Search Results (100)

The transition toward Industry 5.0 in sustainable construction demands a radical reconceptualisation of workforce development, moving beyond purely technical training to embrace human-centricity, digitalisation, green competencies, and socio-cognitive resilience. Traditional vocational and higher education systems have largely failed to bridge the gap between emerging construction industry demands and the competencies possessed by current and future professionals. This systematic review investigates how Learning Factories’ 5.0 immersive, experiential, and technology-rich educational environments can address these gaps in sustainable construction contexts. Drawing on a synthesis of 71 peer-reviewed publications spanning 2015–2026 and supplemented by targeted construction-domain literature, this study pursues three objectives: (1) identifying core competencies for Industry 5.0 readiness in sustainable construction, (2) examining how Learning Factories 5.0 support the development of these competencies, and (3) proposing a competency-driven framework for integrating Learning Factories 5.0 into sustainable construction education and training. Seven transdisciplinary competency clusters are identified—Attitude toward Digitalisation, Technical–Green Proficiency, Information and Data Literacy, Digital Security, Collaborative Systems Thinking, Adaptive Problem-Solving, and Reflective Sustainability Practice—and a theoretically derived, eight-phase Construction Learning Factory 5.0 (CLF5.0) Framework is proposed as a conceptual architecture for future empirical development and institutional adaptation. The framework is presented as a generative starting point rather than a prescriptive model, and its effectiveness in diverse construction education contexts requires empirical validation through future implementation studies. Findings reveal that while Learning Factories offer transformative potential, critical barriers remain in terms of economic feasibility, faculty development, industry–academia alignment, and empirical validation. This paper contributes a construction-specific competency architecture and implementation pathway to support the industry’s transition toward a sustainable, human-centric, and Industry 5.0-aligned future. Full article

This paper presents a Digital Twin (DT)-based framework for the control, monitoring, and intelligent optimization of an Assembly/Disassembly/Repair Mechatronic Production Line (A/D/R MPL), developed as a laboratory platform aligned with Industry/Education 4.0/5.0 paradigms. The A/D/R MPL is assisted by two complementary cyber–physical robotic systems: an Assembly/Disassembly/Replacement Cyber–Physical Robotic System (A/D/R CPRS), and a Mobile Cyber–Physical Robotic System (MCPRS), enabling both fixed and mobile intelligent operations. The CPRS is equipped with an industrial robotic manipulator (IRM) responsible for A/D/R tasks, while the A/D Mechatronic Line (A/D ML) consists of seven interconnected workstations (WS1–WS7) dedicated to storage, transport, quality control, and final product handling. MCPRS includes a wheeled mobile robot (WMR), carrying a robotic manipulator (RM) and Mobile Visual Servoing System (MVSS). Each workstation is connected to a local slave programmable logic controller (PLC), which communicates via PROFIBUS with a master PLC located at the CPRS level. Additional communication infrastructures include LAN PROFINET and LAN Ethernet for local integration, and WAN Ethernet connectivity enabled through open platform Communication-Unified Architecture (OPC-UA), ensuring interoperability, scalability, and remote accessibility. Also, MODBUS TCP as serial industrial communication is used between the master PLC and the MCPRS. Virtual environment supports task planning through Augmented Reality (AR) and real-time monitoring through Virtual Reality (VR). The system behaviour is modelled with synchronized hybrid Petri Nets (SHPNs) which describe the discrete and hybrid dynamics of A/D/R processes. Artificial intelligence (AI) techniques are integrated into the DT framework for optimal task scheduling and adaptive decision-making. As a laboratory-scale implementation, the proposed system provides a comprehensive platform for experimentation, validation, and education. It supports Education 4.0/5.0 objectives by facilitating hands-on learning, human–machine interaction, and the integration of emerging technologies such as AI, Digital Twins, AR/VR, and cyber–physical systems. At the same time, it embodies Industry 4.0/5.0 principles, including interoperability, decentralization, sustainability, robustness, and human-centric design. Full article

