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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.

Research on knowledge creation within eSports learning is scarce. This study extends the understanding of competition-oriented collaborative learning in eSports by examining the relationship between the dynamics of knowledge creation modes and the continuum of the motivational profile, along with the moderating effects of mutualistic co-presence therein.

Participants were recruited from the community of massively multiplayer online gamers (MMOGs). Through a quantitative survey, their motivations (i.e. self-extrinsic, self-intrinsic, peer-extrinsic and peer-intrinsic motivations), knowledge creation involvements (i.e. internalization, externalization, combination and socialization) and perception of mutualistic benefit of self and peers were captured for hypothesis testing.

Significant and positive direct relationships were observed between four motivations and four knowledge creation modes. The mutualistic co-presence positively moderated the positive relationship between the self-extrinsic, peer-extrinsic and peer-intrinsic motivations and socialization. When mutualistic self-benefit were outweighed, peer-extrinsic motivated gamers became less likely to perform internalization, whereas self-extrinsic and peer-extrinsic motivated gamers were less likely to perform combination.

This study is among the first to rationalize the relationship between motivational profile and the dynamics of knowledge creation in eSports learning. The conceptualization of the new construct – mutualistic co-presence – using the ecological concept of symbiosis is uncommon in prior literature. The findings also demonstrate that the four modes of knowledge creation in eSports learning are continuous and interwoven; they can be initiated at any point and do not necessarily occur in a specific sequence.

The research paper examines the complex relationship between gamification, student engagement and academic performance in educational environments. The study employed a structural equation model that highlights important connections among key constructs within the educational setting.

This research aims to explore the connection between gamification, student engagement and academic performance in educational settings. The study employs various statistical techniques such as factor analysis, Kaiser–Meyer–Olkin (KMO), Bartlett’s test, component transformation matrix, correlation and regression analysis, descriptive statistics, ANOVA, coefficients and coefficient correlations, residual statistics and confirmatory factor analysis (CFA) to analyze the data.

It was found that active participation by the instructor and good time management skills have a positive impact on student engagement levels (β = 0.380, p < 0.001; β = 0.433 and p < 0.001). However, peer interaction does not significantly predict student engagement (β = −0.068 and p = 0.352). Additionally, there is a positive correlation between student engagement and performance (β = 0.280 and p < 0.001).

The study highlights the importance of innovative design to fully utilize gamification. Future research should consider design, user characteristics and educational context. The findings can guide informed decisions about gamification in education, fostering motivation and learning objectives.

The study presents a reliable tool for assessing student engagement and performance in educational settings, demonstrating high Cronbach’s alpha and robust reliability. It identifies student engagement and time management as significant predictors of Global Learning Outcome. The findings can inform decisions on implementing gamification in educational settings, promoting intrinsic motivation and aligning with learning objectives.

The research highlights the transformative impact of gamification on educational practices, highlighting its potential to enhance student experiences, motivate, promote diversity and improve long-term academic performance, highlighting the trend of integrating technology into education.

In today’s ever-changing education landscape, it is essential to incorporate innovative techniques to keep students engaged and enthusiastic about learning. Gamification is one such approach that has become increasingly popular. It is a concept that takes inspiration from the immersive world of games to enhance the overall learning experience.

This study holistically and systematically consolidates the available research on digital reading to reveal the research trends of the past 20 years. Moreover, it explores the thematic evolution, hotspots and developmental characteristics of digital reading. This study, therefore, has the potential to serve as a research guide to researchers and educators in relevant fields.

The authors applied a bibliometric approach using Derwent Data Analyzer and VOSviewer to retrieve 2,456 publications for 2003–2022 from the Web of Science (WoS) database.

The results revealed that most studies' participants were university students and the experimental methods and questionnaires were preferred in digital reading researches. Among the influential countries or regions, institutions, journals and authors, the United States of America, University of London, Electronic Library and Chen, respectively, accounted for the greatest number of publications. Moreover, the authors identified the developmental characteristics and research trends in the field of digital reading by analyzing the evolution of keywords from 2003–2017 to 2018–2022 and the most frequently cited papers by year. “E-books,” “reading comprehension” and “literacy” were the primary research topics. In addition, “attention,” “motivation,” “cognitive load,” “dyslexia,” “engagement,” “eye-tracking,” “eye movement,” “systematic analysis,” “meta-analysis,” “smartphone” and “mobile reading/learning” were potential new research hotspots.

This study provides valuable insights into the current status, research direction, thematic evolution and developmental characteristics in the field of digital reading. Therefore, it has implications for publishers, researchers, librarians, educators and teachers in the digital reading field.

To support achieving sustainable development goals (SDGs), we integrated science, technology, engineering and math (STEM) and extended reality technologies into an artificial intelligence (AI) learning activity. We developed Feature City to facilitate students' learning of AI concepts. This study aimed to explore students' learning outcomes and behaviors when using Feature City.

