Search Results (112)

Immersive technologies such as augmented reality (AR) and virtual reality (VR) have emerged as powerful tools in cultural heritage education and preservation. Building on prior work that demonstrated the effectiveness of gamified XR applications in engaging users with heritage content and drawing on existing studies in neuroscience and cognitive psychology, this study explores how immersive experiences support multisensory integration, emotional engagement, and spatial presence—all of which contribute to the deeper encoding and recall of heritage narratives. Through a theoretical lens supported by the empirical literature, we argue that the interactive and embodied nature of AR/VR aligns with principles of cognitive load theory, dual coding theory, and affective neuroscience, supporting enhanced learning and memory consolidation. This paper aims to bridge the gap between technological innovation and cognitive understanding in cultural heritage dissemination, identifying concrete design principles for memory-driven digital heritage experiences. While promising, these approaches also raise important ethical considerations, including accessibility, cultural representation, and inclusivity—factors essential for equitable digital heritage dissemination. Full article

Urban green spaces (UGSs) and forests play a vital role in shaping sustainable and livable cities, offering not only ecological benefits but also spaces that are essential for human well-being, social interactions, and everyday life. Understanding the landscape features that resonate most with public preferences is essential for enhancing the appeal, accessibility, and functionality of these environments. However, traditional approaches—such as surveys or single-data analyses—often lack the nuance needed to capture the complex and multisensory nature of human responses to green spaces. This study explores a cross-modal methodology that integrates natural language processing (NLP) and deep learning techniques to analyze text and image data collected from public reviews of 19 urban parks in Nanjing. By capturing both subjective emotional expressions and objective visual impressions, this study reveals a consistent public preference for natural landscapes, particularly those featuring evergreen trees, shrubs, and floral elements. Text-based data reflect users’ lived experiences and nuanced perceptions, while image data offers insights into visual appeal and spatial composition. By bridging human-centered insights with data-driven analysis, this research provides a robust framework for evaluating landscape preferences. It also underscores the importance of designing green spaces that are not only ecologically sound but also emotionally resonant and socially inclusive. The findings offer valuable guidance for the planning, design, and adaptive management of urban green infrastructure in ways that support healthier, more responsive, and smarter urban environments. Full article

This study introduces an educational framework that merges 3D modeling with AI-assisted narrative interaction to apply digital technology in cultural heritage education, exemplified by an ancient carriage culture. Through immersive tasks and contextual narratives, the course notably improved learners’ professional skills and cultural awareness. Experimental results revealed significant knowledge acquisition among participants post-engagement. Additionally, the user experience improved, with increased satisfaction in the narrative interaction design course. These enhancements led to heightened interest in cultural heritage and deeper knowledge acquisition. Utilizing Norman’s three-layer interaction model, Ryan’s contextual narrative theory, and Falk and Dierking’s museum learning experience model, the study developed a systematic course for multi-sensory design and contextual interaction, confirming the positive impact of multimodal interaction on learning outcomes. This research provides theoretical support for the digital transformation of cultural education and practical examples for educational practitioners and cultural institutions to implement in virtual presentations and online learning. Full article

Ubiquitous blended learning, leveraging mobile devices, has democratized education by enabling autonomous and readily accessible knowledge acquisition. However, its reliance on traditional interfaces often limits learner immersion and meaningful interaction. The emergence of the wearable metaverse offers a compelling solution, promising enhanced multisensory experiences and adaptable learning environments that transcend the constraints of conventional ubiquitous learning. This research proposes a novel framework for ubiquitous blended learning in the wearable metaverse, aiming to address critical challenges, such as multi-source data fusion, effective human–computer collaboration, and efficient rendering on resource-constrained wearable devices, through the integration of embodied interaction and multi-agent collaboration. This framework leverages a real-time multi-modal data analysis architecture, powered by the MobileNetV4 and xLSTM neural networks, to facilitate the dynamic understanding of the learner’s context and environment. Furthermore, we introduced a multi-agent interaction model, utilizing CrewAI and spatio-temporal graph neural networks, to orchestrate collaborative learning experiences and provide personalized guidance. Finally, we incorporated lightweight SLAM algorithms, augmented using visual perception techniques, to enable accurate spatial awareness and seamless navigation within the metaverse environment. This innovative framework aims to create immersive, scalable, and cost-effective learning spaces within the wearable metaverse. Full article

