Search Results (1,585)

In many developing countries, seismic vulnerability remains high due to the widespread presence of informally constructed buildings without professional design or technical supervision. In Colombia, where nearly 60% of structures are non-engineered, this issue is especially acute. The objective of this study is to design, implement, and quantitatively evaluate the Learning Experience for Earthquake Awareness Program (LEAP), an experiential educational strategy for young students that enhances seismic knowledge, promotes sustainable construction awareness, and contributes to disaster risk reduction as a component of social sustainability. To address this challenge, LEAP introduces students to basic principles of structural mechanics and seismic behavior through playful, hands-on activities combining theoretical instruction, practical experimentation, collaborative design, and the testing of model structures. An experimental design with pre- and post-surveys was implemented with 141 participants, including 80 secondary school students (grades 8th–11th) and 61 university students enrolled in engineering, architecture, and construction programs, using 3D-printed models, earthquake simulators, and interactive games. Statistical analysis using the Wilcoxon signed-rank test ($p<0.05$) revealed significant improvements in conceptual understanding and perception, including gains in distinguishing between the hypocenter and epicenter ($+45.39\%$, $p=5.10\times {10}^{-8}$, $r=0.50$), understanding seismic magnitude ($+39.01\%$, $p=1.67\times {10}^{-12}$, $r=0.71$), and visually identifying structural vulnerabilities ($+25.50\%$, $p=4.50\times {10}^{-2}$, $r=0.41$). Overall, LEAP contributes to disaster risk reduction and social sustainability by strengthening seismic awareness and responsible construction practices. The most significant results were observed among secondary school students, while university participants mainly reinforced applied and visual comprehension. Given its convenience sample, lack of control group, and immediate post-test, findings should be interpreted as exploratory and associative. Full article

Education can be conceptualized as a complex socio-technical system in which teacher engagement functions as a dynamic component supporting system performance and adaptability. The present study examines how science teachers’ perceptions of sustainable education interact with their levels of work engagement, providing empirical insights into system-level relationships relevant to educational sustainability. The study sample consisted of 246 science teachers, and data were collected using the Sustainable Education Scale and the Engaged Teacher Scale. Adopting a systems-informed analytical perspective, the study employs machine learning methods (Random Forest, CART, Extra Trees, and Bagging Regression) to explore non-linear relationships and interaction patterns that may remain obscured in conventional linear analyses. The results indicate that structural factors such as weekly teaching hours and academic qualifications are associated with variations in both sustainable education perceptions and work engagement. Moreover, the findings suggest a reciprocal relationship between sustainability-oriented perceptions and teacher engagement, consistent with feedback dynamics observed in complex educational systems. Rather than proposing a new theoretical framework or algorithm, the study demonstrates the utility of machine learning as a methodological tool for examining system-level interactions and emergent patterns in education, offering empirical insights that may inform sustainability-oriented practices in complex social systems. Full article

Over the past five years, generative AI has carved out a major role in architecture, especially in education and visual idea generation. Most of the time, the literature talks about AI as a tool, an assistant, or sometimes a co-creator, always highlighting efficiency and the end product in architectural design. There is a steady rise in empirical studies, yet the real impact on how young architects learn still lacks a solid theory behind it. In this systematic review, we dig into peer-reviewed work from 2015 to 2025, looking at how generative AI fits into architectural design education. Using PRISMA guidelines, we pull together findings from 40 papers across architecture, design studies, human–computer interaction and educational research. What stands out is a clear tension: on one hand, students crank out more creative work; on the other, their reflective engagement drops, especially when AI steps in as a replacement during early ideation instead of working alongside them. To address this, we introduce the idea of “AI sparring”. Here, generative AI is not just a helper—it becomes a provocateur, pushing students to think critically and develop stronger architectural concepts. Our review offers new ways to interpret AI’s role, moving beyond seeing it just as a productivity booster. Instead, we argue for AI as an active, reflective partner in education, and we lay out practical recommendations for studio-based teaching and future research. This paper is a theoretical review and conceptual proposal, and we urge future studies to test these ideas in practice. Full article

This manuscript examines how distinct epistemic attitudes toward singularity and generality have been articulated in medical writing across different historical contexts, offering a conceptual and meta-historical analysis of two enduring genres in biomedical literature: the individualized case report and the systematically aggregated clinical trial. Hippocratic case narratives are considered as a particularly lucid articulation of a mode of inquiry that privileges detailed observation of individual patients, while medieval Aristotelian natural philosophy exemplifies a contrasting emphasis on regularity, intelligibility, and general explanation. Renaissance medical and philosophical traditions are treated as a mediating moment in which attention to anomaly, wonder, and singularity was explicitly re-legitimized within learned medicine. These historically situated articulations are not presented as stages in a progressive narrative, but as recurrent epistemic orientations that are repeatedly reconfigured under different theoretical, institutional, and technological conditions. The paper argues that the tension between attention to exceptional cases and the pursuit of generalizable knowledge continues to structure modern biomedical writing, where case reports remain essential for identifying rare, novel, or anomalous phenomena, while clinical trials formalize strategies for producing reproducible, population-level evidence. Full article

