This study investigates immersive learning in virtual reality (VR), focusing on emotional engagement, technology efficacy, and AI interaction. Using Structural Equation Modeling (SEM), we explore both self-reported factors (e.g., Technology Acceptance, Emotional Engagement, Presence) and system-derived variables (e.g., GPT Usage, System Behavior). Results show that higher emotional engagement significantly enhances both technology adoption and efficacy. The model demonstrated excellent fit (CFI = 0.988, RMSEA = 0.069), explaining 54.5% to 70.7% of the variance in key constructs. Perceived presence was a strong predictor of adoption and engagement, emphasizing the role of immersive features in supporting learner interaction. A surprising finding revealed that AI interaction, while enhancing emotional engagement, also reduced the sense of presence, suggesting a trade-off between cognitive involvement and immersion. These findings highlight the importance of emotional design and AI interaction in improving engagement and outcomes in VR-based education.

Immersive Virtual Reality (VR) environments create new opportunities for interactive learning by integrating embodied control, real-time feedback, and spatial attention. To understand how learners engage with these environments, we use gaze-ray casting—a lightweight proxy for attention based on headset orientation—to examine how visual focus on avatar gestures shapes task behaviour and perceived system interactivity. Our findings show that gaze predicted system interaction (β = .726, R² = .61), but this effect only enhanced presence for learners with high technological efficiency (interaction β = .59). Crucially, gaze only predicted task activity when the UI overlays did not compete with avatar gestures. When interface elements occluded gesture space, gaze engagement dropped, and presence declined. Nonlinear analyses also revealed a tipping point: when both gaze and efficacy were high, dizziness reports spiked, an overload pattern missed in linear models. These results suggest that gaze-based engagement fosters immersion only when learners can fluently interpret system cues. Without adaptive support, active users may encounter strain rather than flow. Gaze-ray data, thus, offer a scalable diagnostic for detecting alignment, or friction, between learner attention and system design. Designing for immersive learning requires synchronising visual demands with user confidence and capacity, ensuring that interaction remains a source of motivation, not disruption.

Immersive Virtual Reality (VR) has the potential to transform learning, but its success depends not only on technical design but on how learners experience value, agency, and discomfort. This study models how technical efficacy (TE), technology adoption (TAM), and embodied presence (PRES) interact with dizziness (DIZ) and task design to shape performance in VR. Using structural equation modeling (SEM), generalized additive models (GAM), and multivariate regression, we found that TAM fully mediated the impact of TE on PRES (β = .542, p < .001), suggesting that technical fluency only enhances immersion when learners perceive the system as meaningful. Presence increased dizziness (β = .36, p = .001), but only TAM—rather than TE—sustained immersion under strain. A nonlinear moderation effect showed that effort (EFFSYS) predicted performance (PERFSYS) more strongly under high DIZ—especially in exploratory designs, where learners retained behavioral flexibility. In contrast, linear paths suppressed this dynamic, flattening performance variance. Despite similar DIZ levels across conditions, only exploratory paths enabled “productive strain,” converting discomfort into engagement. Our findings suggest that immersive learning emerges from the alignment of effort, motivation, and interaction design—not from realism alone. Designing for persistence, not just presence, is critical: discomfort can fuel engagement if learners can act, adapt, and understand why it matters.

As AI continues to reshape industries, enhancing AI literacy is essential for empowering learners to engage confidently and critically with emerging technologies. Virtual Reality (VR) presents opportunities to connect theoretical understanding with practical application, yet educational integration is often hindered by technical and pedagogical challenges. This study explores how immersive VR environments can be designed to promote AI literacy and identifies factors influencing students’ intent to adopt such technologies. Using Classlet—a VR platform incorporating interactive multimodal tasks, narrative-driven activities, and GenAI avatar interactions—we developed a virtual office where learners completed research tasks and simulation scenarios using instructor-generated prompts. A mixed-methods approach was employed across participants from Hong Kong and Malaysia, examining AI literacy in contexts such as fast fashion and European society. Regression analyses revealed that adoption intent was strongly predicted by enjoyment, perceived performance, and behavioral control (R² = 0.803), while post-intervention AI literacy was predicted by AI self-efficacy and enjoyment (R² = 0.421). Notably, female participants reported significantly lower AI efficacy (p = .042), highlighting the need to address baseline differences. Qualitative data underscored the engaging and immersive nature of the experience, while also revealing opportunities for improving GenAI prompt design to support more elaborative and reciprocal interactions.

