Search Results (977)

The Norwegian construction sector has long struggled with conflict, particularly in large-scale and complex projects, where adversarial practices, rigid procurement systems, and insufficient early collaboration are common. This study explores how partnering contracts, which are collaborative delivery models designed to align stakeholder interests, affect conflict dynamics in real-world settings. Employing a mixed-methods approach, it combines semi-structured interviews with 21 experienced Norwegian construction professionals and a structured survey of 33 industry experts. The findings reveal that partnering can foster trust, improve communication, and reduce adversarial behavior through mechanisms such as early contractor involvement, joint goal setting, and open dialogue. However, participants also identified critical risks: superficial collaboration rituals, ambiguous roles, and unresolved structural inequalities that can exacerbate tensions. Importantly, the study emphasizes that partnering success depends less on the contract itself and more on cultural alignment, stakeholder competence, and long-term relational commitment. These insights contribute to a more nuanced understanding of how collaborative contracting influences conflict mitigation in the Norwegian construction sector. Full article

High-rise construction presents heightened safety risks due to vertical complexity, spatial constraints, and workforce variability. Conventional safety management often proves insufficient, especially in rapidly urbanizing or resource-limited settings. This study proposes a hybrid methodological framework to systematically identify and prioritize the critical factors influencing occupational safety in Vietnamese high-rise construction projects. Based on 181 valid survey responses from construction professionals, 23 observed variables were developed through extensive literature review and expert consultation. Exploratory Factor Analysis (EFA) was employed to empirically group 23 validated indicators into five key latent dimensions: (1) Safety Training and Inspection, (2) Employer’s Knowledge and Responsibility, (3) Worker’s Competence and Compliance, (4) Working Conditions and Environment, and (5) Safety Equipment and Signage. These dimensions were then structured into an Analytic Hierarchy Process (AHP) model, with pairwise comparisons conducted by industry experts to calculate consistency ratios and derive factor weights across three high-rise project case studies. The findings provide actionable insights for construction managers, safety professionals, and policymakers in developing and underdeveloped countries, supporting data-driven decision-making for safer and more sustainable urban development. Full article

Background: As population aging accelerates, the demand for professionals in older adult care continues to rise. Traditional teaching methods often fail to improve students’ willingness to serve older adults or foster teamwork. This study evaluated the effects of integrating a flipped classroom with project-based learning (PBL) and a hands-on clinical practicum into a health internship course. Methods: A mixed-methods design was adopted. Participants included 88 interdisciplinary university students enrolled in an 18-week, two-credit geriatric health internship course offered at a university in central Taiwan from August 2023 to July 2024. The course combined flipped classroom and PBL approaches, as well as clinical practicum activities. Data on willingness to serve older adults, teamwork skills, and learning outcomes were collected using structured questionnaires and analyzed with paired t-tests. Results: Significant improvements were found in willingness (from 68.93 to 73.15), teamwork (67.33 to 71.45), and learning outcomes (89.84 to 102.14) (p = 0.001). Qualitative findings further revealed increased empathy, improved teamwork, and enhanced ability to apply knowledge in real-world contexts. Conclusions: A teaching approach that integrates a flipped classroom, PBL, and a clinical practicum can effectively enhance students’ competencies in older adult care. Future research should explore long-term and cross-cultural impacts. Full article

This study investigates how Greek professionals formulate upward requests and simultaneously manage rapport and workplace identity within hierarchical exchanges. The data comprise 400 written requests elicited through a discourse–completion task from 100 participants, supplemented by follow-up interviews. Integrating pragmatic perspectives on request mitigation with Spencer-Oatey’s Rapport-Management model and a social constructionist perspective on identity, the analysis reveals a distinctive “direct-yet-mitigated” style: syntactically direct head acts (typically want- or need-statements) various mitigating devices. This mitigation enables speakers to preserve superiors’ face, assert entitlement, and invoke shared corporate goals in a single move. Crucially, rapport work is intertwined with identity construction. Strategic oscillation between deference and entitlement projects four recurrent professional personae: the deferential subordinate, the competent and deserving employee, the cooperative team-player, and the rights-aware negotiator. Speakers shift among these personae to calibrate relational distance, demonstrating that rapport management functions not merely as a politeness calculus but as a resource for dynamic identity performance. This study thus bridges micro-pragmatic choices and macro social meanings, showing how linguistic mitigation safeguards interpersonal harmony while scripting desirable workplace selves. Full article

