Search Results (1,206)

The transition to a circular economy requires professionals to adopt new strategies and a systemic approach to product development. This shift demands continuous learning and the development of new competencies to understand and apply circular economy principles. In this context, innovative educational approaches that foster engagement and lifelong learning (LLL) are essential. Gamification can support this process by enhancing motivation, creativity, problem-solving, and knowledge retention, while interactive tools help learners critically examine and operationalise circular economy principles. This article discusses the design and application of the “Circularity Deck of Cards,” a learning resource developed as part of a European-funded project Be@t, to facilitate the circular design of products and services. The study follows a mixed-methodological approach encompassing three phases: a systematic mapping of international tools and methodological approaches; the conceptual and visual development of the resource; and its implementation and evaluation through a workshop involving undergraduate, master’s, and doctoral students and researchers in fashion design and textile engineering in Portugal. The data were collected using a questionnaire that combined quantitative and qualitative questions, designed to assess the receptiveness to, challenges of, and opportunities arising from gamification in the teaching of circular design. The findings indicate that participants responded positively to the tool, recognising its value as both a pedagogical resource and a professional instrument for promoting sustainability and circularity in the textile and clothing industry. Ultimately, gamification catalyses training students, designers, and industry professionals to address the challenges of circularity, fostering new perspectives on circular design in professional practice. Full article

As artificial intelligence (AI) technologies advance, traditional craftsmen face new challenges: innovating using digital tools while preserving cultural authenticity and heritage knowledge. The “hybrid artisan,” who strategically integrates AI-based design tools with traditional craft, emerges as a response to this tension. This article addresses research questions regarding how integrating generative AI technologies into design processes influences: (1) artisans’ productivity and product quality; (2) cultural authenticity and heritage preservation; (3) sustainable business models in creative entrepreneurship. The research methodology employs a convergent design with mixed methods, combining: (a) a systematic literature review (SLR) guided by the preferred reporting items for systematic reviews and meta-analyses (PRISMA 2020, n = 33 articles, 2022–2025); and (b) a qualitative survey (n = 13 artisans, Romania; semi-structured questionnaire, 34 items). The literature review identifies three dominant human–AI collaboration models: task-level cooperation, process-level coordination, and system-level co-creation. Diffusion models fine-tuned with low-rank adaptation (LoRA) and generative adversarial networks (GANs) achieve cultural authenticity scores of 73–95% while reducing design time by 30–70%. Empirical data reveal paradoxes: artisans value authentic creativity and sustainability (4 of 13 respondents (31%) rate sustainability as “extremely important”) but adopt AI cautiously (6 of 13 respondents (46%) report that they were not familiar with AI tools). Those using AI report 15–40% productivity gains without a proportional increase in sales, suggesting that market recognition of AI-assisted crafts remains uneven and that sustainability benefits are not yet clearly linked to AI use in practice. The successful “hybrid artisan” model relies on collaborative rather than autonomous AI positioning, explicit cultural safeguards in system design, and transparent communication with consumers about AI involvement. This research provides a conceptual heuristic, points to new research directions, and outlines policy implications for understanding when and how AI-assisted craft practices may support cultural integrity while also accepting that such benefits are context-dependent and not universally validated. Full article

STEM project-based learning (PBL) reports have long struggled with nonuniformity and subjectivity in assessing higher-order thinking skills. This study proposes a human-in-the-loop (HITL) enhanced multi-agent system to address these challenges. Drawing upon established assessment frameworks, the system operationalizes the evaluation of critical and creative thinking into a multi-stage automated pipeline comprising scoring, review, and aggregation agents. Using Deep Research-generated reports as scoring references, a total of 101 STEM PBL reports were evaluated to validate the system’s performance. Results demonstrate that the multi-agent system achieves high scoring stability and consistency. Furthermore, the HITL mechanism significantly improves the alignment between automated scores and expert teacher judgments. In addition, hierarchical clustering based on the system’s outputs successfully identified three distinct performance groups with different levels of creative thinking and critical thinking. These findings indicate that the HITL-enhanced multi-agent system can support a more objective and transparent assessment of STEM PBL reports, providing actionable insights for learning analysis and educational evaluation. Full article