Background: Multicultural education and second-language acquisition engaged neural networks, supporting executive function, memory, and social cognition in adulthood, represent powerful forms of brain-inspired multisensory learning. The neuroeducational framework integrates neuroscience with pedagogical practice to understand how linguistically and culturally rich environments drive neuroplasticity and cognitive adaptation in adult learners. Objective: This systematic review synthesizes findings from 80 studies examining neuroplasticity and cognitive outcomes in adults undergoing multicultural and second-language acquisition, focusing on underlying neural mechanisms and educational effectiveness. Methods: The analysis included randomized controlled trials and longitudinal studies employing diverse neuroimaging techniques (fMRI, MEG, DTI) to assess structural and functional brain network changes. Interventions varied in terms of immersion intensity (ranging from limited classroom contact to complete environmental immersion), multimodal approaches (integrating visual, auditory, and kinesthetic elements), feedback mechanisms (immediate vs. delayed, social vs. automated), and learning contexts (formal instruction, naturalistic acquisition, and technology-enhanced environments). Outcomes encompassed cognitive domains (executive function, working memory, attention) and socio-emotional processes (empathy, cultural adaptation). Results: Strong evidence demonstrates that multicultural and second-language acquisition induce specific neuroplastic adaptations, including enhanced connectivity between language and executive networks, increased cortical thickness in frontal–temporal regions, and white matter reorganization supporting processing efficiency. These neural changes are correlated with significant improvements in working memory, attentional control, and cognitive flexibility. Immersion intensity, multimodal design features, learning context, and individual differences, including age and sociocultural background, moderate the effectiveness of interventions across adult populations. Conclusions: Adult multicultural and second-language acquisition represents a biologically aligned educational approach that leverages natural neuroplastic mechanisms to enhance cognitive resilience. Findings support the design of interventions that engage integrated neural networks through rich, culturally relevant environments, with significant implications for cognitive health across the adult lifespan and for evidence-based educational practice. Full article

The present study explores the affordances of virtual reality (VR) technologies to enhance digital and media literacy skills within an interdisciplinary and inclusive K-12 English as a Foreign Language (EFL) learning context. Addressing gaps in research on the design and impact of VR experiences in secondary education, the study investigates VR affordances not only as a learning tool, but also as a medium for knowledge co-creation through learning by doing, with students acting as the agents within digital social contexts. The study was conducted for two years, with 59 participants aged 13–14 years old, following a structured five-phase intervention model with the intent to comply with DigComp 2.2 guidelines for digital citizenship and the Universal Design for Learning (UDL) for inclusive educational practices. The phases involved (a) training on the technological level to leverage digital tools; (b) media and information literacy (MIL) instruction in VR; (c) collaborative VR artifact creation; (d) peer evaluation; and (e) dissemination with peers from other sociocultural contexts for an iterative process of continuous content improvement and social discourse. Mixed methods data collection included pre/post-course surveys, pre/post-tests, observation journals, and student-generated VR artifact evaluations. The findings indicate consistent learning gains across both years, with an average pre–post gain of 18 points (Cohen’s d = −2.25; t = −17.3, p < 0.001). The VR-supported intervention fostered complex skillset building within a VR-supported dynamic learning environment that caters to diverse needs. Students’ reflections informed a framework for designing inclusive media literacy in VR, structured around three main pillars: Narrative Structure, Strategic Design, and Representation Awareness. These themes encapsulate the practical, cognitive, and ethical dimensions of VR design. Sub-themes with examples contribute to understanding the key design elements of VR in promoting participatory engagement, digital and media literacy, critical discourse, and inclusive education. The sub-themes per pillar are signaling and multisensory cues, storyline, and artful thinking; schema formation, multimedia encoding, and optimal cognitive load; and bias-free, respect for emotional impact, and language and symbols. Complementary quantitative findings confirmed the themes of the proposed framework, revealing a positive correlation between the perceived ease of use (PEoU) with digital skills development and a negative correlation between perceived usefulness (PU) and cognitive load. The study concludes with recommendations for pedagogy, curriculum design, and future research to empower learners in shaping sustainable digital futures. Full article

Inclusive education aims to ensure equitable participation for all students. Technology plays a crucial role in this endeavor by providing tools that eliminate barriers, personalize learning, and foster active participation, especially for students with functional diversity or specific needs. This research examines whether the adoption of technologies facilitates or poses challenges for achieving effective inclusive education. Through a Systematic Literature Review (SLR), the most commonly used technologies were identified and both their benefits and challenges were evaluated. The PRISMA methodology was applied, and databases such as Scopus were used, undergoing two study refinement processes, resulting in 93 primary studies that contributed to addressing the posed research questions. The findings reveal the use of various technologies in inclusive educational settings, such as screen readers, braille devices, and augmented reality technologies. Their benefits include improved accessibility, enhanced active participation, and the promotion of critical skills like critical thinking and creativity. These tools help create more motivating and equitable learning environments, which aid in reducing dropout rates and strengthening social inclusion. However, the implementation of these technologies faces significant challenges, such as high costs, lack of adequate training for teachers, social inequalities, and ethical barriers. To maximize the effectiveness of these tools, it is crucial to modernize inclusive policies and tailor educational strategies to the specific needs of each student. This study has limitations, including variability in the quality of the studies analyzed, which may affect the generalization of the results. Future research should explore the long-term impacts of technologies on inclusive education and evaluate the necessary teacher training strategies for their effective implementation. Full article

