Search Results (283)

This systematic review comprehensively explores the integration of Extended Reality (XR) technologies, comprising Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), into New Zealand’s STEM education framework. In alignment with PRISMA 2020 guidelines, we systematically analyzed 127 peer-reviewed studies from the Web of Science (n = 48), Scopus (n = 57), and Dimensions (n = 22) and incorporated 15 grey literature sources, resulting in 142 studies included in the review. Our meta-analysis found substantial improvements in student conceptual understanding from XR-enhanced STEM modules. Specifically, we observed an average increase of 23.4% when compared to traditional instructional methods (95 percent Confidence Interval: 18.7 to 28.1 percent, p < 0.001). These gains were especially prominent in interactive learning environments where immersive XR applications supported deeper engagement and the visualization of abstract STEM concepts. The qualitative synthesis highlighted several key barriers that limit effective XR integration. These include technological infrastructure gaps reported in 68 percent of reviewed studies, a critical need for educator training cited by 82 percent of studies, and curriculum alignment issues present in 57 percent of cases. Methodological quality was assessed using the Mixed Methods Appraisal Tool (MMAT) 2018, and the qualitative component employed a deductive thematic coding approach with inter-coder reliability verification. Successful institutional implementations were also identified. At Auckland University of Technology, XR-supported courses produced a 67 percent increase in student engagement, while Wellington High School achieved a 41 percent reduction in STEM achievement gaps through targeted XR interventions. Based on the evidence, we propose a four-phase implementation framework that addresses the technological, pedagogical, and policy requirements for sustainable XR adoption. These findings highlight the role of immersive technologies in supporting human-centered digital transformation and future skills development in the transition to Industry 5.0. The review contributes evidence-based insights that support the transition from technology-driven approaches associated with Industry 4.0 to the human-centered, socially oriented priorities of Industry 5.0. It also identifies critical research gaps, particularly in long-term learning outcomes and the integration of Mātauranga Māori within XR-enabled STEM environments. Full article

Immersive technologies—such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR)—are increasingly adopted in cultural heritage settings to support education, public engagement, and digital preservation. This scoping review systematically maps existing research on immersive learning within cultural heritage contexts, identifying major trends, pedagogical approaches, and reported outcomes. Following the PRISMA-ScR framework, nineteen studies were selected from 235 publications published between 2016 and 2025 across four databases: ACM Digital Library, Web of Science, ProQuest, and Scopus. Findings reveal a predominant focus on enhancing learner motivation, engagement, and the perceived authenticity of immersive experiences. However, empirical validation of learning outcomes—particularly regarding sustained knowledge retention, critical reflection, and inclusive participation—remains scarce. Persistent gaps are also evident in accessibility and scalability, alongside ethical concerns related to cultural sensitivity, power asymmetries, and the representation of diverse heritage voices. By foregrounding participatory and co-creation approaches, this review highlights how collaborative design processes can enhance learner engagement and support the sustainable digital preservation of cultural heritage. Full article

The burden of disability is rising rapidly in Africa, where a severe shortage of rehabilitation professionals and limited infrastructure create a major treatment gap. Immersive virtual reality and serious games have shown promise for upper limb rehabilitation, but current extended reality (XR) solutions lack personalization, cultural adaptability, real-time feedback, and scalability. This perspective paper proposes a conceptual AI-enhanced XR framework tailored to African low- and middle-income countries. We identify how generative AI, large language models, multiagent systems, and explainable AI can address specific rehabilitation barriers. The framework integrates these four pillars into a three-layer architecture covering content creation, interaction, and decision support. We analyze implementation considerations specific to African contexts—infrastructure, capacity building, cultural adaptation, ethics, and financing—and outline a detailed research agenda with near, medium, and longer term priorities. Realizing this vision requires co-design with African communities, investment in local capacity, adaptation to infrastructure constraints, and development of ethical frameworks. AI-enhanced XR has the potential to democratize access to quality rehabilitation across Africa, but this potential must be validated through rigorous, context-sensitive research. Full article

