been extensively explored. This study aims to address this knowledge gap by identifying and predicting current lean practices and assessing the strengths and weaknesses of LC implementation in Pakistan.

Using robust statistical methods to analyze 92 valid responses, the study reveals that approximately 54% of lean practices are currently in use in the construction industry of Pakistan, with a population mean ranging from 52.7% to 55.6%.

Surprisingly, the research identifies instances where some construction firms in Pakistan are implementing LC practices, even though they have only a limited understanding of its underlying principles. Notably, certain subprinciples, such as visual management, top management commitment to change, employee training, process cycle time reduction and production optimization, are less integrated within the construction industry. Exploring the possibility of implementing LC, recommendations for strategies to implement LC in Pakistan are suggested, aligning with the conceptual model proposed by the researchers.

The novelty of this work offers insights that can serve as a comprehensive guide for developing nations. It provides a structured approach to assess and benchmark LC practices, which, in turn, can contribute to a more efficient and effective construction industry. Moreover, the strategies proposed in this research can aid developing countries in the efficient implementation of LC. This will have a positive implication for both economic and developmental outcomes.

This paper describes the development of a digital role play game (RPG) designed to help construction apprentices to better communicate with their supervisors about issues with the potential to impact on their physical and psychological health and safety.

A participatory approach was adopted to utilise the knowledge and insights of the target users to inform the digital RPG development. Apprentices and supervisors were interviewed to identify characteristics of effective supervisor-apprentice communication, which became the RPG’s learning objectives. The scenarios constructed in the RPG were drawn from lived experiences shared by the apprentices in the interviews. During the development process, consultations were conducted with an advisory committee comprising of apprentices and supervisors to improve the realism of the RPG scenarios.

Three scenarios were developed for the RPG. In each scenario, players are asked to make decisions at various interaction points about how the characters should respond to the unfolding and challenging situations. Scripts were developed for the game, which were acted out and motion captured to animate digital MetaHuman characters embedded in a virtual construction site. Two example situations are introduced in this paper to illustrate the development process.

To our knowledge, the RPG introduced is one of the first applications of digital game-based training in the construction industry. The adoption of a participatory design approach ensures that the game content relates to real-world experiences. The digital RPG is highly interactive and engaging in nature and presents a novel approach to developing “soft” skills in construction.

This study aims to develop a novel theoretical model for predicting the users’ intention to use virtual tools designed for construction risk evaluation. Risk evaluation is a vital objective for construction managers. This paper intends to examine critical factors such as potential benefits, motivation, performance expectancy and rich sources of information that may affect users’ intention to use virtual technology.

A pile training module (PTM) was developed in a virtual environment to analyze the proposed virtual reality-technology acceptance model (VR-TAM) factors. Further, a questionnaire survey was conducted with the participation of 102 construction professionals in China to validate the proposed VR-TAM model and PTM tool. The retrieved data was computed to test the proposed model by using partial least squares structural equation modeling and the significance of the PTM tool in a virtual environment.

The results of this study reveal that high-significance paths represent five relationships between crucial factors affecting users’ intention to use a selected virtual reality (VR) module. Five of seven hypothesis paths were significant with acceptable t-values. By quantitative measurement of high-significance paths, this research has found that each factor under VR-TAM has received significant loadings, with many above the 0.7 threshold mark and others around 0.6. The top factors include “motivation” and “benefits” and have multiplier effects on “intention to use” as the source factors.

The finding of this study presents crucial factors for VR adoption, and the proposed VR-TAM model contributes to the body of knowledge toward managing construction risk using pre-optimization and understanding in a virtual environment. This study supports Chinese construction company managers in effectively using VR technology in their construction projects for risk assessment and management.

This study offered the development of a novel VR-TAM integrated with risk assessment techniques for piling processes. Further, the developed model was analyzed by using a survey of Chinese construction professionals to collect perceptions about the modified theoretical model of VR-TAM.

Set-based design (SBD) is a lean tool widely adopted for improving design processes and providing value maximization to clients. The purpose of this paper is to present the development and testing of a lean simulation game that incorporated point-based and SBD principles. The objective of the game was to enhance learning of lean design management among construction students.