This study investigates the effects of embodied (breathing exercises) and cognitive interventions on adolescents’ flow experience and cognition patterns. Using a mixed-methods design, 303 vocational high school students were assigned to three groups: Embodied Task Group (N = 108), Cognitive Task Group (N = 100), and Mental Health Course Group (N = 95). Experiment 1 employed a 3×2 Multivariate Analysis of Covariance (MANCOVA) design to compare flow experience dimensions, while Experiment 2 used Epistemic Network Analysis (ENA) to analyze diary entries. Results showed that the Embodied Task Group outperformed the Cognitive Task Group in “Unambiguous Feedback” (η_p² = 0.01, a small effect) and had higher “Transformation of Time” (η_p² = 0.01, a small effect) than the Mental Health Course Group. ENA revealed that the Embodied Group developed stronger body-environment interaction patterns, shifting cognition pattern from psychological evaluations to dynamic bodily processes over time. Conversely, the Cognitive Task Group maintained event-focused cognition with weaker mind–body integration. Findings highlight breathing exercises’ potential to enhance flow experience through embodied awareness and multisensory processing, offering practical implications for mental health education by promoting embodied learning tasks to foster flow experience. Full article

Sustainable and technology-enhanced learning (TEL) plays a crucial role in supporting learners with dyslexia by providing accessible, personalized, and inclusive educational experiences. The case study discusses learning challenges of students with dyslexia due to both pedagogical and technological factors. Traditional teaching methods that rely heavily on text-based instruction can make it difficult for them to process and retain information. Many digital tools and learning platforms are not designed with accessibility features like text-to-speech or dyslexia-friendly fonts, making it harder for dyslexic students to engage with content. A lack of individualized instructional approaches, such as multisensory learning or adaptive learning technologies, can hinder their progress. Additionally, inadequate teacher training on dyslexia-friendly strategies can result in ineffective support in the classroom. The aim of this paper is to identify the most appropriate pedagogical and technological aspects and their applicability to the development of tools for dyslexic learners and to elucidate the most effective way of learning according to needs. This paper presents a case study on the learning object design to overcome dyslexia barriers and improve the quality of students’ learning. Full article

Background: Early Hearing Detection and Intervention (EHDI) programmes must partner effectively with families navigating complex circumstances. Adolescent parents (APs) in Teen Parent Units (TPUs) represent a dynamic group demonstrating resilience as they balance childcare, education, and their own developmental journeys. This study explores their understanding of infant hearing, sources of knowledge, and the development of an effective teaching tool. Methods: A qualitative study was conducted with AP learners at a TPU in Aotearoa, New Zealand. Following a period of relationship-building, three focus groups were held. Data were analysed using content analysis and reflexive thematic analysis. Results: AP learners demonstrated a strong awareness of multisensory interactions. Major sources of knowledge included their relational interactions with people they trusted (midwives and family members), rather than social media. Four key themes emerged in the teaching tool’s development: (1) the effectiveness of multimodal teaching tools, (2) the benefits of peer-supported group learning, (3) the impact of high strain, and (4) the importance of Te Ao Māori (a Māori worldview). Conclusions: This study highlights the importance of culturally grounded health interventions for families navigating complex life circumstances. Group-based learning fostered peer support, hands-on multimodal teaching was effective, and culturally relevant materials and pedagogies enhanced engagement. EHDI programs may more effectively support infants from families navigating complex circumstances by collaborating with trusted support people, integrating with wraparound care networks, utilising safe and familiar settings, and delivering interventions in an engaging and culturally appropriate manner. Full article

Social media influencers strategically design the auditory and visual features of short videos to enhance consumer engagement. Among these, auditory emotional arousal and visual variation play crucial roles, yet their interactive effects remain underexplored. Drawing on multichannel integration theory, this study applies multimodal machine learning to analyze 12,842 short videos from Douyin, integrating text analysis, sound recognition, and image processing. The results reveal an inverted U-shaped relationship between auditory emotional arousal and consumer engagement, where moderate arousal maximizes interaction while excessively high or low arousal reduces engagement. Visual variation, however, exhibits a positive linear effect, with greater variation driving higher engagement. Notably, audiovisual congruence significantly enhances engagement, as high alignment between arousal and visual variation optimizes consumer information processing. These findings advance short video marketing research by uncovering the multisensory interplay in consumer engagement. They also provide practical guidance for influencers in optimizing voice and visual design strategies to enhance content effectiveness. Full article