This study presents an integrated bibliometric analysis (BA) and systematic literature review (SLR) of construction safety research (CSR) to examine its evolution and emerging technological directions. It aims to move beyond descriptive mapping by linking long-term research trends with recent technological advancements to provide a structured understanding of how construction safety is transitioning toward data-driven and resilient systems. Utilising the PRISMA-guided approach, 1979 publications were analysed, revealing an average annual growth rate of 18%, driven by increasing safety concerns and the rapid implementation of digital technologies. The findings demonstrate that conventional safety research, centred on hazard identification, safety culture, and management commitment, is gradually being complemented by advanced technologies such as artificial intelligence (AI), machine learning (ML), extended reality (XR), and digital twins. These technologies enable predictive risk assessment, real-time monitoring, and immersive training, supporting a shift from reactive to proactive safety management. Despite these advancements, critical gaps remain, including limited real-world validation of AI-based systems, insufficient integration of technologies into cohesive frameworks, and underexplored socio-cultural factors influencing adoption. These challenges were addressed by proposing a research-to-practice framework for integrating emerging technologies into construction safety management. The framework incorporates technological, organisational, and human factors to enhance adaptability, risk management, and overall construction project resilience. Additionally, the research contributes to the body of knowledge by providing a comprehensive and analytically grounded framework that bridges the gap between research and practical implementation, while also identifying future research directions to support the development of intelligent, resilient, and adaptive construction safety systems. Full article

Background and Objectives: Artificial intelligence (AI) and extended reality (XR) are increasingly being integrated into telemedicine, yet clinician adoption depends not only on perceived utility but also on digital preparedness and technology-related burden. This study compared clinician acceptance of AI-only, XR-only, and combined AI+XR telemedicine scenarios and examined whether AI literacy, health literacy, technostress, age, and sex explained variability in acceptance. Materials and Methods: We conducted a cross-sectional, anonymous online vignette survey among 117 resident physicians and nurses from a tertiary-care hospital and affiliated outpatient clinics in Western Romania. Participants evaluated three randomized telemedicine scenarios (AI-only, XR-only, and AI+XR) using a 3-item Acceptance Index scored from 1 to 4. Additional measures included a study-developed AI literacy quiz, the Romanian-validated HLS-EU-Q16, an adapted brief technostress scale, prior AI/XR exposure, perceived accessibility, perceived value, privacy concern, and demographic variables. Results: Acceptance was highest for the combined AI+XR scenario (3.74 ± 0.49), followed by AI-only (3.64 ± 0.56) and XR-only (3.49 ± 0.64). AI+XR acceptance was significantly higher than AI-only and XR-only acceptance (both p < 0.001), although the absolute between-scenario differences were modest. Residents reported consistently higher acceptance than nurses across all scenarios, whereas sex differences were small and non-significant; younger age showed only weak inverse associations with acceptance. AI+XR acceptance correlated positively with AI literacy (ρ = 0.60) and health literacy (ρ = 0.23), and negatively with technostress (ρ = −0.47). In multivariable analysis, higher AI literacy (β = 0.603, p < 0.001) and health literacy (β = 0.241, p < 0.001) independently predicted higher AI+XR acceptance, whereas technostress was inversely associated (β = −0.212, p < 0.001). Conclusions: In this sample, clinicians rated the integrated AI+XR vignette most favorably, but the observed differences between scenarios should be interpreted cautiously and as hypothesis-generating rather than definitive evidence of superiority. Acceptance appeared to depend more on digital readiness and technostress than on age or sex, supporting implementation strategies focused on literacy-building, workflow fit, and burden reduction. Full article

Competency in musculoskeletal (MSK) ultrasound requires learners to relate probe manipulation to spatial reasoning, image projection, and the appearance of characteristic artefacts, which remains challenging during early training due to the limited spatial context provided by conventional instructional resources. This study investigates whether reconstructing real MSK ultrasound examinations in an immersive extended reality (XR) environment is perceived as useful for early familiarisation with probe handling and image interpretation. The proposed system reproduces ultrasound acquisitions using synchronised ultrasound video, six-degree-of-freedom probe tracking, and surface scans acquired from cadaveric specimens, enabling the reconstruction of spatially accurate probe trajectories with each ultrasound frame linked to a corresponding position and orientation. Within the XR environment, users can interactively explore these trajectories or observe automated playback in which the recorded probe motion is presented together with the corresponding ultrasound sequence. An exploratory evaluation with healthcare professionals was conducted to assess perceived usefulness and clarity of spatial relationships. The results indicate that participants perceived spatially coherent playback of real ultrasound examinations in XR as a potentially useful aid for understanding probe–image relationships. These findings suggest the feasibility of this approach as a complementary resource for introductory MSK ultrasound training. Full article