After a thorough and comprehensive literature review consisting of secondary data in journal papers, books, thesis references and primary data in the form of interviews with lean practitioners, the simulation game prototype was developed. The testing of the game was carried out with a study group. Data were collected during the gameplay with the help of a questionnaire survey on a confidence scale and Likert scale and assessed using the Wilcoxon signed-rank test, histogram, one-sample t-test and false discovery rate (Benjamini–Hochberg) correction method.

The data collected both pre- and post-simulation showed an increase in average confidence in understanding from 3.33 to 3.89, a 16.7% rise. The data was further interpreted by using Wilcoxon signed-rank test, indicating that the post-simulation learning experience was significantly better than the pre-simulation one. Promising positive results were obtained for the questions on game design, engagement and understanding of point-based design and SBD concepts.

The simulation game helps bridge the gap between knowledge building and real-life by effectively imitating the process. The game facilitates a dynamic and critical approach toward developing new educational simulation games and their successful incorporation in propagating lean principles in the construction industry.

Safety training can effectively facilitate workers’ safety awareness and prevent injuries and fatalities on construction sites. Traditional training methods are time-consuming, low participation, and less interaction, which is not suitable for students who are born in Generation Z (Gen Z) and expect to be positively engaged in the learning process. With the characteristic of immersive, interaction, and imagination, virtual reality (VR) has become a promising training method. The purpose of this study is to explore Gen Z students’ learning differences under VR and traditional conditions and determine whether VR technology is more suitable for Gen Z students.

This paper designed a comparison experiment that includes three training conditions: VR-based, classroom lecturing, and on-site practice. 32 sophomore students were divided into four groups and received different training methods. The eye movement data and hazard-identification index (HII) scores from four groups were collected to measure their hazard-identification ability. The differences between the participants before and after the test were tested by paired sample t-test, and the differences between the groups after the test were analyzed by one-way Welch’s analysis of variance (ANOVA) test.

The statistical findings showed that participants under VR technology condition spent less time finding and arriving at the Areas of Interest (AOIs). Both the eye movement data and HII scores indicated that VR-based safety training is an alternative approach for Gen Z students to traditional safety training methods.

These findings contribute to the theoretical implications by proving the applicability of VR technology to Gen Z students and empirical implications by guiding colleges and universities to design attractive safety training lessons.

The purpose of the article is to develop an innovative pedagogic tool: an escape room board game to be played in-class, targeting an introduction to an ethics course for engineering students. The design is student-centred and aims to increase students' appreciation, commitment and motivation to learning ethics, a challenging endeavour for many technological students.

The methodology included the design, development and in-class application of the mentioned game. After application, perception data from students were collected with pre- and post-action questionnaire, using a quasi-experimental method.

The results allow to conclude that the developed game persuaded students be in class in an active way. The game mobilizes body and mind to the learning process with many associated advantages to foster students' motivation, curiosity, interest, commitment and the need for individual reflection after information search.

The main limitation of the game is its applicability to large classes (it has been successfully tested with a maximum of 65 students playing simultaneously in the same room).

The originalities and contributions include the presented game that helped to captivate students to ethics area, a serious problem felt by educators and researchers in this area. This study will be useful to educators of ethics in engineering and will motivate to design tools for a similar pedagogical approach, even more so in areas where students are not especially motivated. The developed tool is available from the authors at no expense.

The proliferation of ChatGPT, as in many other digital technologies and social media, has increasingly impacted many aspects of modern life, including second and foreign language education. This study, building on a common theoretical position of all these advances in Artificial intelligence (AI), seeks to establish a model for ChatGPT research on English language learning. It specifically explores the dimensions in which ChatGPT aids students in their English language learning.

The study adopts grounded theory in collecting and analyzing data from 20 ResearchGater (RG) through a two-week RG discussion about ChatGPT uses in their language learning contexts. Data collected via the discussion was analyzed thematically.

Preliminary findings show that ChatGPT can be used in developing learners' language skills; scaffolding the learning process by providing feedback to students on their language use and acting as partners in practicing language with recommended activities for more language practice.

The study contributes a five-dimension model for artificial intelligence assisted language learning (AIALL). The model involves flexible teacher's role to consolidate learner autonomy and provide enjoyable learning, urges future innovation, and celebrates various applications. Examining the AIALL model of ChatGPT for language learning, teachers should provide some directions for properly using this new application.