There is little evidence of the implementation of the Principles for Responsible Investment in Agriculture and Food Systems between universities and businesses, and there is even less research that prioritizes people and implements sustainable development with a territorial focus. In this article, we address a form of collaborative work that integrates academia with business, where the Principles for Responsible Investment in Agriculture and Food Systems (CFS-RIA) are seen as an opportunity to promote and strengthen the management of a business in the communities where it operates, and determine a new way of working from its links with the university. The experience is developed in the provinces of Santiago Rodríguez, Valverde (Mao), and Dajabón in the Dominican Republic, with the aim of contributing, using this new approach, to economic, social, environmental, and governance development in the territory. The conceptual and methodological basis for the university–business link is Working With People, a model that integrates key elements of planning such as social learning, collaborative participation, and project management models. The main catalysts of the experience are the business values and the stakeholders who insert the principles into their programs and projects. Among these is an innovative Family Social Responsibility Program with female entrepreneurs and organic banana production. It is concluded that the implementation of the CFS-RIA Principles has a significant impact on the sustainable development of the region and that the university–business link reinforces the social responsibility of companies, providing an opportunity for the entry of new actors. Full article

Students with learning disabilities (LD) often struggle to develop deep, transferable conceptual understanding in mathematics due to cognitive and processing challenges, underscoring the relevance of instruction grounded in strong teacher pedagogical content knowledge (PCK). This issue is critical given widening post-pandemic achievement gaps and increased expectations for conceptual understanding in inclusive classrooms. Although many studies document effective mathematics interventions for students with LD, relatively few examine how teachers’ PCK functions in these classrooms. In contrast, general education research highlights the importance of PCK for conceptual learning. This manuscript bridges these studies by examining how insights from broader PCK research may inform instruction for students with LD. This manuscript presents a practice-based conceptual synthesis of research on mathematics teachers’ PCK, integrating findings from special education and mathematics intervention literature with classroom vignettes and practitioner examples. The synthesis highlights how core PCK components—content knowledge, understanding of student thinking and misconceptions, and instructional strategies—may support early conceptual understanding in students with LD, emphasizing multiple representations, error analysis, and routines that promote generalization through distributed practice. Implications for practice, professional development, and future research are discussed, offering practice-informed pathways to support inclusive mathematics instruction for students with LD. Full article

Instead of being a mechanism used by management in the name of productivity, it is suggested that social power theory can be combined with the extended marketing mix to empower groups of actors in organisations. These two foundational rubrics usually perpetuate the status quo, but when used with a fresh approach, they may be used to improve engagement. The question is how these two theories can be used to describe performance, connections and power relationships, and how might this change organisations for the better? This conceptual paper combines these two rubrics in a single heuristic that reflects hidden currents in organisations. Understanding how these intersections work can foster greater empowerment for actors and produce efficiencies for management. Learning how to use the points of leverage would be a significant step forward for marketing within and between organisations. Full article

This study proposes a functional framework to enhance the efficiency and effectiveness of e-learning content creation by systematically integrating generative artificial intelligence (AI) technologies. While previous research on e-learning has primarily focused on systems and infrastructure, little attention has been given to content creation. To address this gap, we present a five-step methodology: (1) conducting a systematic literature review of existing e-learning development frameworks; (2) proposing a content-specific framework centered on instructors and technical support roles; (3) outlining a detailed task-based content creation process; (4) identifying and classifying commercial AI tools applicable to each functional unit; and (5) comparing the tools based on their strengths, limitations, and suitability. The proposed framework includes eight key functional stages, ranging from lesson planning to editing, automation, and final review. For each stage, AI tools such as ChatGPT, Synthesia, MidJourney, and Grammarly are evaluated and mapped to the corresponding workflow phase. The findings suggest that integrating AI tools into content creation can significantly reduce production time and cost, improve instructional quality, and lower e-learning sector entry barriers. This study contributes a conceptual model and practical strategies for leveraging AI in scalable, high-quality digital education environments. Full article