Purpose: This study provides a critical examination of the literature on applying artificial intelligence (AI) and Extended Reality (XR) in restaurant settings and related foodservice operations. It focuses on how AI and XE influence consumer nutrition awareness and decision-making about food choices, and their implications for customer satisfaction, loyalty, and service delivery in foodservice environments. Design/methodology/approach: The study adopts a systematic literature review (SLR) approach following the PRISMA method. An initial search identified over 3900 academic papers published between 2016 and 2025. Studies were selected on the basis of predetermined inclusion and exclusion criteria, and 26 peer-reviewed articles were analyzed. The review provides a conceptual synthesis and develops propositions for practical applications and future research directions. Findings: The review reveals a shift from static systems that rely on optimization, toward adaptive and user-centered solutions that are behavior-oriented. AI applications predominate in the case of calorie tracking, personalized recommendations, and menu planning. Though deployment of XR technologies (e.g., AR and VR) is less prevalent, they offer potential for immersive, and real-time interventions. A key distinction emerges between studies demonstrating empirical effectiveness (e.g., improved understanding and healthier choices) and those focused on technical and/or conceptual developments. To date, there has been limited validation of behavioral impacts in foodservice settings. Originality: This study offers a theory-informed conceptualization of AI and XR applications in restaurant and foodservice contexts by integrating three perspectives: hospitality (menus and dining experience), nutrition (dietary awareness and healthier choices), and human–technology interaction (technology acceptance and user engagement). The study reconceptualizes AI- and XR-enabled systems as behavioral intervention tools and outlines a focused research agenda for advancing nutritional communication in foodservice environments. Full article

Extended reality (XR), encompassing augmented reality (AR), virtual reality (VR), and mixed reality (MR), is a key enabling technology for virtual worlds, and XR-related patents continue to grow rapidly. However, patent-based XR technology analysis faces a fundamental challenge: document–keyword matrix (DKM) built from patent titles and abstracts are typically high dimensional, sparse, and often exhibit excess zeros, which can distort inference when conventional text mining pipelines are applied without a generative count perspective. In this study, we propose a statistically grounded XR technology analysis framework that combines likelihood-based count modeling with interpretable structure mining to map XR sub-technologies from a patent DKM. Using an XR patent–keyword matrix, we fit Poisson regression (PR), negative binomial regression (NBR), and zero-inflated negative binomial regression (ZINBR) models via maximum likelihood estimation (MLE), controlling for document-length effects. Model selection by Akaike information criterion (AIC) consistently favored NBR for both target keywords, indicating substantial overdispersion in XR patent counts. We interpret exponentiated coefficients as incidence rate ratios (IRRs) and construct a technology relatedness network from significant IRR edges, revealing a dual-axis XR structure: reality is anchored in an AR or VR experience and content axis such as virtual and augment, whereas extend is embedded in a structure and integration axis for example, surface, edge, layer, and connectivity-related terms. To show how the proposed method can be applied to real domains, we searched the XR patent documents, and analyzed them for XR technology analysis. Full article

Extended Reality (XR) and Artificial Intelligence (AI) are increasingly converging within cyber–physical infrastructures, including digital twins, the Spatial Web, and smart-city systems. These environments require new frameworks for understanding how human performance emerges through sustained interaction with immersive interfaces and adaptive computational agents. This paper introduces the TAXI–XI-CAP framework, a two-layer model that links psychobiological mechanisms of XR–AI interaction to higher-level, experimentally testable capability constructs. The TAXI layer defines 42 mechanisms spanning perception, cognition, physiology, sensorimotor control, and social coordination, while XI-CAP organizes these into capability patterns such as remote dexterity, distributed cognition, and adaptive workload regulation. Derived through a theory-guided synthesis across XR, neuroscience, and human–automation interaction, the framework models performance as emerging from interacting mechanisms under real-world constraints. A validation-oriented research agenda is proposed, emphasizing mechanism-level measurement, capability-level evaluation, and longitudinal testing. The TAXI–XI-CAP framework provides a structured basis for hypothesis generation, comparative analysis, and empirical validation of XR–AI systems, supporting the development of reliable, scalable, and human-centered Extended Intelligence infrastructures. Full article