This study investigates how technological and pedagogical factors influence students’ intention to engage with virtual worlds on educational metaverse platforms and examines the resulting learning outcomes in sustainability education. Traditional sustainability education often fails to effectively engage students with real-world challenges. Metaverse platforms provide immersive, interactive environments that bridge theoretical knowledge with practical application but face usability, complexity, and user comfort issues that can hinder engagement and learning. Using a mixed-methods approach, 54 undergraduate students from Hong Kong and the Philippines participated in sustainability modules via the Classlet metaverse platform. Regression analysis revealed that Ease of Use, Enjoyment, Perceived Performance, and Immersion accounted for 77.1% of the variance in intent to engage. Ease of Use and Enjoyment were the strongest positive predictors, while higher Immersion negatively impacted VR users, indicating that excessive complexity reduces usability. Additionally, gaming experience influenced enjoyment, with weekly gamers reporting higher engagement. Desktop users showed the highest intent to use the platform, whereas VR users experienced greater immersion but also more discomfort. Qualitative feedback highlighted the platform’s engaging and innovative features alongside technical and navigational challenges affecting learning outcomes. These findings highlight the need to balance interactivity, usability, and adaptability in educational technologies. Recommendations include implementing adaptive learning pathways, enhancing onboarding processes, and offering customizable interaction levels to accommodate diverse learner needs. Refining immersive learning approaches can better connect theoretical concepts with real-world sustainability applications, fostering increased student engagement and improved learning outcomes.

The purpose of this study was to evaluate the effectiveness and relevance of AI-powered non-player characters (NPCs) in educational settings within the metaverse platform Classlet, particularly within the domain of applied social sciences. Integrating Speech Act Theory, Prospect Theory, and the Recognition-Primed Decision Model into AI prompt templates enhanced interactions and positively impacted student engagement. The AI NPCs achieved a performance ratio of 128%, providing contextually relevant responses effectively maintained by the prompt templates. A survey on students’ perceptions of the AI and VR integration revealed positive user perceptions, with strong correlations between enjoyment, perceived usefulness, and intent to use. Correlational analysis showed a strong fit (R2 = 0.816) for user intent, which had a mean of 74%. U-tests also indicated that female and non-VR users encountered more technical difficulties. Overall, the results suggest new ways of using AI and VR to promote learning engagement and interactions within applied social sciences.

Abstract. Virtual Reality (VR) platforms hold significant potential to enhance student engagement through immersive and interactive learning experiences. These environments create dynamic spaces that can improve educational outcomes by fostering deeper engagement. However, existing research often overlooks critical motivational, cognitive, and social factors within VR settings, leading to fragmented and less effective learning experiences. This study examines how integrating these factors can enhance student participation and improve learning outcomes in VR educational contexts. Specifically, it applies the Technology Acceptance Model (TAM) to predict students' intent to use VR for learning. The findings indicate that incorporating these factors into TAM effectively predicts students' intent to use VR platforms, with key predictors including positive attitudes, enjoyment of immersive technology, and perceived performance. This study provides a solid foundation for understanding how motivational, cognitive, and social factors converge to influence learning outcomes in immersive environments, offering valuable insights for future research and practice in educational technology.

This study investigates the integration of Virtual Reality (VR) into STEM education to enhance student engagement and conceptual understanding. Immersive environments offer interactive, hands-on learning experiences that transform traditional pedagogical approaches. The research addresses key challenges in STEM education, including the lack of empirical support for effective scaffolding strategies and ongoing technological limitations faced by educators. Participants, consisting of engineering and computing students, completed both VR and non-VR tasks in four domains: food processing, audio compression, substations, and search engines. Findings showed that VR significantly enhanced engagement, comprehension, and the application of theoretical knowledge. However, some participants reported physical discomfort and technical barriers. Gender differences emerged, with female students rating the immersive experience more favorably, and engineering students exhibiting greater enthusiasm for VR than computing students. Linear regression results indicated a strong predictive model (R² = 0.826), with intent to use VR being driven primarily by perceived performance and usefulness. The study emphasizes the value of integrating narrative scaffolding, supportive design features, and continuous guidance to optimize the impact of VR in STEM learning. Future work should address usability concerns and further refine VR tools to support diverse learner needs.