Education for sustainable development (ESD) is a developing educational concept that aims to achieve economic, social and environmental sustainability through education. Cultural sustainability education aims to cultivate awareness and protection of cultural assets, promote sustainable development and foster environmental responsibility. This study establishes a cyber-physical metaverse of cultural sustainability learning to cultivate students' motivation, multicultural identity, critical thinking and sustainability thinking.

In this study, virtual reality (VR) and 3D printing technologies were utilized to create a cyber-physical metaverse learning environment. This learning environment is designed to allow elementary school children to learn about indigenous cultures and the architecture of slate houses, as well as socio-architectural issues. Learners will be able to experience first-hand the plight of the indigenous tribal areas and the exploration of related cultural knowledge.

The study collected pre- and post-test data through questionnaires, using covariates to analyze learners' perceptions of learning. The results of this study showed that cyber-physical metaverse learning environment had a significant impact on learning motivation, multicultural identity and sustainability thinking for culturally sustainable education. However, this study’s impact on critical thinking skills in students remains to be confirmed.

This is a quasi-experimental study of a single country’s elementary school children in the indigenous area, so its findings cannot be extrapolated to other areas or to learners of different ages.

This study introduces a framework for incorporating both virtual and real cultures to promote sustainable learning. The cyber-physical metaverse learning is used to supplement teaching activities to enhance learners' motivation in learning multicultural knowledge. Students were able to recognize and protect cultural assets, as well as emphasize the importance of sustainable development.

The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype index was constructed as well as several approaches of XAI were employed to interpret Black Box models and assess the magnitude and direction of the impact of the features used.

The research paper involved the construction of a sentiment index termed the NFT hype index, which aims to measure the influence of market actors within the NFT industry. This index was created by analyzing written content posted by 62 high-profile individuals and opinion leaders on the social media platform Twitter. The authors collected posts from the Twitter accounts that were afterward classified by tonality with a help of natural language processing model VADER. Then the machine learning methods and XAI approaches (feature importance, permutation importance and SHAP) were applied to explain the obtained results.

The built index was subjected to rigorous analysis using the gradient boosting regressor model and explainable AI techniques, which confirmed its significant explanatory power. Remarkably, the NFT hype index exhibited a higher degree of predictive accuracy compared to the well-known sentiment indices.

The NFT hype index, constructed from Twitter textual data, functions as an innovative, sentiment-based indicator for investment decision-making in the NFT market. It offers investors unique insights into the market sentiment that can be used alongside conventional financial analysis techniques to enhance risk management, portfolio optimization and overall investment outcomes within the rapidly evolving NFT ecosystem. Thus, the index plays a crucial role in facilitating well-informed, data-driven investment decisions and ensuring a competitive edge in the digital assets market.

The authors developed a novel index of investor interest for NFT assets (NFT hype index) based on text messages posted by market influencers and compared it to conventional sentiment indices in terms of their explanatory power. With the application of explainable AI, it was shown that sentiment indices may perform as significant predictors for NFT sales and that the NFT hype index works best among all sentiment indices considered.

This paper examines the evolution of massive open online courses (MOOCs) literature over the past 15 years and identifies its significant developments.

Utilizing main path analysis (MPA) on a dataset of 1,613 articles from the Web of Science (WoS) databases, the authors construct the main pathway in MOOC literature through a citation analysis. Pajek software is used to visualize the 34 influential articles identified in the field.

Three phases emerge in MOOC research: connectivism as a learning theory, facilitating education reform and breaking barriers to MOOCs adoption. Multiple-Global MPA highlights sub-themes including self-regulated learning (SRL), motivation, engagement, dropouts, student performance and the impact of COVID-19.

First, data limitations from the WoS core collection might not cover all research, but using reputable sources enhances data validity. Second, despite careful algorithm selection to enhance accuracy, there remains a limitation inherent in the nature of citations. Such biased citations may result in findings that do not fully align with scholars' perspectives.

The authors' findings contribute to the understanding of MOOCs literature development, enabling educators and researchers to grasp key trends and focus areas in the field. It can inform the design and implementation of MOOCs for more effective educational outcomes.

This study presents novel methodologies and important findings for advancing research and practice in MOOCs.