Search Results for
"learning"

The interplay between workforce dynamics and sustainability transitions has been examined across different research strands, yet often in isolation. Despite the need for horizontal policy alignment within transition governance, workforce development remains underexplored in policy mix research. This study examines how policy mixes unfold within the horizontal governance of the workforce in low-carbon energy transitions. It operationalises the core policy mix characteristics by exploring their interaction and feedback across horizontal scales of governance. Drawing on empirical evidence from the case of Schleswig-Holstein, Germany, and based on content analysis and 22 interviews, this paper analyses policies and processes tackling labour shortages in the region's energy transition. The findings reveal that energy workforce needs are poorly integrated across policy domains, with weak political commitment undermining credibility and delaying the development of instruments. Stakeholder-led initiatives compensate for policy shortcomings, yet their disconnection from formal structures limits collective learning and reinforces institutional inertia. © 2025 The Author(s)

The promise of knowledge society is clean, creative, and expressive work. Technological advancements would relieve humans from the tedium and hardship of labor, and access to knowledge and expansion of higher education would diminish the existing social inequalities of industrial society. Based on ethnographic fieldwork in Switzerland's mechanical and electrical engineering industry, this article illustrates how the work experiences of apprentices challenge the image of labor in a knowledge society ostensibly freed from all forms of material, technological, and social constraint. I demonstrate that the persistence of the tedium and potential danger of industrial work, of organizational hierarchies, the decreasing social validation of mechanical and manual labor, and expectations and aspirations to singularity make youth increasingly interested in other kinds of employment and training. The article takes the work and learning relations in the Swiss mechanical and electrical engineering sector as a symptom of emerging tensions around the division of labor and valorization of different forms of skills, and the meaning and motivations of work in late capitalism. I argue that future anthropological studies of work and education in de-industrialized settings might do well to examine the social critique of industrial work in concert with its aesthetic critique. © 2025 American Anthropological Association.

This study introduces a clustering-driven adaptive User Experience (UX) architecture for e-learning systems, aligning machine learning segmentation with the 21st-century 4C educational framework (critical thinking, communication, collaboration, creativity). The objective is to dynamically personalize digital learning interactions through a microservices architecture responsive to users' UX profiles. A quantitative survey was conducted involving 50 active users of Shopee and Tokopedia, whose interaction feedback was mapped using the User Experience Questionnaire (UEQ). Three unsupervised clustering techniques—KMeans, Agglomerative, and DBSCAN—were compared. KMeans outperformed the others with a silhouette score of 0.157, compared to 0.146 for Agglomerative and −0.017 for DBSCAN, identifying three meaningful clusters representing high, medium, and low UX proficiency. A one-way ANOVA test confirmed statistically significant differences (p < 0.01) among the clusters in dimensions such as error clarity, support responsiveness, and user confidence. These UX profiles were then mapped to individualized microservices: Cluster 0 received autonomous content with minimal support, Cluster 1 was offered guided prompts, and Cluster 2 was provided with simplified interfaces and proactive assistance. Each cluster was aligned with specific 4C competencies to ensure pedagogical relevance. The proposed architecture, built with gRPC-based microservices, enabled asynchronous, low-latency personalization based on user cluster membership. The novelty of this research lies in its dual alignment—technological (microservices + machine learning) and educational (4C competency mapping)—to construct a scalable and responsive e-learning environment. The system design, although validated through simulation, demonstrates a practical foundation for future deployment in platforms like Moodle or OpenEdX. By linking behavioral UX clustering to pedagogical intervention strategies, this study offers a model for adaptive, data-informed instructional systems that are both scalable and learner-centered. © 2025, Bright Publisher. All rights reserved.

