Search Results (108)

The rapid expansion of the Internet of Medical Things (IoMT) has enhanced healthcare services, but it has also exposed these systems to a growing range of cyberattacks. Addressing this challenge requires effective intrusion detection solutions. Machine learning-based intrusion detection systems (IDSs) offer a promising approach. In this research, we leverage IoMT-TrafficData, a recently published dataset specific to IoMT environments, to develop intrusion detection models based on federated learning (FL), which preserves data privacy while enabling the use of lightweight learning algorithms suited to resource-constrained devices. In addition, SHAP-based interpretability methods are employed to explain model decisions, thereby improving reliability and transparency. Compared with existing IDS solutions for IoMT, this research proposes an approach that balances performance, privacy, and interpretability while accounting for resource limitations, resulting in three unified, lightweight, and interpretable detection models tailored to different data types in IoMT environments. This work thus provides a solid foundation for future research on secure medical IoT systems. Full article

This exploratory study examined a dual-role artificial intelligence-supported programming environment that integrated human-in-the-loop item generation and on-demand AI debugging within a flipped cognitive apprenticeship framework. Programming tasks were initially generated by GPT-4o and were subsequently reviewed, revised, and approved by the instructor before release. Both instructional conditions completed the same instructor-approved tasks and received the same compiler and automated test-case feedback. Students in the AI Debug-enabled condition could additionally request diagnostic guidance after an unsuccessful submission, whereas students in the comparison condition did not have access to AI-generated debugging assistance. The analytic sample comprised 45 students in the AI Debug-enabled condition and 16 students in the comparison condition. Prior-semester programming achievement, operationalized as the total grade obtained in the preceding programming course, was used as an archival baseline covariate. The observed baseline difference was not statistically significant. Programming-task performance was recorded across 13 instructional weeks. A generalized estimating equation model controlling for prior-semester programming achievement showed no significant overall condition effect, but revealed significant effects of instructional week and the Condition × Week interaction. Prior-semester programming achievement significantly predicted weekly task performance. The comparison condition also obtained higher midterm and final examination scores after adjustment for prior achievement. The findings do not demonstrate a consistent programming-performance advantage associated with access to AI Debug. Instead, adjusted differences varied across instructional weeks and assessment contexts. Because the study used naturally occurring nonequivalent groups and did not retain AI Debug activation records, the results should be interpreted as exploratory associations concerning feature availability rather than causal effects of actual AI use. The primary contribution lies in documenting a human-supervised architecture that integrates instructor-facing AI item generation and student-facing debugging assistance while distinguishing AI-supported task performance from independent programming achievement. Full article

Transseptal puncture constitutes the foundational step required for left atrial access, serving as the critical gateway for pulmonary vein isolation, left-sided electrophysiological ablations, and percutaneous structural heart interventions. Although fluoroscopically guided transseptal puncture demonstrates high technical success rates alongside low reported complication rates, procedural training historically relies on unstructured apprenticeship models where overlooked mechanical nuances generate the majority of periprocedural adverse events. Methodological execution demands precise interatrial septal mapping, preprocedural left atrial thrombus screening, systemic anticoagulation, and rigorous hardware de-airing protocols. Real-time imaging using transesophageal or intracardiac echocardiography enhances fluoroscopic landmarks, facilitating precise localized puncture at the thin fossa ovalis while safeguarding adjacent anatomical structures such as the aortic root, posterior left atrial wall, and pericardial space. Modern auxiliary technologies, including radiofrequency crossing devices, provide systematic escalation strategies for fibrotic or altered septal substrates. Left atrial access must be unequivocally confirmed before dilator or sheath advancement using appropriate imaging, hemodynamic, or other procedural confirmation methods according to the technique employed. Ultimate procedural safety and operator competence depend on maintaining rigorous multi-modality confirmation protocols rather than relying on technical improvisation. Full article

Our current moment is marked by profound institutional, ecological, and social upheaval. The unparalleled amassing of wealth by an infinitesimal percentage of the world’s population; populist movements on the left and right born of broken social contracts; escalating global conflicts and ecological collapse amidst breakneck technological advance—these are all emblematic of the uncharted ruptures that humans, our living kin, and our planetary system are currently weathering. The following viewpoint piece endeavors to shed light on the challenges, complexities, and opportunities of this polycrisis through the lens of academia. By highlighting the inherent contradiction that modern academia has unwittingly created through its narrow “apprenticeship” training structure, this paper first illustrates how one of the most highly skilled workforces in the world is nonetheless particularly ill-positioned to navigate the present moment holistically. The manuscript next argues that to address this gap, leaders of academia must expand their understanding of well-being, productivity, and expertise to include the fruits of their faculty members’ creative wellspring—a term that captures the humanistic, generative capabilities including vulnerability, reflection, courage, and connection that undergird value-based decision making, professional perseverance, and sustained collaboration with others. To move these ideas from theory to practice, the manuscript next emphasizes how the nurturance of a coaching ethos can support faculty in reenchanting their academic careers. The implications of an increasingly holistic, creative notion of expertise for promoting social and planetary flourishing are also considered. Full article