Competence-oriented Education for Sustainable Development requires evidence that immersive and gamified learning experiences elicit sustainability-relevant change beyond short pre–post windows. This study examines the Art Nouveau Path, a location-based mobile augmented reality heritage game implemented in Aveiro, Portugal, using a four-wave repeated cross-sectional design with anonymous student samples: baseline (S1-PRE, N = 221), immediate post-activity (S2-POST, N = 439, validated n = 438), follow-up (S3-FU, N = 434), and distant follow-up (S4-DFU, N = 69, validated n = 67). Analyses were anchored in a shared 25-item GreenComp-based questionnaire (GCQuest) block targeting Embodying Sustainability Values (ESVs; scale of 1 to 6) and combined distribution-aware descriptives, nonparametric omnibus, and pairwise tests with Holm correction, and planned robustness checks including equal-n downsampling and alternative scoring. Results displayed a pronounced post-activity peak (S2-POST), partial attenuation at follow-up (S3-FU), and convergence toward baseline at distant follow-up (S4-DFU), accompanied by loss of the high-agreement tail. Item-level contrasts suggested that later-wave declines concentrated in effortful self-regulation and critical appraisal items, whereas value endorsement items were more stable. These findings indicate that field-deployable mobile AR heritage paths may generate strong proximal competence-aligned signals; nevertheless, durable enactment-oriented change is likely to require structured reinforcement and integration into broader curricular sequences. Full article

The concept of “human-centric, sustainable and resilient smart cities” in Industry 5.0 (I5.0) refers to urban socio-technical ecosystems in which digital infrastructures and services are explicitly oriented toward human well-being, ecological stewardship, and systemic resilience rather than purely technological optimization or automation. Grounded in the I5.0 framework, which promotes human-centricity, sustainability, and resilience as equally important pillars, this paradigm repositions smart cities as value-driven environments that integrate enabling technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), Extended Reality (XR), and related digital infrastructures within participatory, transparent, ethical, and accountable governance structures. From this perspective, technologies function as means through which cities develop higher-order capabilities for sensing, decision support, coordination, interaction, and adaptive service delivery. At the same time, they address digital divides and include measures that promote and protect inclusion, trust, and long-term socio-environmental viability. This entry synthesizes the conceptual foundations, technological enablers, capability-oriented architecture, governance implications, and emerging challenges that influence the transformation of smart cities into human-centric, sustainable, and resilient innovation systems in the I5.0 era. Full article

The current literature on electrical system maintenance highlights three technology domains—Building Information Modeling (BIM), Digital Twin (DT), and extended reality (XR)—that have independently demonstrated strong potential for improving lifecycle information management, predictive analytics, and operational support. However, their convergence remains largely underexplored, particularly in electrical system maintenance. This paper provides a structured review of BIM–DT–XR convergence in electrical system lifecycle management, examining their roles across lifecycle phases and their integration through literature synthesis and cross-domain implementation evidence. BIM is analyzed as a basis for modeling and integrating facility management with electrical asset lifecycles; DT as a framework for dynamic system representation and applications in electrical and power systems; and XR as a means of visualizing and interacting with BIM-DT environments. Cross-domain implementation evidence from an industrial electrical facility and a tertiary smart-building pilot shows that BIM–DT–XR integration is technically feasible at pilot scale. However, the analysis identifies five structural integration gaps: semantic misalignment between building-oriented IFC and grid-oriented CIM ontologies; fragmented standard adoption; inconsistent data governance and naming practices; validation approaches focused on syntactic rather than dynamic model fidelity; and the separation of XR visualization from predictive DT capabilities. The implementation evidence further indicates that real-world deployment remains constrained by data quality limitations, integration complexity, cost factors, and interoperability with legacy systems. The review concludes that, despite the maturity of individual technologies, their effective application depends on advances in semantic alignment, lifecycle data governance, validation of dynamic models, and scalable integration frameworks, enabling the transition toward integrated, interoperable, and lifecycle-aware infrastructures for electrical system maintenance. Full article

