Search Results (381)

Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well acknowledged, but little work addresses what design or interactions techniques developers can employ or build into experiences to work around these limitations. We conducted a scoping literature review, with the aim of mapping the current landscape of design principles and interaction techniques employed in near-field AR environments. We searched for literature published between 2016 and 2025 across major databases, including the ACM Digital Library and IEEE Xplore. Studies were included if they explicitly employed design or interaction techniques with a commercially available HMD for near-field AR experiences. A total of 780 articles were returned by the search, but just 7 articles met the inclusion criteria. Our review identifies key themes around how existing techniques are employed and the two competing goals of AR experiences, and we highlight the importance of embodiment in interaction efficacy. We present directions for future research based on and justified by our review. The findings offer a comprehensive overview for researchers, designers, and developers aiming to create more intuitive, effective, and context-aware near-field AR experiences. This review also provides a foundation for future research by outlining underexplored areas and recommending research directions for near-field AR interaction design. Full article

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article

The education sector in Tanzania faces significant challenges, especially in public primary schools. Unmanageably large classes and critical teacher–pupil ratios hinder the provision of tailored tutoring, impeding pupils’ educational growth. However, artificial intelligence (AI) could provide a way forward. Advances in generative AI can be leveraged to create interactive and effective intelligent tutoring systems, which have recently been built into embodied systems such as social robots. Motivated by the pivotal influence of teachers’ attitudes on the adoption of educational technologies, this study undertakes a qualitative investigation of Tanzanian primary school mathematics teachers’ perceptions of contextualised intelligent social robots. Thirteen teachers from six schools in both rural and urban settings observed pupils learning with a social robot. They reported their views during qualitative interviews. The results, analysed thematically, reveal a generally positive attitude towards using social robots in schools. While commended for their effective teaching and suitability for one-to-one tutoring, concerns were raised about incorrect and inconsistent feedback, language code-switching, response latency, and the lack of support infrastructure. We suggest actionable steps towards adopting tutoring systems and social robots in schools in Tanzania and similar low-resource countries, paving the way for their adoption to redress teachers’ workloads and improve educational outcomes. Full article

Background: Equine-assisted experiential learning (EAL) is an emerging approach that uses human–horse interactions to develop leadership skills through experiential methods. Purpose: This review synthesizes the literature on the role of EAL in developing leadership competencies and explores its implications for workplace learning. Design/methodology/approach: A narrative review was conducted examining empirical studies and theoretical frameworks on EAL and leadership development. Findings/Conclusions: Recent studies show EAL improves self-awareness, emotional intelligence, nonverbal communication, trust building, adaptability, and problem solving. These competencies are fostered through activities such as ground-based exercises, join-up techniques, and trust-building tasks, which require congruence between intention and action. Participants report behavioral changes such as improved empathy, clarity under pressure, and team cohesion. These align with core management skills for organizational performance. Implications: EAL complements traditional leadership training by developing relational and embodied leadership skills, including trust building, adaptability, and emotional intelligence, which contribute to organizational resilience and sustainable growth. Full article

As first-hand testimonies and accounts of the Holocaust fade, scholars and artists alike have struggled to depict and contextualize the genocide’s monumental violence. But depicting violence and its aftermath poses several problems, including the question of how to recall loss without artificially filling in or effacing the absence so central to its understanding. In essence, remembering the Holocaust is a paradox: the preservation of an absence. Marianne Hirsch’s influential concept of postmemory addresses this paradox and asks questions about memorial capacity in the twenty-first century. This essay considers Hirsch’s postmemory in the context of W.G. Sebald’s 2001 novel Austerlitz, which uses a combination of prose and photography to engage the difficulties inherent in memory work without access to eyewitnesses. Through the interaction of printed text and images, Austerlitz subtly references Lurianic mysticism’s concept of tikkun and Tree of Life (ilanot) diagrams. The result is a depiction of memory that is both process-based and embodies absence. My reading of Austerlitz traces a Jewish heritage within the work of a non-Jewish German author by attending to a tradition of mystical thought embedded in the novel. This situates Sebald’s fiction in a much longer Jewish history that stretches out on either end of the event of the Holocaust. Structurally, Sebald develops a tikkun-like process of (re)creation which relies on gathering material scraps of the past and imaginatively engaging with their absences in the present. Images, just as much as text, are central to this process. Reading Austerlitz in the context of Kabbalah reveals an intellectual and artistic link to a Jewish history that, while predating the Holocaust, nonetheless sheds light on post-Holocaust memories of loss. Full article