This study explores the potential of integrating Virtual Reality technology into art restoration education and conducts a preliminary usability evaluation for an immersive training prototype. Amidst the digital transformation of cultural heritage preservation, traditional apprenticeship-based education faces challenges such as irreversible damage risks to artifacts, high costs of restoration materials, and a lack of error tolerance for beginners. To address these issues, virtual environments provide a “zero-risk” simulation laboratory, allowing learners to engage in repetitive practice with real-time feedback. This research focuses on a prototype of a “Virtual Conservation and Restoration Education system” (V-CARE system) and conducted usability testing with 20 students at Cheng Shiu University. A mixed-method evaluation approach was employed, combining the System Usability Scale (SUS) for quantitative measurement and the 12 VR Heuristics proposed by Sutcliffe and Gault for qualitative verification. The evaluation suggests preliminary evidence in terms of learnability, interaction naturalness, and immersion. Finally, the study discusses potential layout considerations for prospective virtual environments, aiming to provide a baseline reference for virtual applications in cultural preservation training. Full article

Agriculture is one of the most hazardous occupational sectors, with conventional safety training often suffering from limited realism, low engagement, and reduced opportunities to reproduce hazardous scenarios safely. This article provides a structured analysis of digital and technology-enhanced approaches for safety education and training in agriculture. A literature-based framework was developed by combining five groups of digital tools—immersive technologies, simulators and digital twins, serious games and gamification, e-learning systems, and AI-based educational tools—with five learning contexts: formal education, vocational education and training, apprenticeships and traineeships, lifelong and on-the-job learning, and peer or community-based learning. In addition, a heuristic Application Priority Score (APS) was proposed to assess each technology–context combination according to evidence availability, cost–benefit feasibility, technology–learner fit, and inclusivity/accessibility. The results show that evidence is unevenly distributed, with stronger attention to immersive technologies, simulation-based approaches, and game-based learning in formal education, whereas lifelong, on-the-job, and peer/community learning remain less explored. The scoring framework also indicates that no single digital tool is universally suitable: the most promising solutions depend on the training context, learner experience, implementation costs, and accessibility barriers. The study provides a context-sensitive framework to support future research and the design of more inclusive and effective digital safety training solutions in agriculture. Full article

The European crafts ecosystem faces critical structural threats, declining practitioner numbers, weakening intergenerational transmission, limited digital literacy, and competition from industrial imitation. Existing online craft communities are narrowly material-specific and structurally ill-suited to the cross-disciplinary dialogue required for systemic sector transformation. This paper presents the design, iterative development, and pilot evaluation of the Craeft Community, a multi-stakeholder Virtual Community of Practice (VCoP) developed within the Horizon Europe CRAEFT project. Three research questions guided the study: how a multi-stakeholder VCoP should be structured to overcome disciplinary fragmentation; to what extent a stewarded digital forum can operationalize Situated Learning and Communities of Practice theory; and what factors facilitate or inhibit engagement and post-funding sustainability. Using design-based research, the platform evolved through four iterative phases, culminating in restructuring from a material-based architecture into five transversal thematic pillars, driven by survey evidence from 151 European craft professionals and systematic stakeholder feedback. The pilot phase yielded 86 registered members, 31 posts, and 27 interactions, with Transmission & Training as the most engaged pillar. Qualitative analysis reveals substantive cross-disciplinary discourse alongside a structural Effort-Engagement Gap, a persistent tension between forum participation demands and the gravitational pull of mainstream social media. The study demonstrates that a thematically organized, stewarded VCoP can meaningfully operationalize apprenticeship-based learning in digital settings, advancing craft heritage preservation, economic resilience, and hybrid professional identity formation at the intersection of craft and technology. Full article