This study investigates the integration of the metaverse and artificial intelligence (AI) avatars in social science education, amidst global challenges that require holistic approaches to cultivate critical global citizenship. While virtual reality (VR) offers immersive learning potential, the effectiveness of the metaverse and AI avatars in shaping educational experiences remains underexplored. This study examines the impact of immersive metaverse learning, including AI avatars, on students' perceptions and intentions to use this technology for social science education. The study explores metaverse-based learning across diverse social science topics, including transitional environments design, food waste management, linguistics research, computational thinking in sociology, and grammar analysis. Findings indicate strong student engagement with immersive learning, supporting experiential learning theories and demonstrating potential for complex topic exploration. Regression analysis reveals that ‘Function,’ ‘Usefulness,’ and ‘Interest’ significantly predict students’ intent to use metaverse-based learning (R² = 0.588, p < .001), underscoring the importance of engaging and interactive elements. However, students perceived environments with AI avatars as more difficult to navigate (p = 0.037), highlighting usability challenges despite their potential for interactivity. Further analysis showed that while AI avatars encouraged interaction, their limited implementation in this study may have restricted their perceived effectiveness. Additionally, students engaging with AI-driven environments expressed mixed experiences, with some appreciating the interactivity while others found them less intuitive. Further research is needed to explore long-term impacts, refine AI-driven learning interactions, and expand applications across diverse educational settings.

This study delves into the educational possibilities and user experiences offered by a Metaverse platform, utilizing immersive Virtual Reality (VR) to bolster engagement and learning in communication and grammar. In the wake of advancing digital technologies, there's an imperative to reevaluate conventional educational practices for their effectiveness in engaging students and fostering in-depth learning. Despite VR's potential in education, integrating these immersive experiences effectively into pedagogical frameworks and ensuring their accessibility and usability poses significant challenges. Our research employed a mixed-method approach, blending quantitative analysis to gauge user engagement, learning effectiveness, and acceptance of technology with qualitative feedback for deeper insight into user experiences. Participants navigated specially designed Metaverse scenarios, engaging with AI avatars through interactive tasks and narrative explorations across two distinct modules focused on grammar intricacies and the evolution of search technologies. The quantitative findings underscore a substantial correlation between users' interest and their intent to utilize the platform, accounting for 59% of the variance in intent. Qualitative responses highlight a robust engagement level and favorable perceptions of the Metaverse experience, particularly driven by the method being interesting. 

This study examines the effectiveness of a game-based metaverse platform in enhancing learning outcomes in economics education. Students were virtually transported back to the Great Depression within the metaverse. System data and self-assessment surveys assessed aspects such as ease of use and perceived usefulness for learning, evaluating their impact on student performance and their intent to use the metaverse for future learning. These measures also captured students' reported interest and enjoyment, gauging their engagement levels. According to self-assessment surveys, students found the metaverse platform engaging, relevant, vivid, and social, highlighting the successful integration of pedagogy and technology. The study's results are supported by regression analysis, which demonstrated a strong positive relationship with an R2 of 0.853, indicating that a significant proportion of variance in student engagement can be explained by the aesthetics of the metaverse platform and the interest it generated. Challenges such as technical issues and varying learning efficiencies were also noted. Overall, the study highlights the potential of game-based learning environments and virtual reality in economics education to foster student engagement and promote the adoption of innovative learning systems.