The construction sector significantly contributes to global environmental degradation through intensive resource extraction, high energy consumption, and substantial waste generation. Addressing this unsustainable trajectory requires integrated approaches that simultaneously improve operational efficiency and material circularity. Lean Construction (LC) and Circular Economy (CE) offer complementary frameworks for enhancing process performance and reducing environmental impacts. However, their combined implementation remains underdeveloped and fragmented. This study conducts a systematic literature review (SLR) of 18 peer-reviewed articles published between 2010 and 2025, selected using PRISMA 2020 guidelines and sourced from Scopus and Web of Science databases. A mixed-method approach combines bibliometric mapping and qualitative content analysis to investigate how LC and CE are jointly operationalized in construction contexts. The findings reveal that LC improves cost, time, and workflow reliability, while CE enables reuse, modularity, and lifecycle extension. Integration is further supported by digital tools—such as Building Information Modelling (BIM), Design for Manufacture and Assembly (DfMA), and digital twins—which enhance traceability and flow optimization. Nonetheless, persistent barriers—including supply chain fragmentation, lack of standards, and regulatory gaps—continue to constrain widespread adoption. This review identifies six strategic enablers for LC-CE integration: crossdisciplinary competencies, collaborative governance, interoperable digital systems, standardized indicators, incentive-based regulation, and pilot demonstrator projects. By consolidating fragmented evidence, the study provides a structured research agenda and practical insights to guide the transition toward more circular, efficient, and sustainable construction practices. Full article

Based on flipped learning, digital competence, and inclusive instructional design, this study employs a mixed-method approach (quantitative and qualitative) to evaluate the pilot and involves academics from six European universities. Teacher participants co-designed and implemented flexible learning scenarios using the FLeD tool, which integrates pedagogical patterns, scaffolding strategies, and playful features. Using a mixed-methods research approach, this study collected and analyzed data from 34 teachers and indirectly over 800 students. Results revealed enhanced student engagement, self-regulated learning, and pedagogical innovation. While educators reported increased awareness of inclusive teaching and benefited from collaborative design, challenges related to tool usability, time constraints, and the implementation of inclusivity also emerged. The findings support the effectiveness of structured digital tools in promoting pedagogical transformation in online, face-to-face, and hybrid learning. This study contributes to the discussion on the digitalization of higher education by illustrating how research-informed design can enable educators to develop engaging and flexible inclusive learning environments in line with the evolving needs of learners and the opportunities presented by technology. Full article

Building information modeling (BIM) has emerged as a fundamental component of Industry 4.0 recently. BIM construction engineers (BCEs) play a pivotal role in implementing BIM, and their personal competency is crucial to the successful application and promotion of BIM technology. Existing research on evaluating BIM capabilities has mainly focused on the enterprise or project level, neglecting individual-level analysis. Therefore, this study aims to establish an individual-level competency evaluation model for BCEs. Firstly, the competency of BCEs was divided into five levels by referring to relevant standards and domestic and foreign research. Secondly, through the analysis of literature data and website data, the competency evaluation indicator system for BCEs was constructed, which includes four primary indicators and 27 secondary indicators. Thirdly, variable weight theory was used to optimize the weights determined by general methods and calculate the comprehensive weights of each indicator. Then the competency levels of BCEs were determined by the interval grey clustering method. To demonstrate the application of the proposed method, a case study from a Chinese enterprise was conducted. The main results derived from this case study are as follows: domain competencies have the greatest weight among the primary indicators; the C9-BIM model is the secondary indicator with the highest weight (${\mathsf{\omega }}_j$ = 0.0804); and the competency level of the BCE is “Level 3”. These results are consistent with the actual situation of the enterprise. The proposed model in this study provides a comprehensive tool for evaluating BCEs’ competencies from an individual perspective, and offers guideline for BCEs to enhance their competencies in pursuing sustainable professional development. Full article