This paper examines multisensory museums, envisioned as extended or hybrid realities where the physical and digital coexist to offer cognitively and emotionally engaging experiences to the public, while enhancing the sense of authenticity. Multisensory communication can improve accessibility, as it conveys the content through multiple perceptual channels, and it can solicit more inclusive, participatory, and creative audience engagement through the stimulation of emotions. A methodological approach to digitisation, communication strategies, interaction, creative storytelling, immersive technologies, and accessibility issues are discussed in depth, in relation to emerging museological practices. Machine learning and generative AI are opening new scenarios in management practices and decision-making, in data analyses and in natural language processing, and in the creation of personalised content addressed to the audience. A short overview about how these algorithms evolve and work is presented, considering the challenges, threats, expectations, and ethical implications they pose. Another key topic is the sense of authenticity. How is it changing in today’s users? How do virtual and mixed realities, storytelling, and user experience design in museums influence it? This paper explores these issues, presenting some case studies which have cultural, social, philosophical, and ethical implications, at a time when museums are redesigning their role in a society undergoing profound transformation. Full article

Electroencephalography (EEG)-basedpersonal identification has gained significant attention, but fluctuations in emotional states often affect model accuracy. Previous studies suggest that multisensory stimuli, such as video and olfactory cues, can enhance emotional responses and improve EEG-based identification accuracy. This study proposes a novel deep learning-based model, CNN-BiLSTM-Residual Network (CBR-Net), for EEG-based identification and establishes a multisensory emotional EEG dataset with both video-only and olfactory-enhanced video stimulation. The model includes a convolutional neural network (CNN) for spatial feature extraction, Bi-LSTM for temporal modeling, residual connections, and a fully connected classification module. Experimental results show that olfactory-enhanced video stimulation significantly improves the emotional intensity of EEG signals, leading to better recognition accuracy. The CBR-Net model outperforms video-only stimulation, achieving the highest accuracy for negative emotions (96.59%), followed by neutral (94.25%) and positive emotions (95.42%). Ablation studies reveal that the Bi-LSTM module is crucial for neutral emotions, while CNN is more effective for positive emotions. Compared to traditional machine learning and existing deep learning models, CBR-Net demonstrates superior performance across all emotional states. In conclusion, CBR-Net enhances identity recognition accuracy and validates the advantages of multisensory stimuli in EEG signals. Full article

The aim of this research is to investigate and use a variety of immersive multisensory media techniques in order to create convincing digital models of fossilised tree trunks for use in XR (Extended Reality). This is made possible through the use of geospatial data derived from aerial imaging using UASs, terrestrial material captured using cameras and the incorporation of both the visual and audio elements for better immersion, accessed and explored in 6 Degrees of Freedom (6DoF). Immersiveness is a key factor of output that is especially engaging to the user. Both conventional and alternative methods are explored and compared, emphasising the advantages made possible with the help of Machine Learning Computational Photography. The material is collected using both UAS and terrestrial camera devices, including a multi-sensor 3D-360° camera, using stitched panoramas as sources for photogrammetry processing. Difficulties such as capturing large free-standing objects using terrestrial means are overcome using practical solutions involving mounts and remote streaming solutions. The key research contributions are comparisons between different imaging techniques and photogrammetry processes, resulting in significantly higher fidelity outputs. Conclusions indicate that superior fidelity can be achieved through the help of Machine Learning Computational Photography processes, and higher resolutions and technical specs of equipment do not necessarily translate into superior outputs. Full article

This work presents a comparative study of low cost and low invasiveness sensors (plantar pressure and inertial measurement units) for classifying cross-country skiing techniques. A dataset was created for symmetrical comparative analysis, with data collected from skiers using instrumented insoles that measured plantar pressure, foot angles, and acceleration. A deep learning model based on CNN and LSTM was trained on various sensor combinations, ranging from two specific pressure sensors to a full multisensory array per foot incorporating 4 pressure sensors and an inertial measurement unit with accelerometer, magnetometer, and gyroscope. Results demonstrate an encouraging performance with plantar pressure sensors and classification accuracy closer to inertial sensing. The proposed approach achieves a global average accuracy of 94% to 99% with a minimal sensor setup, highlighting its potential for low-cost and precise technique classification in cross-country skiing and future applications in sports performance analysis. Full article