Large language models (LLMs) are increasingly integrated into interactive systems across domains such as software development, robotics, and education. As these systems evolve from simple chat interfaces to autonomous, tool-using agents, the design of human–LLM interaction becomes critical. This paper presents a structured review of interaction with LLM-based systems, focusing on how prompting and interaction design mediate system behaviour and autonomy in practice. We analysed 87 studies from 2021–2025, identifying key interaction mechanisms and application-specific challenges. Based on this synthesis, we propose a two-dimensional taxonomy that classifies systems by interaction mechanism (conversational exploration, task-oriented assistance, tool-mediated interaction, and agentic workflows) and level of autonomy (advisory systems, guided execution, delegated execution, and high-autonomy execution). The taxonomy is supported by decision rules, worked examples, and a human-centred lens, emphasizing user control, transparency, error handling, and learning. Our review highlights a shift from single-turn prompting to structured multi-step workflows and the need for evaluation that considers both process and outcomes, particularly in safety-critical settings. This work provides a framework for analysing, comparing, and informing the design of human-centred interaction with LLM-based systems. Full article

The present study seeks to synthesize the scientific evidence from the last decade (2015–2025) regarding the transition from inequality in technological access toward social stratification mediated by automated decision-making systems. Following PRISMA 2020 guidelines and the SPIDER model, a corpus of 74 high-impact records from Scopus, Web of Science, ProQuest, and PsycINFO was examined. The results reveal an exponential growth in scientific production since 2018, marking a shift from infrastructure-based inequality toward a systemic stratification mediated by algorithmic opacity. Three critical sectors of exclusion are categorized: the socio-health nexus, the labor market, and the educational ecosystem. Methodologically, quantitative algorithmic auditing predominates (58%), although mixed sociotechnical approaches have increased by 25% since 2021 to capture experiences of intersectional vulnerability. The study concludes that AI acts as an active agent of social reproduction, necessitating a transition toward “Algorithmic Justice” and “Human-Centric Governance.” Finally, a “Reinstating AI” framework is proposed to democratize technological development and mitigate systemic biases, offering a roadmap for researchers and policymakers in the pursuit of technological sovereignty. Full article

Learning is fundamentally human, even as Artificial Intelligence (AI) challenges human exclusivity. AI, along with Virtual Reality (VR), emerges as a powerful tool that is set to transform higher education, the institutional embodiment of this pursuit at its highest level. These technologies offer the potential not to replace the human factor, but to enhance our ability to create more adaptive, immersive, and truly human-centric learning experiences, aligning powerfully with the emerging vision of Education 5.0, which emphasizes ethical, collaborative learning ecosystems. This research maps how AI and VR tools act as a disruptive force, examining additionally their capabilities and limitations. Moreover, it explores how AI and VR interact to overcome traditional pedagogy’s constraints, fostering environments where technology serves human learning goals. Employing a comprehensive two-month audit of over 60 AI, VR, and AI-VR hybrid tools, the study assesses their functionalities and properties such as technical complexity, cost structures, integration capabilities, and compliance with ethical standards. Findings reveal that AI and VR systems provide significant opportunities for the future of education by providing personalized and captivating environments that encourage experiential learning and improve student motivation across disciplines. Nonetheless, numerous challenges limit widespread adoption, such as advanced infrastructure requirements and strategic planning. By articulating a structured evaluative framework and highlighting emerging trends, this paper provides practical guidance for educational stakeholders seeking to select and implement AI and VR tools in higher education. Full article

Background/Objectives: Echocardiography reports are essential diagnostic tools, but their complexity and specialized English terminology frequently hinder comprehension for non-specialists and patients. This study addresses these accessibility gaps by developing a resource-efficient large language model (LLM) system designed to translate and summarize English echocardiography results into Traditional Chinese. Methods: To overcome significant hardware constraints, we utilized Quantized Low-Rank Adapter (QLoRA) techniques and the Unsloth acceleration framework to fine-tune LLaMA-3.2-1B and LLaMA-3.2-3B-Instruct models on a single mid-tier GPU. The system employs a dual-stage inference architecture: the first stage provides technical medical translation for clinicians, while the second stage generates simplified, patient-centric educational summaries to enhance health literacy. Results: Evaluation across multiple metrics, including BLEU, ROUGE, METEOR, and Perplexity, demonstrated that the LLaMA-3.2-3B-Instruct model with the AdamW 8-bit optimizer achieved the most stable validation performance, excelling in semantic coherence and structural consistency. A preliminary qualitative error analysis conducted in the Discussion section further identified clinical nuances, such as terminology simplification and minor hallucinations, underscoring the critical necessity of a Human-in-the-Loop verification procedure. Conclusions: These findings validate the feasibility of deploying cutting-edge medical AI in resource-limited clinical environments. While the results reflect validation-only performance on a specialized dataset, the platform offers a scalable foundation for enhancing clinical decision support and health literacy through accessible, automated medical text processing. Full article