Campus climate research has long been a focus of higher education scholarship; however, studies show that inequalities and a pervasive sense of not belonging continue to negatively affect students. This paper presents the results of a campus-wide survey conducted at a Minority-Serving Institution (MSI), with a sample of 820 undergraduate, master’s, Ph.D., and non-degree students. The authors explore students’ experiences on campus in relation to their identities as well as students’ perceptions of campus climate. Specifically, the paper examines students’ intergroup relations and how these influence their sense of belonging. The survey instrument developed in the frame of this project also included questions designed to assess opportunities students have to develop key values, attitudes, skills, knowledge, and critical understanding related to intercultural and democratic competences necessary for life and work in multicultural societies. This study identifies the areas students perceive as important for development, highlighting which values, attitudes, skills, knowledge, and critical understanding they have had the opportunity to cultivate during their time at the university and those they would like to develop further. The authors hope these findings will inform efforts to strengthen institutional support for more inclusive practices on culturally diverse university campuses and provide evidence-based guidance for designing effective pedagogical interventions. Full article

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is reshaping curricula from K–12 to postgraduate levels. This paper analyzes instructional models including project-based learning, laboratory work, capstone design courses, and robotics competitions, highlighting their effectiveness in developing both technical and creative competencies. Widely adopted platforms such as the Robot Operating System (ROS) are briefly discussed in the context of their educational value and real-world alignment. Through case studies, institutional insights, and synthesis of academic and industry practices, this review underscores the vital role of robotics education in fostering innovation, systems thinking, and workforce readiness. The paper concludes by identifying the key challenges and future directions to guide researchers, educators, industry stakeholders, and policymakers in advancing robotics as both technological and educational frontiers. Full article

The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, these methodologies do not include the learning curve, a critical factor in operator-dependent technologies. This study presents an evaluation model incorporating the learning curve, developed from the domains of the AdHopHTA project. Using System Dynamics (SD), the model was validated and calibrated as a case study to evaluate the use of Point-of-Care Ultrasound (POCUS) in identifying dengue. This approach allowed for the analysis of the impact of the learning curve and patient demand on the revenues and costs of the healthcare system and the cost–benefit indicator associated with dengue detection. The model assesses physician competency and how different training strategies and frequencies of use affect POCUS adoption. The findings underscore the importance of integrating the learning curve into decision-making. This study highlights the need for further investigation into the barriers that limit the effective use of POCUS, particularly in resource-limited settings. It proposes a framework to improve the integration of this technology into clinical practice for early dengue detection. Full article

The TOWCHED project explores how arts and heritage-based educational methodologies can support sustainable development by enhancing key transversal competencies in learners, particularly children and youth. In response to the global challenges outlined in the sustainable development goals (SDGs), this project promotes inclusive and participatory approaches to education that foster social cohesion, intercultural understanding, and civic engagement. Partnering with museums, TOWCHED develops cross-curricular pedagogical interventions, such as experiential, blended, and collection-mediated learning, that link cultural heritage with contemporary social and environmental concerns. These approaches aim to strengthen creativity, critical thinking, collaboration, and self-awareness. TOWCHED demonstrates that heritage collection-based education can play a vital role in transforming schools and other learning environments into hubs for sustainable, lifelong learning. By embedding cultural expression and heritage into educational practices, the project offers a compelling model for empowering individuals to navigate and shape a more equitable and interconnected world. This paper has two aims. First, we introduce TOWCHED, an interdisciplinary project recently funded by the Horizon Europe program of the European Union to preserve and promote education for sustainability in the heritage context. Second, we introduce a set of tools related to the project. Full article

Code duplication, commonly referred to as code cloning, is not inherent in software systems but arises due to various factors, such as time constraints in meeting project deadlines. These duplications, or “code clones”, complicate the program structure and increase maintenance costs. Code clones are categorized into four types: Type-1, Type-2, Type-3, and Type-4. This study aims to address the adverse effects of code clones by introducing LeONet, a hybrid Deep Learning approach that enhances the detection of code clones in software systems. The hybrid approach, LeONet, combines LeNet-5 with Oreo’s Siamese architecture. We extracted clone method pairs from the BigCloneBench Java repository. Feature extraction was performed using Abstract Syntax Trees, which are scalable and accurately represent the syntactic structure of the source code. The performance of LeONet was compared against other classifiers including ANN, LeNet-5, Oreo’s Siamese, LightGBM, XGBoost, and Decision Tree. LeONet demonstrated superior performance among the classifiers tested, achieving the highest F1 score of 98.12%. It also compared favorably against state-of-the-art approaches, indicating its effectiveness in code clone detection. The results validate the effectiveness of LeONet in detecting code clones, outperforming existing classifiers and competing closely with advanced methods. This study underscores the potential of hybrid deep learning models and feature extraction techniques in improving the accuracy of code clone detection, providing a promising direction for future research in this area. Full article