Innovation competencies represent critical determinants for human capital development within contemporary organizational frameworks. This empirical investigation proposes a comprehensive theoretical model examining self-regulated learning (SRL) as a foundational mechanism driving innovation skill acquisition among management graduates. The study systematically analyzes multidimensional relationships between SRL components—metacognition, cognition, and lifelong learning capabilities—and innovation competencies encompassing curiosity, creativity, computational thinking, and systems thinking. Employing stratified random sampling methodology, 367 management students from Gujarat’s metropolitan institutions were surveyed. Statistical analysis utilized ANOVA and structural equation modeling (SEM) techniques to examine complex multi-dimensional relationships. Empirical findings reveal significant gender-based differentials in innovation competencies and substantial experience-mediated effects on curiosity development. SEM analysis demonstrates robust positive associations between SRL components and innovation outcomes (R² = 0.426), with metacognition exhibiting the strongest predictive capacity (t = 3.395, p = 0.001). The investigation contributes empirical evidence supporting systematic SRL integration into management curricula for enhanced innovation competency development. Educational institutions require systematic implementation of metacognitive training protocols, experiential learning optimization, and process-oriented assessment frameworks to cultivate graduate innovation readiness. © The Author(s) 2025.

Value creation pedagogy (VCP) is a prominent approach in entrepreneurial education, defined as students learning through creating value for others. As higher education institutions (HEIs) strive to prepare students for global challenges like sustainability, inequality and employability, VCP offers a compelling approach linking academic learning to societal contribution. Most VCP research has focused on schools or student experiences rather than university educators. To explore how VCP is enacted in higher education and why, twelve diverse HEI cases in non-entrepreneurship settings were investigated, in which educators integrated VCP into courses or programmes. Cases in engineering, healthcare, pedagogy, business, humanities and natural sciences were identified through purposive sampling and examined via educator interviews. Findings revealed strong educator engagement and demonstrated how VCP supports educators and students to progress from problem ideation to real-world implementation. Varying notions of value emerged, shaping VCP practices and influencing the forms of value students create for others. Challenges also surfaced, highlighting educators’ responses to emotional, institutional and pedagogical demands when adopting student value creation as a learning mechanism. While VCP can be introduced gradually, institutional support remains essential. This systematic cross-case study contributes new insights and practical recommendations for integrating VCP across diverse contexts in HEIs. © 2025 The Authors

Ecological sustainable development model is a green ecological model and a prerequisite for economic sustainable development. Higher education is vocational education and vocational training for relevant personnel, aiming to cultivate more professional talents and skilled workers for the country and society, so as to achieve the goal of social development. This paper aims to use advanced technical means to construct an ecological sustainable development model for higher education. Based on relevant computer technology, this paper proposes a support vector machine (SVM) model and a BP (back propagation) artificial neural network algorithm to analyze and study the ecological sustainable development model. Through experimental analysis, it is known that in the survey of teachers, 199 teachers believe that resources should be effectively utilized in the network environment. This part of teachers accounts for the largest proportion, which is 25.51%, while the proportion of teachers with academic theoretical knowledge is the smallest, which is 7.06%. This shows that teachers should strengthen technical learning. In the process of distance education, practical operation is far more important than theoretical knowledge, and teachers’ skill training also affects the sustainable development of education. Finally, the calculation results show that the experimental method has certain significance for the analysis of ecological sustainable development of higher education. © The Author(s) 2025.

Women’s participation in Green-STEM (Science Technology Engineering and Mathematics) careers remains low. This study examined how to remove gender barriers in Environmental-STEM technical and vocational training programs, aiming to expand opportunities for women in the green economy. SENA, Colombia’s public TVET institution, served as the case study. Gender Transformative and Participatory Action Research approaches, along with the MICMAC method, were used to identify, analyze, and address key barriers. Surveys, interviews and focus groups provided qualitative and quantitative data. The MICMAC analysis revealed the relationships among barriers and their interdependencies, identifying nine core barriers. To address these, women-led smart strategies were implemented through learning cycles, supported by small- and full-scale green pilots focused on sustainable resource utilization, production patterns, and circular economy knowledge transfer. As a result, female apprentices strengthened their sustainability-focused skills and confidence, while SENA enhanced its capacity to foster more inclusive Green-STEM vocational pathways. This study expands existing knowledge by deepening the understanding of gender barriers in vocational STEM careers related to sustainability and environmental management in Latin America, where research remains Limited. It offers actionable recommendations on leveraging education to drive progress toward SDGs 4, 5, 12, and 13. © The Author(s) 2025.