Background: The mirror neuron system (MNS) has been proposed as a key neural mechanism linking action perception, motor representation, and social cognition. This framework has increasingly been applied to pain research, encompassing pain empathy, observational learning of pain, and rehabilitative interventions such as mirror therapy. However, the literature is conceptually heterogeneous, methodologically diverse, and spans experimental, social, and clinical domains. Objective: This scoping review aims to map the extent, nature, and characteristics of the available evidence on the relationship between the MNS and pain, clarifying how MNS-related mechanisms are defined, investigated, and applied across different contexts. Methods: A scoping review was conducted using the methodological framework proposed by the Joanna Briggs Institute and reported in accordance with PRISMA-ScR guidelines. We searched PubMed/MEDLINE, Scopus, Web of Science, and PsycINFO. Studies were included if they addressed MNS-related mechanisms in pain processing, pain empathy, pain modulation, or pain rehabilitation. Eligible studies were charted and synthesized descriptively and thematically. Results: Twenty-one studies met the inclusion criteria. The evidence was predominantly derived from clinical and rehabilitative settings, with most studies focusing on mirror therapy or mirror visual feedback interventions. The majority of included populations consisting of adults with chronic pain conditions, particularly phantom limb pain and complex regional pain syndrome. Pain intensity, assessed mainly through self-reported clinical scales, was the most frequently reported outcome. A smaller number of studies investigated action observation or motor imagery paradigms, primarily in chronic musculoskeletal pain, showing short-term hypoalgesic effects. Across studies, substantial heterogeneity was observed in the conceptualization of MNS-related constructs, intervention protocols, outcome measures, and follow-up duration. Conclusions: Despite extensive theoretical discussion of the MNS, empirical applications are largely confined to clinical mirror-based interventions, with limited use of direct neurophysiological or neuroimaging markers. Since crucial conceptual and methodological gaps constrain comparability and translation into clinical practice, there is a need for clearer operational definitions and more integrated experimental and clinical research approaches. Full article

(1) Background: The convergence of Big Data and the Internet of Things (IoT) is transforming digital accounting from retrospective documentation into real-time operational intelligence. This systematic review examines how Industry 4.0 technologies—artificial intelligence (AI), blockchain, edge computing, and digital twins—transform accounting practices through intelligent automation, continuous compliance, and predictive decision support. (2) Methods: The study synthesizes 176 peer-reviewed sources (2015–2025) selected using explicit inclusion criteria emphasizing empirical evidence. Thematic analysis across seven domains—conceptual foundations, system evolution, financial reporting, fraud detection, audit transformation, implementation challenges, and emerging technologies—employs systematic bias-reduction mechanisms to develop evidence-based theoretical propositions. (3) Results: Key findings document fraud detection accuracy improvements from 65–75% (rule-based) to 85–92% (machine learning), audit cycle reductions of 40–60% with coverage expansion from 5–10% sampling to 100% population analysis, and reconciliation effort decreases of 70–80% through triple-entry blockchain systems. Edge computing reduces processing latency by 40–75%, enabling compliance response within hours versus 24–72 h. Four propositions are established with empirical support: IoT-enabled reporting superiority (15–25% error reduction), AI-blockchain fraud detection advantage (60–70% loss reduction), edge computing compliance responsiveness (55–75% improvement), and GDPR-blockchain adoption barriers (67% of European institutions affected). Persistent challenges include cybersecurity threats (300% incident increase, $5.9 million average breach cost), workforce deficits (70–80% insufficient training), and implementation costs ($100,000–$1,000,000). (4) Conclusions: The research contributes a four-layer technology architecture and challenge-mitigation framework bridging technical capabilities with regulatory requirements. Future research must address quantum computing applications (5–10 years), decentralized finance accounting standards (2–5 years), digital twins with 30–40% forecast improvement potential (3–7 years), and ESG analytics frameworks (1–3 years). The findings demonstrate accounting’s fundamental transformation from historical record-keeping to predictive decision support. Full article

This study presents a comprehensive bibliometric and science mapping analysis of research on co-creation and co-production in public administration, based on 819 publications indexed in the Web of Science (WoS). The analysis of scientific production in this field shows sparse early contributions before 2005, followed by steady growth after 2010 and accelerated expansion from 2016 onward, driven primarily by European and United States research communities. In terms of scholarly influence, the results identify a stable core of highly productive and influential authors, institutions, and countries, with strong concentration in Northern and Western Europe and Anglo-Saxon contexts. To address the intellectual structure of the field, science mapping identifies four dominant thematic clusters: (1) co-production and value creation, (2) participation and public engagement, (3) governance and policy, and (4) knowledge development, lessons learned, and evaluative insights. Examining thematic and keyword evolution over time, the findings indicate a shift from early conceptual and normative discussions toward more applied and implementation-oriented research, with increasing attention to barriers, challenges, and enabling conditions in recent years. Overall, the findings show that research on co-creation and co-production has evolved from conceptual fragmentation toward greater thematic consolidation and analytical maturity, while persistent implementation challenges remain. By systematically mapping these developments, the study provides a structured overview that supports future conceptual integration and informs both research agendas and practice-oriented discussions on co-creation and co-production in public administration. Full article