Digital platforms increasingly mediate economic coordination, labor allocation, and decision-making. As artificial intelligence becomes embedded within these platform ecosystems, automation no longer targets only manual labor. Instead, algorithmic systems are displacing routine tasks across both low-wage entry-level work and middle-management functions. This paper argues that the emerging phase of platform-mediated automation risks hollowing out labor structures from both directions, from below through the erosion of repetitive, junior roles, and from above through the automation of supervisory coordination functions. Drawing on institutional economics, platform governance literature, and recent research on AI-enhanced learning and workforce development, the paper examines how this dual displacement creates structural vulnerability. Entry-level roles have historically functioned as apprenticeships in which workers acquire tacit knowledge and critical judgment. At the same time, experienced workers are aging out of the workforce. If platforms curtail formative occupational layers, organizations may face a shortage of workers capable of exercising contextual reasoning required to manage complex systems. The paper situates these developments within broader debates about technological unemployment, platform labor, and the political economy of capitalism. It argues that the challenge is not merely job quantity, but institutional continuity, how societies reproduce practical competence when platforms optimize for efficiency rather than formation. This study proposes a framework for evaluating platform ecosystems by their long-term effects on human capital formation and institutional resilience. Full article

Engineering computer graphics education frequently exhibits a gap between procedural CAD software (e.g., CATIA 2022) training and the strategic engineering reasoning required by industrial practice. This paper documents a holistic redesign of two advanced CAD courses. The study is framed within the Scholarship of Teaching and Learning (SoTL) tradition as a practitioner-led reflective case study. The redesign integrates four pedagogical mechanisms within an enterprise-CAD context: authentic problem-based learning, dual-layered asynchronous video scaffolding, software-agnostic heuristics (including pre-modelling cognitive mapping), and cognitive apprenticeship. The analysis triangulates three institutional data sources: quantitative Course Experience Survey indicators, qualitative student response themes, and twelve consecutive years of cohort-level academic performance records (2013–2024). The 2022 intervention iteration coincided with a marked elevation in academic performance. Grades reached approximately two standard deviations above the historical baseline. Concurrently, qualitative themes highlighted perceived industrial relevance and platform-portable confidence. However, performance in the post-intervention iterations (2023 and 2024) partially regressed. While scores remained above the historical mean, they did not sustain the 2022 peak. This pattern indicates partial sustainment, rather than evidence of a stable or definitive sustained pedagogical effect. This case is reported as descriptive rather than inferential. While the observed patterns align strongly with theoretical predictions, they do not establish definitive causal effects. Ultimately, the primary contribution of this study lies in documenting the integrated operationalization of these four mechanisms. Furthermore, it highlights longitudinal pedagogical sustainability as a critical, under-examined dimension that single-iteration evidence systematically obscures. Full article

This article reports an exploratory, small-cohort mixed-methods case study of how an e-learning platform and a virtual reality (VR) workshop simulator can be integrated into a traditional craft apprenticeship without displacing workshop-based learning. Drawing on the Craeft glassblowing Pilot 1 at the European Centre for Research and Training in Glassmaking (CERFAV), it reports a two-phase mixed-methods study contrasting a Traditional Augmented (TA) group, which used a Craeft e-learning platform and a VR glassblowing simulator, with a Traditional (T) control group following the standard Certificate of Professional Competence (CPC) program. Quantitative data from formative assessments and CPC examination results are combined with qualitative feedback, satisfaction surveys, self-assessment questionnaires, and interviews with apprentices and trainers. In Phase 1, where digital tools were deployed in a separate mode alongside existing instruction, the e-learning platform was perceived as pedagogically valuable, but descriptive differences in assessment outcomes were limited and uneven, with greater score dispersion in the TA group. In Phase 2, redesigned hybrid usage scenarios assigned distinct and complementary roles to the e-learning platform, VR, and workshop practice within an iterative learning cycle, and the descriptive results suggest more consistent patterns of higher scores for the TA group in cross-cutting theoretical subjects, with less variance in their scores. Qualitative analyses show that apprentices adopt a pragmatic stance towards digital tools, using the e-learning platform primarily for revision and exam preparation and VR for workshop discovery and tool recognition, while maintaining a strong attachment to material practice. The study suggests that, in small, high-stakes craft VET program, the perceived value of virtual learning environments depends less on their intrinsic properties than on their orchestration within coherent hybrid designs and on trainers’ capacity to align them with authentic tasks and assessment regimes. All findings should be interpreted as exploratory given the small sample size (n < 20), non-random group assignment, and potential self-selection biases. Full article