Industry 5.0 (I5.0) reframes industrial transformation by placing human-centricity, sustainability, and resilience alongside digitalisation, and by linking the twin transition to circular economy ambitions. While the post-2020 literature is expanding, implications for Manufacturing Systems are presented as fragmented principles, technologies, or isolated use cases, which complicates traceability from I5.0 goals to system-level requirements. This manuscript addresses this gap by consolidating the I5.0 discourse via a challenge-based synthesis and translating it into Manufacturing System implications using an evidence-mapping logic. Reported challenges are clustered into four topic groups (planet and society, products and consumption, production, people) and mapped to the four Manufacturing System pillars to expose evidence concentrations and gaps. Building on this bridge, a Manufacturing Systems’ challenges taxonomy is derived in three streams: (i) personalised and circular products, (ii) sustainable, flexible, human-centric Manufacturing Systems, and (iii) an education and skills paradigm for reskilling across industry and research ecosystems. A research agenda matrix highlights priorities in lifecycle information infrastructures, orchestration metrics, human–automation symbiosis, and governance at a system-of-systems scale. In the coded corpus (n = 30), evidence is denser in Manufacturing Systems and operations and competitiveness and people (22 and 23 papers) than in materials and processes and product, tooling, and assembly (7 and 10 papers). Full article

As secondary educational environments face increasing volatility due to systemic resource constraints and pedagogical uncertainty, understanding the behavioral mechanisms of teacher agency has become paramount. While traditional teacher education has emphasized the execution of standardized curricula, the current era demands a fundamental shift toward adaptive expertise and psychological resilience. This study investigates the processes by which 28 secondary pre-service physical education teachers (PSTs) navigate instructional resource deficits through the lens of adaptive behavior (bricolage) and ecological teacher agency. Utilizing a qualitative case study design, I collected data from two universities in Seoul, South Korea, through reflective journals, revised lesson plans, and micro-teaching video analysis reports over a full 15-week semester. The results identified five coordinates of an adaptive instructional design compass: (1) Facing Constraints, (2) Resource Mining, (3) Contextual Engineering, (4) Simulation, and (5) Reflective Participation. These coordinates represent a transformative behavioral process where PSTs convert environmental deficits into professional assets. The findings reveal distinct adaptation styles based on psychological dispositions: the analytically oriented group (Group A) prioritized structural redesign through digital tools, while the narratively oriented group (Group B) utilized human-centric somatic metaphors and virtual rehearsals to bridge the epistemic void. Crucially, this research suggests that teacher adaptation is not a mere technical adjustment but a dynamic behavioral achievement of agency that ensures the long-term instructional quality of physical education. I propose that teacher education programs should incorporate “Safe Deficit” simulations—carefully calibrated instructional constraints—to trigger adaptive behavior and ensure that future educators can thrive in unpredictable pedagogical contexts without the risk of professional burnout. Full article

The COVID-19 pandemic transformed healthcare education, increasing the shift to digital tools and establishing a hybrid curriculum blending online learning with traditional clinical practice. This study aims to understand how this shift impacts the educational growth and skill building of nursing students. A qualitative approach was conducted to understand the experience of Hong Kong nursing students adapting to online learning during the pandemic and beyond. Fifty nursing students were interviewed, and Colaizzi’s phenomenological method revealed key themes in their learning narratives. The analysis revealed four distinct themes characterizing the students’ experiences: (i) Learning on their terms: the mandated shift in healthcare reflecting a lack of agency during the educational transition; (ii) Knowledge without touch: the perceived incompetence of the COVID-19 nursing cohort, highlighting anxieties regarding a lack of hands-on clinical proficiency; (iii) Words left unsaid: The weight of insecurity, indicating a decline in interpersonal skills due to isolation; and (iv) Beyond the perfect algorithm: the unrehearsed art of care, describing the difficulty in translating digital simulations to complex, human-centric patient care. Findings show that while digital progress ensured continuity in education, it also contributed to reduced clinical confidence, weaker communication skills, and shifts in how nursing students approached their learning. Consequently, the post-COVID environment demands that training programs evolve to address these specific deficits. Advancing the existing pandemic-era nursing literature, this study emphasizes the need for diverse, targeted teaching methods to mitigate these gaps. By intentionally bridging theoretical knowledge with hands-on clinical practice, educators can better support student wellbeing and help restore the confidence and competence required of future graduates. Full article