Over several decades, digital cultural heritage has been increasingly reused across research, education, creative practice and through public community engagement. However, these activities remain undescribed or inconsistently documented and difficult to compare. Organisations typically rely on ‘proxy metrics’ such as downloads, page views or reverse searches to assess use/reuse. However, these metrics reveal little about how materials were transformed, interpreted, or how they generated value and impact. GLAMs often rely on unstructured anecdotes to capture/trace reuse, as it is difficult to retrospectively document reuse when GLAMs publish cultural heritage data openly without the expectation of users to tell the organisation what they did with the digital cultural heritage they accessed and used. Documenting reuse approaches often focuses on single dimensions or factors such as sector, content type, audience or impact. This has resulted in fragmented knowledge about digital cultural heritage reuse, which has created limitations in carrying out evaluations across examples, learning from good practice and planning digital cultural heritage initiatives. This article introduces and empirically grounds a flexible, multi-dimensional schema for documenting and planning digital cultural heritage reuse. Using an abductive methodology that combines literature analysis and synthesis, practitioner interviews, user-journey examinations and iterative prototyping, we developed a six-category framework capturing (1) organisation and context, (2) heritage assets and technologies, (3) purpose and process, (4) users and engagement modes, (5) nature of use and availability, and (6) impact and sustainability. Applied across real-world examples, this framework can reveal forms of value, dependency and risk, often absent from conventional reporting in the reuse of digital cultural heritage. We argue that reuse documentation functions as a form of socio-technical infrastructure, enabling a shared vocabulary and understanding for cross-case comparison, cumulative learning and strategic design of digital heritage initiatives. By shifting categorisation from retrospective description to include prospective planning, the framework supports a more meaningful impact assessment and sustainable reuse of digital cultural heritage as a societal resource. Full article

Sustainable Digital Infrastructure plays an increasingly important role in strengthening regional economic resilience and promoting inclusive growth. However, its dynamic effects on nascent entrepreneurship remain underexplored. Treating China’s smart city pilot policy as a quasi-natural experiment, this study uses data on newly registered enterprises in 288 Chinese cities from 2005 to 2019 and a multi-period difference-in-differences (DID) model to examine this relationship. The results show that Sustainable Digital Infrastructure significantly promotes new venture creation. Owing to environmental dynamism—manifested in creative destruction, strategic wait-and-see behavior, and learning-curve effects—its entrepreneurial impact is initially volatile before becoming significantly and persistently positive. The industry-level analysis reveals heterogeneous effects across sectors: the largest estimated effect occurs in wholesale and retail trade, while the estimated effect in scientific research and technical services strengthens over time. Mechanism analyses provide suggestive evidence for three channels: technological innovation, human capital development, and digital finance. The effects are also more pronounced in eastern China and smaller cities. This study provides empirical evidence and practical guidance for emerging economies seeking to promote new venture creation through digital infrastructure. It conceptualizes “sustainability” in the SDI context as the capacity of digital infrastructure to support enduring and inclusive economic development, rather than as a property of the infrastructure’s environmental performance. Full article

Architectural design problems vary significantly in their degree of definition, and this variation may influence the creative outcomes of student work. This study provides an empirically validated comparison of creativity scores across well-defined and ill-defined architectural design problems, employing a five-criterion framework (elaboration, imagination, flexibility, fluency, and originality) and a double-blind expert jury protocol. By moving beyond theoretical claims, the study offers quantitative evidence on how problem structure shapes creative performance in architectural education. Architecture students were asked to produce solution sketches for both well-defined and ill-defined problems. The creativity of the resulting products was evaluated by an independent jury of domain-expert academics using five criteria established in the literature: elaboration, imagination, flexibility, fluency, and originality. Evaluation scores were subsequently analyzed with statistical methods to determine which problem type elicited higher creativity. In a sample of 20 second-year architecture students, solutions produced for ill-defined problems received statistically significantly higher total creativity scores than those for well-defined problems (p = 0.022, r = 0.51), suggesting that the structural openness of ill-defined problems may be associated with enhanced divergent thinking and original idea generation, though causal mechanisms remain to be established through future process-level research. These results support integrating ill-defined problems and uncertainty-based design scenarios into architectural education studios more frequently to develop creative problem-solving skills. Full article

This exploratory, classroom-based mixed-methods study examined a five-phase, AI-supported multimodal literacy sequence implemented with 25 Grade 4 students over four weeks. The intervention combined interactive digital reading, collaborative narrative writing, AI-supported comic imagery, multimedia editing, and peer reflection. Quantitative analyses compared students’ baseline and post-intervention comprehension scores and summarized responses to a 12-item post-intervention questionnaire. Qualitative data from open-ended responses, classroom observations, and student artifacts were analyzed thematically. Students’ mean comprehension scores increased from 63.81 (SD = 9.70) at baseline to 75.37 (SD = 7.63) after the intervention, representing a significant within-group change, t(24) = 5.49, p < 0.001, dz = 1.10. Questionnaire responses were generally positive, particularly for original story writing, digital comic creation, and the addition of movement and sound. Three qualitative themes were identified: AI-supported representations as scaffolds for narrative comprehension, as catalysts for authorial identity and creative agency, and as mediators of collaborative meaning-making. Because the study used a single-group design and the comparability of the parallel assessment forms was supported through expert content review rather than large-scale psychometric equating, the findings should be interpreted as exploratory evidence of association rather than as causal effects of AI. The study nevertheless illustrates how developmentally appropriate, teacher-mediated AI activities may support multimodal literacy participation in primary education. Full article