Junior high school students were the subjects who used Feature City in an AI learning activity. The learning activity consisted of 90-min sessions once per week for five weeks. Before the learning activity, the teacher clarified the learning objectives and administered a pretest. The teacher then instructed the students on the features, supervised learning and unsupervised learning units. After the learning activity, the teacher conducted a posttest. We analyzed the students' prior knowledge and learning performance by evaluating their pretest and posttest results and observing their learning behaviors in the AI learning activity.

(1) Students used Feature City to learn AI concepts to improve their learning outcomes. (2) Female students learned more effectively with Feature City than male students. (3) Male students were more likely than female students to complete the learning tasks in Feature City the first time they used it.

Within SDGs, this study used STEM and extended reality technologies to develop Feature City to engage students in learning about AI. The study examined how much Feature City improved students' learning outcomes and explored the differences in their learning outcomes and behaviors. The results showed that students' use of Feature City helped to improve their learning outcomes. Female students achieved better learning outcomes than their male counterparts. Male students initially exhibited a behavioral pattern of seeking clarification and error analysis when learning AI education, more so than their female counterparts. The findings can help teachers adjust AI education appropriately to match the tutorial content with students' AI learning needs.

This paper aims to examine the impact of metaverse experiences on customers’ offline behavioral intentions: How do customers’ visits to a hospitality business’s virtual property in the metaverse affect their intentions to visit the physical property in the real world?

Based on the general learning model and social cognitive theory, this research hypothesizes the positive impact of metaverse experiences on customers’ visit intentions and explores two boundary conditions for positive impact: user–avatar resemblance and servicescape similarity. Two experimental studies were conducted.

Metaverse experience has a significant impact on customers’ visit intentions, and this impact is moderated by user–avatar resemblance and servicescape similarity.

This research addresses the call for empirical studies regarding the effects of metaverse experience on people’s behavioral intentions.

As one of the earliest empirical studies on the marketing effects of the metaverse, this research provides a basis for future metaverse studies in the hospitality field.

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.

The challenges facing 21st-century society are becoming increasingly complex, requiring the development of new citizen competencies. This study aims to validate an educational model focused on developing complex thinking in higher education students. Current educational models lack future-ready competencies, necessitating the emergence of new models to guide future generations toward the common good.

This was an adaptation of the causal-layered analysis (CLA) applied to 415 participants from higher education institutions in Mexico, Panama and Spain. Sessions were designed to present the proposed educational model and explore participants’ perceptions of its significance and contributions to future education.

Key findings include the following: participants perceived complexity as difficult and challenging; causes of problems were linked to outdated educational models requiring replacement by those that develop students’ competencies; participants envisioned changes that would develop individuals capable of understanding and transforming society; and participants recognized the model’s transformative potential, offering a novel proposal for 21st-century education.

This research sought to gather opinions from different stakeholders using the CLA methodology, providing a deep understanding of participants’ perspectives on the proposed solution.

The flipped classroom model is an emerging teaching pedagogy in universities, colleges and secondary schools. This model will likely be successful if students prepare and acquire basic knowledge before class hours. Pre-class video lectures are common for students to access knowledge before class hours. However, students often do not watch the pre-class videos or do so only immediately before class hours due to poor engagement and supporting strategies, which can have detrimental effects on their learning achievement. To address this issue, embedding quiz questions into pre-class recorded videos may increase the completion of pre-class activities, students' engagement and learning success. This study examines the effect of a quiz-based flipped classroom (QFC) model to improve students' learning achievement and engagement in a computer science course.

The study involved 173 participants divided into experimental and control groups. The experimental group consisted of 78 students who used the QFC model, while the control group consisted of 73 students who used the conventional flipped classroom (CFC) model.

The 10-week experiment showed that the QFC model effectively improved students' learning achievement and engagement (both behavioral and agentic) compared to the CFC model.

Embedding quiz strategy into the pre-class video demonstrated the potential support to enhance the efficacy of the CFC model. Based on the results of this research, the authors recommended that flipped educators can use the quiz strategy to minimize pre-class issues (especially students' disengagement).

This research adds to the existing literature by evaluating the effect of the newly proposed model on students' learning outcomes and engagement. This study's results can guide colleges and universities intending to implement a blended learning or flipped learning model. The research also gives design, content and course implementation guidelines, which can help engage students to achieve their learning objectives.

This study examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on acquiring tacit knowledge to enhance academic performance in higher education suggests that this research area holds significant importance for experts and policymakers. Consequently, this study aims to explore the factors that influence academic research performance at Chinese universities by acquiring tacit knowledge.

To achieve the study aims, the current approach utilizes the research technique based on the socialization, externalization, internalization and combination (SECI) model and knowledge management (KM) theory. To analyze the study objective, the authors collected data from post-graduate students at Chinese universities and analyzed it using structural equation modeling (SEM) to test the model and hypotheses.

The results indicated that social interaction, internalization and self-motivation have a positive impact on academic research performance through the acquisition of tacit knowledge. Furthermore, the findings suggest that academic researchers can acquire more knowledge through social interaction than self-motivation, thereby advancing research progress.

This study addresses the critical issues surrounding the acquisition of tacit knowledge and presents a comprehensive framework and achievements that can contribute to achieving exceptional academic performance.