HRC is increasingly adopted in industrial and logistics environments, while workforce preparation often remains constrained by instructional approaches that provide limited embodied understanding of safety and ergonomics. This study examines the architectural design and system integration of a modular, human-centred XR platform intended to support safe and ergonomics-aware collaboration within smart logistics contexts. The proposed system integrates XR training scenarios deployed on consumer-grade hardware and follows a structured pedagogical progression from conceptual familiarisation through experiential task execution to reflective ergonomic evaluation. Multimodal feedback mechanisms based on posture-oriented guidance, attention-aware interaction design, and context-sensitive safety cues are incorporated without reliance on intrusive sensing technologies. A structured evaluation framework is defined to examine usability, task performance, and ergonomics-aligned posture indicators using standardised instruments and system-generated telemetry. The architectural design indicates that the framework supports scalable deployment, consistent interaction fidelity, and privacy-conscious data handling across educational and vocational settings. The proposed framework suggests that human-centred XR architectures can strengthen safety-oriented and ergonomically informed HRC within Industry 4.0 logistics environments. Full article

Generative artificial intelligence tools are reshaping design by enabling novice designers to produce professional-quality user interfaces rapidly. However, for novice designers, exposure to AI-generated outputs that are far beyond their capabilities can inhibit creative growth. In this work, we investigate AI overperformance, when superior AI outputs lower the creative confidence of novices, and explore whether human-centred and explainable AI interfaces can mitigate such effects while sustaining creative agency. We conducted a within-subjects experiment with 75 novice designers using a web-based research platform. Participants completed mobile app design tasks under three conditions: Human-Only (baseline), AI Overmatch (exposure to superior AI outputs), and XAI-Enhanced (exposure to AI outputs with an embedded explainable interface). A repeated-measures ANOVA indicated that creative self-efficacy varied significantly, F = 24.67, p < 0.001, η² = 0.18. While creative self-efficacy was significantly decreased in the AI Overmatch condition, M = −1.18, SD = 0.32, when compared to the Human-Only conditions, M = 0.08, SD = 0.15, this was significantly increased in the XAI-Enhanced condition, M U= 0.42, SD = 0.18. This also led to a rise in creative performance across both ideation and output quality. The results showed that the AI Overmatch condition significantly reduced creative self-efficacy and originality; however, this negative effect was mitigated by the XAI-Enhanced interface, which enhanced confidence and idea quality. Mediation analysis demonstrated that expectancy disconfirmation explains the negative impact of AI overperformance on human creativity. These findings provide constructive design principles for educational AI tools and contribute to HCI theory by demonstrating that pedagogically oriented, transparent AI supports human–AI collaboration without diminishing human agency. Full article

School classrooms represent complex, interconnected systems where indoor environmental quality critically influences student health, cognitive performance, and educational equity. Yet traditional approaches operate in disciplinary silos, creating systemic failures in design, operation, and maintenance. This narrative review adopts a systems engineering framework to demonstrate how integrated interventions—spanning policy, design, technology, and operations—create resilient, sustainable, and healthy classroom climates. Amid escalating climate change impacts (rising temperatures, heatwaves, wildfires) and emerging threats (airborne pathogens, urban pollution), reactive measures like school closures prove pedagogically counterproductive. This review synthesizes evidence on natural, mechanical, and mixed-mode ventilation systems optimized through advanced control strategies, smart technologies, and health-centred policies. Key findings reveal that synergistic integration of Policy, Management, Construction, Operation, and Smart Technologies, in a systems engineering framework, outperforms singular strategies. Critical interventions include hybrid ventilation coupled with layered defences (HEPA filtration, UVGI), AI-driven adaptive controls using IoT sensors and Model Predictive Control to optimize energy while managing pollutant concentrations, and mandatory IAQ standards rooted in stakeholder education. By framing classrooms as interconnected engineering systems, this work provides actionable insights for architects, engineers, policymakers, and administrators, positioning future school design toward resilience, sustainability, and human-centred health outcomes. Full article