Co-Creative Robotics combines computational creativity, robotic embodiment, and human–robot collaboration to support or generate creative behavior in physical and social environments. As these systems become more autonomous, data-intensive, and interactive, cybersecurity and privacy can no longer be treated as external safeguards added after creative functionality has been designed. This PRISMA-informed review investigates whether principles of cybersecurity-by-design and privacy-by-design can be integrated into Co-Creative Robotics without constraining creativity, autonomy, and user agency. The database search covered ACM Digital Library, Google Scholar, IEEE Xplore, Scopus, SpringerLink, and Web of Science, and was complemented by two focused backward and forward snowballing iterations. From 623 database records, the final synthesis includes 27 primary studies. The results show that direct literature combining cybersecurity, privacy, and Co-Creative Robotics remains limited, but evidence from creative HRI, social-robot privacy, cyber-physical security, privacy-preserving interaction design, security modeling, and robot ethics supports a conditional answer. Integration is feasible when security and privacy mechanisms are adaptive, explainable, participatory, context-sensitive, and lifecycle-aware. However, the evidence on transparency-oriented privacy mechanisms is mixed: improvements in awareness or acceptance do not consistently translate into reduced disclosure or greater perceived safety. Rigid controls may constrain creative exploration, whereas well-designed controls can support trust, accountable autonomy, safe embodiment, privacy-aware interaction, provenance, and agency-preserving creativity. The review proposes a conceptual lifecycle-oriented research agenda for secure and privacy-aware Co-Creative Robotics. Full article

Generative artificial intelligence (GenAI) provides a new context for examining how external intelligent systems are associated with human cognitive agency and perceived creative intellectual functioning. Drawing on cognitive offloading theory and AI literacy research, this cross-sectional study tested a moderated mediation model linking GenAI use intensity, GenAI cognitive dependence, AI literacy, and perceived academic creativity. Survey data were collected from 936 undergraduates at six universities in China. Confirmatory factor analysis supported the empirical distinctiveness of the four focal constructs, and latent structural equation modeling was used to examine the hypothesized associations. GenAI use intensity showed a positive direct association with perceived academic creativity and a positive association with GenAI cognitive dependence; cognitive dependence was negatively associated with perceived academic creativity. The standardized direct and indirect associations operated in opposite directions, leaving a small model-implied net association (β ≈ 0.040). AI literacy was negatively associated with cognitive dependence and positively associated with perceived academic creativity. The use-dependence association was weaker at higher levels of AI literacy, and the negative indirect association through dependence was correspondingly smaller. These cross-sectional results are interpreted as associations and do not establish temporal or causal ordering. Full article

Emerging digital technologies are reshaping interior design practice, increasing the need for educational approaches that intentionally support students’ perceived workforce readiness. This study examined the implementation of a mobile 3D scanning application within a university interior design course to examine its association with students’ technology learning self-efficacy and perceived workforce readiness. Using a one-group pre–post survey design, data were collected from interior design students who participated in a classroom-based 3D scanning activity using Polycam and completed surveys before and after the instructional experience. A total of 29 pre-test and 21 post-test responses were collected. Survey instruments assessed students’ perceived importance, familiarity, and experience with 3D scanning, along with technology adoption characteristics. Post-intervention measures also examined technology learning self-efficacy and perceived workforce readiness domains, including career development, self-regulated learning, problem solving, and technological competence. Welch’s independent-samples t-tests and Mann–Whitney U tests indicated that the post-test group reported significantly higher perceptions of familiarity with and experience using 3D scanning, as well as several technology-adoption perceptions, than the pre-test group, including ease of use, work style compatibility, efficiency gains, result observability, and trialability. One-sample Wilcoxon signed-rank tests showed that post-intervention composite scores for technology learning self-efficacy and perceived workforce readiness domains were significantly higher than the neutral scale midpoint. Qualitative thematic analysis of open-ended responses further supported these findings, identifying themes of ease of use, engagement, enhanced visualization, creativity, and professional relevance. Overall, the findings suggest that participation in the classroom-based mobile 3D scanning activity was associated with positive post-intervention perceptions of technology learning self-efficacy and perceived workforce readiness. Full article