This study investigates how virtual reality systems can support inclusive access to culturally restricted sacred heritage sites. Two extended reality (XR) approaches were developed and deployed in a real-world setting: a VR360 virtual tour and an AI-driven immersive virtual reality prototype with conversational interaction. A research-in-the-wild, between-subjects study was conducted with 136 participants using mixed methods, including standardized questionnaires (System Usability Scale, User Engagement Scale, and Igroup Presence Questionnaire), retrospective interviews, and exhibition staff observations. The results reveal clear trade-offs between the two systems. The VR360 system demonstrated higher usability and operational reliability, requiring minimal supervision and technical resources, whereas the AI-driven immersive VR system supported embodied exploration and conversational inquiry, which was associated with higher spatial presence and helped visitors address questions during exploration. Qualitative findings further indicate that conversational interaction enhanced user experience but also introduced greater technical complexity and staffing requirements. Overall, the study provides empirical insights for designing and deploying XR systems in heritage contexts and highlights how different levels of immersion and interaction influence usability, presence, and operational feasibility when supporting inclusive access to culturally restricted sites. Full article

This study examines the design and pedagogical evaluation of Extended Reality (XR) applications, with a primary focus on location-based Augmented Reality (AR). The XR applications were implemented within an environmental education program delivered by the Education Center for the Environment and Sustainability (E.S.E.C.) of Kastoria, aiming to enhance students’ understanding of lake ecosystems and environmental awareness through immersive, situated learning experiences. The development followed the ADDIE instructional design framework and was grounded in principles of experiential and situated learning. The educational intervention was conducted in an authentic field setting along the shoreline of Lake Kastoria and combined location-based AR activities with complementary immersive VR experiences. Evaluation data were collected through a structured questionnaire administered to 271 primary and secondary school students, employing XR-relevant constructs including Challenge/Satisfaction/Enjoyment, Ease of Use, Usefulness/Knowledge, Experiential and Situated Learning, Interaction/Collaboration, and Intention to Reuse. In addition, accompanying teachers provided supplementary qualitative feedback to support the interpretation of the findings under authentic field conditions. Descriptive statistical analysis indicated consistently high scores across all constructs (M = 3.27–4.40, SD = 0.41–0.64). Pearson correlation analysis revealed strong associations between Experiential/Situated Learning and Usefulness/Knowledge (r = 0.737), Experiential/Situated Learning and Challenge/Satisfaction/Enjoyment (r = 0.642), Intention to Reuse and Challenge/Satisfaction/Enjoyment (r = 0.635), as well as Usefulness/Knowledge and Challenge/Satisfaction/Enjoyment (r = 0.619). Multiple regression analyses further supported key relationships, including Usefulness/Knowledge as a predictor of Experiential/Situated Learning (β = 0.57, p < 0.001), Experiential/Situated Learning as a predictor of Challenge/Satisfaction/Enjoyment (β = 0.47, p < 0.001), and Interaction/Collaboration as a predictor of Intention to Reuse (β = 0.31, p < 0.001). Intention to reuse was mainly associated with interaction and collaboration, enjoyment and motivation, perceived usefulness/knowledge, and ease of use. Overall, the findings indicate that XR-supported outdoor learning is positively associated with key experiential, emotional, social, and perceived learning dimensions when embedded within a coherent pedagogical framework. Full article

Recent advances in extended reality (XR) have enabled immersive virtual flight experiences for applications such as entertainment and teleoperation support. However, XR-based flight systems that rely primarily on audiovisual cues often fail to evoke a compelling sense of flight and embodied sensation. This study investigates how adaptive wind feedback enhances subjective flight perception in a virtual flight simulation system, Drone Rider. We implemented direction- and velocity-adaptive wind feedback that synchronizes airflow intensity and direction with the user’s motion in the virtual environment, focusing on perceptual effects in a controlled manner to identify key design factors, rather than reproducing aerodynamically accurate airflow. To explore flexible system configurations, two fan installation positions were compared: front-mounted and bottom-mounted. A questionnaire-based user study revealed that adaptive wind feedback significantly enhanced the sense of flight, self-location, and agency compared with the constant-wind and no-wind conditions. However, no significant differences were observed between velocity-adaptive wind and direction- and velocity-adaptive wind conditions. Furthermore, wind delivered from beneath the user yielded flight sensations comparable to those generated by front-mounted airflow. These findings suggest that temporal coupling between airflow intensity and visual motion plays a central role in XR flight perception and provide practical design insights for immersive and flexible XR-based flight simulation systems. Full article