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

With the rise in short-term intercultural mobility programs, enhancing students’ adaptive capacity through structured experiential learning has become a key concern. Using constructivist grounded theory, this study draws on extending the situated learning and embodied cognition theories as analytical frameworks to explore international students’ cross-cultural adaptation within the context of study tours. It develops a three-phase framework (pre-departure, on-site immersion, and post-tour reflection) to trace their transition from cultural distance to adaptation. The findings reveal that the process through which international students shift from cross-cultural distance to multidimensional adaptation can be further accelerated by environmental settings, situational behaviors, and short-term emotional responses within study tour contexts. Moreover, culture-led and nature-led environments evoke distinct patterns of participation and emotional responses, facilitating varying degrees and dimensions of adaptation across psychological, social, and cultural domains. The study extends situated and embodied learning perspectives by conceptualizing study tours as dynamic, context-sensitive learning sites. By considering adaptation processes context-dependent, this study deepens the understanding of how learning, emotion, and environment interact to shape intercultural development and offers practical insights for designing responsive, stage-sensitive study tour programs. Full article

Style transfer technology has seen substantial attention in image synthesis, notably in applications like oil painting, digital printing, and Chinese landscape painting. However, it is often difficult to generate migrated images that retain the essence of paper-cutting art and have strong visual appeal when trying to apply the unique style of Chinese paper-cutting art to style transfer. Therefore, this paper proposes a new method for Chinese paper-cutting style transformation based on the Transformer, aiming at realizing the efficient transformation of Chinese paper-cutting art styles. Specifically, the network consists of a frequency-domain mixture block and a multi-level feature contrastive learning module. The frequency-domain mixture block explores spatial and frequency-domain interaction information, integrates multiple attention windows along with frequency-domain features, preserves critical details, and enhances the effectiveness of style conversion. To further embody the symmetrical structures and hollowed hierarchical patterns intrinsic to Chinese paper-cutting, the multi-level feature contrastive learning module is designed based on a contrastive learning strategy. This module maximizes mutual information between multi-level transferred features and content features, improves the consistency of representations across different layers, and thus accentuates the unique symmetrical aesthetics and artistic expression of paper-cutting. Extensive experimental results demonstrate that the proposed method outperforms existing state-of-the-art approaches in both qualitative and quantitative evaluations. Additionally, we created a Chinese paper-cutting dataset that, although modest in size, represents an important initial step towards enriching existing resources. This dataset provides valuable training data and a reference benchmark for future research in this field. 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

This survey provides a comprehensive review of the integration of large language models (LLMs) into autonomous robotic systems, organized around four key pillars: locomotion, navigation, manipulation, and voice-based interaction. We examine how LLMs enhance robotic autonomy by translating high-level natural language commands into low-level control signals, supporting semantic planning and enabling adaptive execution. Systems like SayTap improve gait stability through LLM-generated contact patterns, while TrustNavGPT achieves a 5.7% word error rate (WER) under noisy voice-guided conditions by modeling user uncertainty. Frameworks such as MapGPT, LLM-Planner, and 3D-LOTUS++ integrate multi-modal data—including vision, speech, and proprioception—for robust planning and real-time recovery. We also highlight the use of physics-informed neural networks (PINNs) to model object deformation and support precision in contact-rich manipulation tasks. To bridge the gap between simulation and real-world deployment, we synthesize best practices from benchmark datasets (e.g., RH20T, Open X-Embodiment) and training pipelines designed for one-shot imitation learning and cross-embodiment generalization. Additionally, we analyze deployment trade-offs across cloud, edge, and hybrid architectures, emphasizing latency, scalability, and privacy. The survey concludes with a multi-dimensional taxonomy and cross-domain synthesis, offering design insights and future directions for building intelligent, human-aligned robotic systems powered by LLMs. Full article

In social networks like community Question-Answering (cQA) services, members interact with each other by asking and answering each other’s questions. This way they find counsel and solutions to very specific real-life situations. Thus, it is safe to say that community fellows log into this kind of social network with the goal of satisfying information needs that cannot be readily resolved via traditional web searches. And in order to expedite this process, these platforms also allow registered, and many times unregistered, internauts to browse their archives. As a means of encouraging fruitful interactions, these websites need to be efficient when displaying contextualized/personalized material and when connecting unresolved questions to people willing to help. Here, demographic factors (i.e., gender) together with frontier deep neural networks have proved to be instrumental in adequately overcoming these challenges. In fact, current approaches have demonstrated that it is perfectly plausible to achieve high gender classification rates by inspecting profile images or textual interactions. This work advances this body of knowledge by leveraging lexicalized dependency paths to control the level of abstraction across texts. Our qualitative results suggest that cost-efficient approaches exploit distilled frontier deep architectures (i.e., DistillRoBERTa) and coarse-grained semantic information embodied in the first three levels of the respective dependency tree. Our outcomes also indicate that relative/prepositional clauses conveying geographical locations, relationships, and finance yield a marginal contribution when they show up deep in dependency trees. Full article