Zhao’s Guzheng: Traditional Chinese Performance Techniques refers to a comprehensive pedagogical and performance framework within the Shandong–Northeast lineage of the Guzheng (Chinese plucked zither). This system is historically rooted in a 200-year family tradition that underwent a pivotal transition in 1953, when it migrated from Shandong Province to the Shenyang Conservatory of Music in Northeast China. It is formally defined by three primary evolutionary pillars: the physical transition from 16-string silk-string folk instruments to standardized 21-string S-shaped academic models; a rigorous right-hand symbolic codification system that serves as a technical grammar for practitioners; and its status as recognized Intangible Cultural Heritage. The tradition represents a sophisticated synthesis of regional folk esthetics, noted for its robust, vigorous acoustic identity and structured conservatory training. By bridging the gap between oral folk apprenticeships and formal institutional pedagogy, the Zhao lineage maintains its specific stylistic authenticity, known as Yun Wei (musical flavor), ensuring that the technical soul of the school remains reproducible within the modern global musical landscape. Full article

In project-based organizations, novices engaged in project-contextualized learning often struggle to balance sustained project learning with immediate task delivery, creating a tension between developmental sustainability and execution sustainability. While informal support mechanisms such as apprenticeship help alleviate this tension, their effectiveness remains limited. To address this issue, this study adopts a Design Science Research approach to develop a generative AI-driven project scaffolding system prototype. The study contributes design knowledge comprising two core elements. First, based on the task execution process, scaffolding support is organized into three dimensions, namely contextualization, cognitive guidance, and cognitive evolution, which correspond to the progression from task understanding to cognitive construction. Second, a cognition-driven scaffolding mechanism is constructed through prompt-driven and knowledge-augmented generation, enabling human-centered intelligent guidance, augmentation, and automation during task execution. Evaluation in a software implementation firm suggests that the system may improve task output quality and support novices’ application of task-relevant strategies in subsequent tasks. These findings indicate the system’s potential to support the sustainability of both project learning and task execution in project practice. This study provides design insights for embedding GenAI-driven scaffolding in project practice, helping organizations in similar project contexts establish sustainable project support approaches. Full article

Rural schools present distinctive social, material, and pedagogical conditions that shape how pre-service teachers (PSTs) experience mentoring during teaching practice. This systematic review synthesised empirical studies published between 2010 and 2025 to examine how mentor teachers in rural South African schools contextualise their mentoring. Following PRISMA 2020 guidelines, 21 qualitative and mixed-methods studies were analysed using thematic synthesis. Findings show that mentoring remains predominantly apprenticeship-based, emphasising classroom control and syllabus coverage rather than the development of responsive pedagogies. Limited modelling was observed in digital technology integration, formative assessment, culturally responsive teaching (CRT), and restorative classroom management. This review proposes a framework for context-based mentoring grounded in pedagogical content knowledge for mentoring (PCK-M) and recommends structured mentor development, university-school partnerships, and explicit coaching tools to strengthen PST professional learning in rural contexts. Through responsive, context-based mentoring, this approach ensures that pre-service teachers develop the skills, confidence, and contextual understanding needed to thrive in rural classrooms. Full article

This article examines two-state proportional hazard rate models with unobserved heterogeneity specific to each state, a framework that is especially relevant for labor market transitions. To make estimation feasible in large longitudinal datasets, we implement hshaz2s, a Stata routine that uses analytical expressions for the gradient vector and Hessian matrix of the log-likelihood function through the dual second-order moment (d2 ml) method. The empirical application estimates a discrete-time duration model for transitions between employment and unemployment using Spanish labor market microdata for young low-skilled workers over 2000–2019. The results show that apprenticeship contracts are associated with lower exit rates from employment than other temporary contracts, but not with faster transitions from unemployment back into employment. The estimates also reveal substantial state-specific unobserved heterogeneity, with a large latent group characterized by persistent spells in both states. Analytical second-order information also markedly reduces convergence time under richer heterogeneity structures. Overall, the article makes this class of two-state hazard models operational for applied research and provides new evidence on apprenticeship and temporary contracts in Spain. Full article

The Associated Press (AP) Stylebook, endearingly called “the journalist’s bible,” contains thousands of entries outlining style rules and situational guidance. Designed initially for practitioners, the AP stylebook is a seminal resource at many journalism education programs. Its density and complexity as a learning material inherently poses cognitive load risks for novices—and yet—it remains notably under researched. This explanatory sequential mixed methods study explored journalism instructor axiology, pedagogy, and perceptions of teaching effectiveness when introducing AP Style to novice students. Findings revealed that while AP Style remains a pillar of U.S. journalism curriculum, experienced instructors sometimes feel uncertain about the effectiveness of their introductory pedagogy. They described a hodgepodge of methods and design constraints often incongruous with knowledge of human cognitive architecture. We problematize these findings through cognitive load research, recommend Cognitive Apprenticeship Model principles to reduce load-inducing strategies, and suggest directions for future research. Full article