The implementation of artificial intelligence (AI) in education is gaining more attention, and as a result, more research is being conducted on the views and conceptualisations of AI by educators. The understanding of teacher candidates is vital for the AI integration in education, which should be human-centred, and still, there is a lack of studies focusing mainly on teacher candidates in the field of the native language. This qualitative phenomenological research aimed to explore metaphors of 46 Turkish language teacher candidates (third- and fourth-year undergraduates in Northern Cyprus) representing their answer to the prompt “AI is like because…”. The data were collected through open-ended questions and analysed using content analysis along with expert validation. Participants produced 46 valid metaphors, which were divided into five thematic categories: (1) AI as Teacher or Learner (21.7%), (2) AI as Method/Strategy (21.7%), (3) AI as Evolving Living Organism (13%), (4) AI as Guide/Helper (21.7%), and (5) AI as Danger/Threat (21.7%). Four groups expressed positive or neutral attitudes towards AI, such as considering it a clever teacher, a useful tool, a growing entity, or a guide. One category revealed negative views, perceiving AI as a destructive force. Overall, 78.3% of participants expressed optimistic views about AI, while 21.7% of them pointed to concerns. Turkish language teacher candidates generally perceive AI as a supportive, human-like assistant in the classroom, but a few of them express concerns about its existence. These results emphasise the importance of incorporating AI literacy and ethics into teacher education. Equipping future language teachers with the skills to use AI in the classroom might be a way of implementing AI in schools that is confident, critical, and human-centred. Full article

Design Thinking (DT) has been widely promoted as a creative, human-centred approach for engaging students with real-world problems. Yet, research consistently shows that DT in mainstream schooling often struggles with ambiguity, superficial engagement with socio-scientific issues, weak integration of disciplinary knowledge, and epistemological tensions with school learning. In this paper, we examine whether DT can become more effective and educationally meaningful when enacted through a socio-constructionist environment using digital media as both design tools and design products. Drawing on a school-based intervention with 70 students using ChoiCo—an open-source digital authoring system for creating socio-scientific games—we analysed critical incidents of student interaction to explore how constructionist digital media mediate reasoning, collaboration, and conceptual development. Our findings show that ChoiCo supports conceptual clarity, iterative refinement, and epistemic grounding by requiring students to encode ideas into rules, thresholds, and consequences. The system’s malleability and embedded feedback align with a special socio-constructionist DT model developed through a multi-organisational European Research and Innovation Project ExtenDT2, enabling rapid prototyping and collaborative meaning-making. We argue that socio-constructionist DT offers a promising way to address long-standing shortcomings of DT in education, shifting the focus from producing polished artefacts to engaging in meaningful, iterative, and epistemically rich design activity. Implications for curriculum design, teacher practice, and the integration of constructionist digital media in DT pedagogy are discussed. Full article

As the Industry 5.0 transition unfolds, engineering education must evolve to integrate Lean manufacturing with advanced digital tools and sustainable, human-centred practices. This study presents the design and implementation of a Lean Learning Factory (LLF) that addresses this challenge by combining traditional Lean methods with technologies such as simulation, robotics, and virtual reality in a modular educational environment. At the University Centre Pitești, six hands-on projects were implemented to guide students through key concepts, including production system layout, digital assistance, sustainability, and human–robot collaboration. Through experiential learning, students engage in iterative design, data analysis, and practical validation using real equipment and software platforms. The results indicate that the LLF effectively supports the development of technical, digital, transversal, and human-centred competencies aligned with EUR-ACE^® standards. Students acquire skills in process optimisation, ergonomics, and sustainable production, while also reflecting on the ethical and social implications of automation. The study concludes that the LLF model provides a scalable and adaptable framework for engineering education. It fosters competence-based learning and prepares students for the demands of Industry 5.0. This paper contributes a replicable educational approach that blends Lean efficiency, digital transformation, and human-centred values into a cohesive learning ecosystem. Full article