Traditional villages are irreplaceable cultural heritages, embodying complex human–environment interactions. This study uses historical geography analysis, kernel density estimation, centroid migration modeling, and Geodetector techniques to analyze the 2000-year spatiotemporal evolution and formation mechanisms of 224 nationally designated traditional villages in China’s Qinling-Daba Mountains. The findings are as follows: (1) These villages significantly cluster on sunny slopes of hills and low mountains with moderate gradients. They are also closely located near waterways, ancient roads, and historic cities. (2) From the embryonic stage during the Qin and Han dynasties, through the diffusion and transformation phases in the Wei, Jin, Song, and Yuan dynasties, to the mature stage in the Ming and Qing dynasties, the spatial center of these villages shifted distinctly southwestward. This migration was accompanied by expansion along waterway transport corridors, an enlarged spatial scope, and a decrease in directional concentration. (3) The driving forces evolved from a strong coupling between natural conditions and infrastructure in the early stage to human-dominated adaptation in the later stage. Agricultural innovations, such as terraced fields, and sociopolitical factors, like migration policies, overcame environmental constraints through the synergistic effects of cultural and economic networks. Full article

Grounded in the theory of metacognitive prediction error minimization, this study is the first to propose and empirically validate the mechanism of implicit metacognitive predictive processing by which bodily interaction influences the Aha! experience. Three experimental groups were designed to manipulate the level of temporal synchrony in bodily interaction: Immediate Mirror Group, Delayed Mirror Group, and No-Interaction Control Group. A three-stage experimental paradigm—Prediction, Execution, and Feedback—was constructed to decompose the traditional holistic insight task into three sequential components: solution time prediction (prediction phase), riddle solving (execution phase), and self-evaluation of Aha! experience (feedback phase). Behavioral results indicated that bodily interaction significantly influenced the intensity of the Aha! experience, likely mediated by metacognitive predictive processing. Significant or marginally significant differences emerged across key measures among the three groups. Furthermore, fNIRS results revealed that low-frequency amplitude during the “solution time prediction” task was associated with the Somato-Cognitive Action Network (SCAN), suggesting its involvement in the early predictive stage. Functional connectivity analysis also identified Channel 16 within the reward network as potentially critical to the Aha! experience, warranting further investigation. Additionally, the high similarity in functional connectivity patterns between the Mirror Game and the three insight tasks implies that shared neural mechanisms of metacognitive predictive processing are engaged during both bodily interaction and insight. Brain network analyses further indicated that the Reward Network (RN), Dorsal Attention Network (DAN), and Ventral Attention Network (VAN) are key neural substrates supporting this mechanism, while the SCAN network was not consistently involved during the insight formation stage. In sum, this study makes three key contributions: (1) it proposes a novel theoretical mechanism—implicit metacognitive predictive processing; (2) it establishes a quantifiable, three-stage paradigm for insight research; and (3) it outlines a dynamic neural pathway from bodily interaction to insight experience. Most importantly, the findings offer an integrative model that bridges embodied cognition, enactive cognition, and metacognitive predictive processing, providing a unified account of the Aha! experience. Full article

Research based on the theory of embodied cognition has revealed that the vertical position of target information in space influences individuals’ construal level, which in turn affects their ethical decision-making. However, previous studies have shown inconsistent effects of construal level on ethical decision-making, which may be moderated by factors such as the manipulation methods of construal level and the salience of trade-offs. This study examines how manipulating the vertical position (high/low) of target information in space—thereby altering perceived spatial distance—impacts ethical decision-making through the lens of embodied cognition, using eye-tracking technology. Experiment 1 isolated the effect of target verticality, while Experiment 2 introduced trade-off salience as an additional factor. Eye-tracking metrics in Experiment 1 revealed that lower target positions significantly increased late-stage cognitive processing difficulty. Experiment 2 demonstrated an interaction between target position and trade-off salience in ethical decision-making. These findings suggest that spatial positioning influences cognitive processing via construal level, with its effects on ethical decision-making moderated by trade-off cues. In summary, this study reveals the significant influence of trade-off salience as a contextual cue in individuals’ ethical decision-making while also providing an embodied cognition perspective to inform decision behavior in human–computer interaction contexts. Full article

Desktop Virtual Worlds (DVWs) offer unique spatial affordances for education, yet understanding of how these environments support meaningful learning experiences remains limited. This study introduces the Socio-Spatial Embodiment Model, a novel framework conceptualizing learning in DVWs as shaped by the interconnection of embodied presence, place-making, and community formation. Through semi-structured interviews conducted with 14 experienced educators from the Virtual Worlds Education Consortium, we investigated how these dimensions intersect and what design strategies facilitate this integration. Thematic analysis revealed that strategic design employs cognitive offloading techniques and biophilic metaphors to enhance embodied presence, balance familiar elements with spatial innovations to create meaningful places, and leverage synchronous engagement with institutional identity markers to facilitate learning communities. Our findings identified design strategies that facilitate stronger perceived student connections to the learning environment and community, when DVW designs address spatial, emotional, social, and cultural factors while reinforcing both cognitive and perceptual processes. This research advances understanding of embodied learning in virtual environments by identifying the dynamic interdependence among presence, place, and community, providing practical strategies for educators in creating more meaningful virtual learning experiences. Full article