Within the framework of United Nations Sustainable Development Goal 4 (SDG 4: Quality Education), adult aesthetic education faces challenges related to the sustainability of access, personalisation, and humanistic values. This study examines levels of acceptance regarding generative AI-assisted aesthetic education in the Open University of China. Drawing on the Technology Acceptance Model (TAM) and lifelong learning theory, we surveyed 518 adult learners and used descriptive analysis (based on the full sample) alongside binary logistic regression and PLS-SEM (based on the 355 learners who had prior aesthetic education experience) to analyse adoption readiness, functional preferences, and influencing factors. Our main findings are as follows: (1) 91.5% of learners recognised the importance of aesthetic education, yet the actual participation rate was only 68.5%; (2) 50% of respondents expressed clear willingness to use AI-assisted aesthetic learning, with the most desired functions being “personalised art interpretation” and “creative inspiration support”; (3) no significant age-related differences were found in AI adoption readiness; (4) logistic regression identified aesthetic cognition and learning experience as significant predictors of AI adoption willingness; and (5) SEM showed that learning experience had the strongest direct effect on AI adoption readiness (β = 0.62) and partially mediated the relationship between aesthetic cognition and AI adoption readiness. We conclude that generative AI should be positioned not as a “substitute” but as a “personalised interpreter and creative partner” in adult aesthetic education. These findings provide practical implications for the digital transformation of The Open University of China and the design of AI-based educational products. Full article

As education embraces digital transformation, integrating AI into pedagogy is increasingly important. One promising innovation is AI-generated 3D models, which help visualize complex concepts, enhance spatial reasoning, and foster creativity. Unlike traditional 3D modeling, which requires advanced skills and time, AI tools make content creation more accessible to educators and students. This study develops and validates a structured methodology for using AI-generated 3D models in education. It supports personalized, rapid, and intuitive content development, particularly in STEM. The framework includes guidelines for effective text-to-3D prompts, validation of educational impact, and a roadmap toward immersive technologies like VR, AR, and digital twins, enabling scalable, student-centered learning experiences. Full article

Long-context modeling is important for long-horizon generation tasks, yet larger context windows do not necessarily ensure stable organizational continuity. We propose Dimension-Constrained Organizational Relay (DCOR), a workflow-level framework that reformulates long-horizon generation as the ordered propagation of finite organizational states rather than repeated replay of complete token histories. DCOR introduces Order and Dimension to represent sequential organizational evolution and task-oriented constraints, and comprises Organizational Set Extraction, Dimension-Constrained Generation, Organizational Relay, and Organizational Convergence. We evaluate DCOR on cumulative multi-instance advertisement generation and long-form article generation. Across ten advertisement runs, DCOR generated 259–315 structured creative blocks per run, averaging 279.3 ± 17.9, while maintaining the required format and producing no exact duplicate blocks. At the matched 30-block scale, its main advantage was cumulative structured production rather than the lowest character-level repetition. In long-form generation, DCOR achieved the lowest mean character-level 4-gram and 6-gram repetition compared with Direct Generation, Rolling-Summary Generation, Hierarchical-Outline Generation, and Neural RAG-Memory, while maintaining high Distinct-2 and Distinct-3 values. Ablation results further showed that removing Dimension, Organizational Relay, or Order increased repetition and reduced sustained multi-section expansion. These findings support organizational-state propagation as a complementary mechanism for structured long-horizon generation under restricted local-context conditions. 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 examines how Generative AI (GenAI) was integrated into creative sustainability education through the STEM Education for Sustainability (STEM4S) framework. Conducted in 2024, the study examined a nine-week intervention comprising a breastfeeding-room track in a second-year interior-design course and a sports-gym track in a third-year commercial-space-design course. Twenty students completed the pre-assignment questionnaire, and 18 completed matched pre- and post-assignment questionnaires after two withdrawals. GenAI was introduced as a scaffolded method-bank tool to support prompt-based ideation, visualization, and critique. A qualitative-dominant mixed-methods case-study design combined matched pre- and post-assignment questionnaires, student reflections, classroom observations, project outcomes, and professional critique records. Paired comparisons showed that students’ self-rated SDG 11 knowledge increased from 2.94 ± 1.16 to 3.56 ± 0.92 (p = 0.012, Cohen’s d_z = 0.67), while SDG 5 knowledge decreased from 4.39 ± 0.70 to 3.72 ± 1.02 (p = 0.014, Cohen’s d_z = −0.65); both findings are interpreted as exploratory due to the small sample. Qualitative findings indicate that GenAI supported visual exploration but also produced prompt difficulty, visual repetition, and spatial inconsistency. The findings suggest that GenAI can extend the STEM4S method bank when embedded within civic learning, critique, and human design judgment, while its transferability requires further testing across contexts. Full article