The use of the metaverse in education has gained increasing attention as a potential supplement to traditional teaching methods. This study aimed to investigate the impact of experiential learning on students' intent to use metaverse learning platforms and to explore how the metaverse can support these approaches. The study included participants from three countries and used metaverse scenes, such as a restaurant or Hong Kong scene, to complete learning tasks and interact with Non-Player Characters (NPCs) to complete assessments over a semester. The results of a correlational analysis showed that pedagogical factors had a greater impact on students' intent to use the metaverse for educational purposes than technical factors, which was unexpected. However, the study also identified challenges in adapting content to match the needs and skills of students who may not be familiar with games, as well as using the metaverse for more advanced pedagogical approaches, due to limitations in integrating content. Based on the findings, recommendations for educators, designers, and researchers are provided to enhance the effectiveness of metaverse-based education. Overall, the results of this study suggest that the metaverse can be a valuable addition to traditional teaching methods.

The goal of this study is to introduce and evaluate a novel online simulation method built upon buyer-seller roleplay in a private social network for housing economics education. This is at a time when classroom disruptions due to COVID-19 require new methods to engage with students asynchronously. While methods like game-based learning simulations show potential to engage, they are often high-fidelity and require high setup costs. This is also the case for existing housing simulation games, for which besides being single player mode, costs for technical customization and learning curve reduces adoption in the classroom. In this context, the use of social networks to facilitate a low-fidelity buyer-seller housing roleplay may provide flexible learning goals and peer engagement, but its implementation is unclear. This gap in knowledge has motivated this investigation, for which undergraduate students in Hong Kong participated in property buyer-seller roleplay. Students posted available property and buyers bid for them using comments on a private social media app, Soqqle. 

Despite the rapid advancement of virtual reality (VR) and its integration into educational settings, the adoption of metaverse learning platforms often encounters challenges. These include technical limitations and a lack of understanding of how these platforms impact learning effectiveness and user engagement. Previous studies have revealed mixed outcomes regarding the effectiveness of VR in education, with many platforms failing to meet user expectations in terms of usability and learning outcomes. This uncertainty hampers the broader adoption of immersive learning technologies. Thus, this study aims to investigate what factors contribute most significantly to the effectiveness and user adoption of metaverse learning platforms. Specifically, it examines how perceived usefulness and efficiency influence learners' intentions to use these platforms. Linear regression analysis was employed to analyze the data, revealing that perceived usefulness (USE) and perceived efficiency (PERF2) are significant predictors of learners’ intent to use the platform, explaining 62.6% of the variance in intent scores.

The Metaverse is rapidly gaining recognition as an innovative educa- tional tool, offering immersive and interactive experiences that align with con- temporary teaching methodologies. This study evaluates the Metaverse’s efficacy in enhancing student engagement and motivation, with a focus on its design attributes. By integrating quantitative analyses of student perspectives with qual- itative insights, the research identifies key factors—ease of acquiring new skills, user-perceived efficiency, and the interactivity of the design—as central to fos- tering engagement. The investigation involved 51 students from language and European history courses, who engaged in Metaverse simulations to practice rel- evant skills: a telephony group honed business communication in a virtual office, while a history group delved into the 15th-century spice trade in European set- tings. Their uniformly positive responses underscore the Metaverse’s potential to engage a broad spectrum of learners. Notably, the simplicity of skill acquisition and perceived learning efficiency accounted for approximately 59.9% of the vari- ance in students’ willingness to use the Metaverse for educational purposes. The study also sheds light on gender-specific preferences, with female students show- ing a higher propensity towards the method and explores the impact of moderate gaming experience on adaptability to this novel learning medium. These findings highlight the Metaverse’s versatility as an educational resource and underscore the importance of considering diverse learner backgrounds to optimize its pedagogical value.

Through an education-centric metaverse learning application, this research aims to assess the use of narrative richness to deliver media, language, and sustainability literacy education. The 21st-century learning needs require teaching and learning resources to be shared and managed more effectively across institutions. The use of metaverse features can help to manage varying narrative richness to boost learning reflection and attitude. Despite its potential, it is unclear how narrative richness in the metaverse can enhance teaching and learning. The study proposed in this research, which includes institutions from four Asian countries, is driven by this knowledge and evidence gap. Module leaders conceptualize and evaluate a purpose-built metaverse-learning application to produce rich and realistic learning experiences. We utilize narratives to enhance the realism of learning experiences and will assess the effects of narrative richness on learning reflection and attitude.