This study aims to identify and quantify the critical factors influencing construction labor productivity. A systematic review and meta-analysis of 27 empirical studies published between 2000 and 2024 were conducted in accordance with PRISMA guidelines. This study synthesizes findings from a variety of global studies and calculates the relative importance index of various factors affecting construction labor productivity. The findings indicate that 66 CFs, categorized into 12 groups, influence construction labor productivity. The results findings underscore the pivotal role of labor-related factors, particularly “worker experience and skills”, and site management factors, such as “competent supervisors” and “effective communication”. Additionally, environmental factors, such as “weather conditions”, have been demonstrated to play a significant role. The meta-analysis identified substantial regional variations and an increasing importance of factors like worker motivation and technological advancements. Moreover, in light of the evident disparities among regional influential factors, including but not limited to climate, economics, and culture, the findings of this study underscore the imperative for customized, localized management methodologies to enhance construction labor productivity, which will provide practical suggestions for project managers in the region and globally. Full article

Background/Objectives: In Australia, attrition rates in undergraduate nursing degrees have been increasing nationally. The aim of this study was to explore if and how clinical laboratory-based peer-assisted learning (PAL) improved the first-year nursing student learning experience and retention at a regional university. A further aim was to explore any perceived benefits for third-year student participants. Methods: This is a descriptive study design. The study recruited eight third-year nursing students (named ‘LabPALs’) offering support to 42 first-year nursing students during their self-directed laboratory practice sessions. The first-year students included a high percentage of mature aged and ‘first in family’ students. Over an eight-week period, LabPALs provided peer support for up to four students per one-hour practice session. Unit grade outcomes were compared with students not exposed to the PAL sessions. Both the LabPAL mentors and first-year participants were asked to evaluate their experience. Results: It was found that PAL project participation was associated with higher completion rates when compared with non-participation. When combined with exposure to their experienced peers’ perspectives and support, participation was associated with academic success. Thematic analysis found that first-year nursing students reported developing both ‘confidence’ and ‘competence’ in their laboratory learning spaces. The third-year LabPAL students reported skills gained in facilitating peer learning and perceived their experience as very rewarding. Conclusions: This research suggests that PAL enhances clinical laboratory learning among undergraduate nursing students. Full article

The rapid spread of artificial intelligence (AI) in education means that students need to master both AI literacy and personal agency. This study situates a sample of 425 Slovenian secondary technical students within a three-tier framework that maps psychological empowerment onto AI literacy outcomes within a cultural–historical activity system. The agency competence assessments yielded four profiles of student agency, ranging from fully empowered to largely disempowered. The cluster membership explained significant additional variance in AI literacy scores, supporting the additive empowerment model in an AI-rich vocational education and training context. The predictive modeling revealed that while self-efficacy, mastery-oriented motivations, and metacognitive self-regulation contributed uniquely—though small—to improving AI literacy, an unexpectedly negative relationship was identified for internal locus of control and for behavioral self-regulation focused narrowly on routines, with no significant impact observed for grit-like perseverance. These findings underscore the importance of fostering reflective, mastery-based, and self-evaluative learning dispositions over inflexible or solely routine-driven strategies in the development of AI literacy. Addressing these nuanced determinants may also be vital in narrowing AI literacy gaps observed between diverse disciplinary cohorts, as supported by recent multi-dimensional literacy frameworks and disciplinary pathway analyses. Embedding autonomy-supportive, mastery-oriented, student-centered projects and explicit metacognitive training into AI curricula could shift control inward and benefit students with low skills, helping to forge an agency-driven pathway to higher levels of AI literacy among high school students. The most striking and unexpected finding of this study is that students with a strong sense of competence—manifested as high self-efficacy—can achieve foundational AI literacy levels equivalent to those possessing broader, more holistic agentic profiles, suggesting that competence alone may be sufficient for acquiring essential AI knowledge. This challenges prevailing models that emphasize a multidimensional approach to agency and has significant implications for designing targeted interventions and curricula to rapidly build AI literacy in diverse learner populations. Full article