Integrating people with hearing disabilities into schools is one of the biggest problems that Latin American societies face. Mexican Sign Language (MSL) is the main language and culture of the deaf community in Mexico. However, its use in formal education is still limited by structural inequalities, a lack of qualified interpreters, and a lack of technology that can support personalized instruction. This study outlines the conceptualization and development of a mobile application designed as an adaptive assistive technology for learning MSL, utilizing a combination of computer vision techniques, deep learning algorithms, and personalized pedagogical interaction. The suggested system uses convolutional neural networks (CNNs) and pose-estimation models to recognize hand gestures in real time with 95.7% accuracy. It then gives the learner instant feedback by changing the difficulty level. A dynamic learning engine automatically changes the level of difficulty based on how well the learner is doing, which helps them learn signs and phrases over time. The Scrum agile methodology was used during the development process. This meant that educators, linguists, and members of the deaf community all worked together to design the product. Early tests show that sign recognition accuracy and indicators of user engagement and motivation show favorable performance and are at appropriate levels. This proposal aims to enhance inclusive digital ecosystems and foster linguistic equity in Mexican education through scalable, mobile, and culturally relevant technologies, in addition to its technical contributions. Full article

This study explores how small and micro fashion and apparel enterprises (SMFAEs) conceptualize and structure social and environmental responsibility within an industry characterized by fragmented supply chains and limited institutional guidance. A qualitative, exploratory case study design examined four Québec-based enterprises through semi-structured interviews; these were analyzed using a hybrid thematic approach interpreted through stakeholder and legitimacy theories. The findings reveal three interdependent dimensions of responsible entrepreneurship: foundational commitments rooted in personal values; organizing mechanisms combining formal tools and informal learning to support continuous improvement; and contextual constraints related to sourcing and systemic opacity. The study advances understanding of early-stage responsibilization as a dynamic alignment between conviction, method, and feasibility. It contributes an integrative model that reframes sustainability from a compliance-oriented goal to an adaptive practice grounded in dialogue and learning. This perspective shows that meaningful sustainability emerges not from universal standards alone but from strengthening everyday human-scale processes of collaboration and adaptation. Full article

Engineering laboratory courses are essential for developing conceptual understanding and practical skills; however, the time students spend assembling prototypes and troubleshooting wiring issues often reduces opportunities for analysis, programming, and reflective learning. To address this limitation, this study designed and evaluated an integrated STM32-based educational laboratory that consolidates the main peripherals required in a microcontroller course into a single Printed Circuit Board (PCB) platform. A quasi-experimental intervention was implemented with 40 engineering students divided into a control group using traditional STM32 Blue Pill and breadboard connections and an experimental group using the integrated platform. Throughout ten laboratory sessions, data were collected through pre- and post-tests, laboratory logs, and the Motivated Strategies for Learning Questionnaire Short Form (MSLQ-SF). Results showed that the experimental group achieved a Hake normalized learning gain of 40.09% compared with 16.22% in the control group, also showing that it completed the sessions an average of 27 min faster and facilitated a substantial reduction in hardware- and connection-related errors. Significant improvements were also observed in metacognitive and improved motivational and self-regulated learning scores. Overall, the findings indicate that reducing operational barriers in laboratory work enhances both cognitive and motivational learning processes, supporting the adoption of integrated educational hardware to optimize learning outcomes in engineering laboratory courses. Full article

This study explores the integration of technology and artificial intelligence (AI) as catalysts for professional teacher development within the context of Mexico’s educational challenges. Adopting a qualitative and exploratory approach, a four-phase workshop was conducted with 40 high school and university-level teachers from the National Polytechnic Institute (IPN). The methodology included scientific modeling activities using traditional methods, software (Tracker, ver. 6.2.0), and AI tools (ChatGPT-3.5), while analyzing participants’ perceptions and experiences. The findings reveal a clear disconnect between teachers’ theoretical competencies and their practical skills, with persistent gaps in scientific literacy at both educational levels. However, this study documents that the workshop functioned as a genuine professional learning community, where inter-academic collaboration and peer-learning proved to be an effective strategy for addressing these deficiencies. Technology, specifically the Tracker software, served as a catalyst for conceptual understanding. Despite AI’s potential for research, its limitations in the precision of responses reinforced this study’s central conclusion: technology does not replace the teacher’s work but transforms the teacher’s role into a critical mediator, responsible for guiding students to develop analytical and critical thinking in a complex digital environment. Full article