Search Results (3,597)

Decolonising assessment remains an underdeveloped yet essential component of higher education transformation. In research, much attention has been assigned to decolonising content knowledge and pedagogy, with limited attention to assessment. Hence, this systematic literature review examines empirical studies published between 2018 and 2025 to explore how decolonial assessment is enacted in higher education. Using the PRISMA 2020 framework, 17 studies were analysed to identify theoretical foundations, methodological trends, dominant themes, key findings, and literature gaps to make recommendations for future research. The findings reveal six interconnected practices characterising decolonial assessment: humanising learning, contextualising assessment within students’ cultural and community realities, disrupting power hierarchies through co-creation, collaborative and peer-based approaches, diversifying modes of expression, and enhancing transparency and cultural responsiveness. These practices validate students’ lived experiences, foreground multiple epistemologies, and challenge traditional assessment norms, thereby promoting deeper engagement, agency, and belonging. However, the scholarship is constrained by a reliance on small-scale qualitative designs, limited theoretical development, and regional concentration, particularly in South Africa and the United States. The review concludes that while decolonial assessment offers transformative potential, its broader institutional uptake requires methodological pluralism, stronger theoretical frameworks, and policy-level support. The paper recommends embedding decolonial principles in assessment design, expanding research across diverse contexts, and strengthening lecturer capacity to develop equitable, inclusive, and contextually grounded assessment practices that advance epistemic justice in higher education. Full article

Entrepreneurial ecosystems are increasingly viewed as drivers of sustainable and inclusive development, yet their true capacity to translate entrepreneurship into inclusive outcomes remains insufficiently understood. This study addresses this gap by linking national-level entrepreneurship indicators to three dimensions of inclusive growth—decent work and economic growth (SDG 8), innovation and infrastructure (SDG 9), and inequality reduction (SDG 10)—using data from the Global Entrepreneurship Monitor’s National Expert Survey (NES) for 37 countries over the period 2020 to 2024. By integrating multistage machine learning techniques with institutional and ecosystem theories, the study captures the nonlinear and interdependent dynamics among entrepreneurial framework conditions. The results reveal that development outcomes depend not on isolated factors but on complementarities among finance, infrastructure, and R&D transfer. Entrepreneurial ecosystems foster innovation and productive employment, yet their inclusiveness hinges on institutional efficiency, governance quality, and redistributive capacity. The findings show that policy intent diverges from policy impact, as governmental support and cultural norms exert adverse effects when institutional coherence and absorptive capacity are weak. The research advances entrepreneurship theory by moving beyond linear, additive models toward a systemic understanding of ecosystem complementarity, and offers policy insights, emphasizing that innovation-led growth must be embedded in institutional coherence and social inclusion to achieve sustainable and equitable development. Full article

Island destinations combine natural settings, local culture, and participatory activities that may support recovery, social connection, and personal meaning. Evidence remains limited on the relative contribution of different island experience dimensions to tourist satisfaction and well-being, especially in inhabited island destinations. This study examined four experience dimensions in West Island, Sanya, China, and used the findings to develop a destination improvement model. Tourist satisfaction was conceptualised as a visit-specific evaluation, while tourist well-being referred to the broader psychological benefits associated with travel. An explanatory sequential mixed-methods design was adopted. The quantitative phase used 411 valid questionnaires from Chinese domestic tourists. A full six-construct confirmatory factor analysis assessed the measurement model, after which multiple and simple linear regressions tested the prespecified direct relationships. The six-factor model showed good fit (χ²(390) = 389.98, p = 0.491, CFI = 1.000, TLI = 1.000, RMSEA = 0.000, SRMR = 0.035). The four experience dimensions explained 58.0% of the variance in tourist satisfaction. Co-creation experience made the largest unique contribution (β = 0.345), followed by emotional experience (β = 0.329) and environmental experience (β = 0.312; all p < 0.001). Educational experience was not significant (β = 0.029, p = 0.422). Tourist satisfaction had a significant positive influence on tourist well-being (β = 0.764, p < 0.001; R² = 0.583). Semi-structured interviews with 12 experienced tourists explained the coefficient pattern through ten themes, and seven academic and industry experts refined five strategic components through two Delphi rounds. The resulting model prioritises cultural co-creation, emotional resonance, environmental quality, and service support, while treating transformative learning as an area for targeted development and evaluation. The integration of survey results, tourist accounts, and expert assessment provides an evidence base for selecting and monitoring destination improvements in inhabited island settings. Full article

Audio magnetotelluric (AMT) sounding is an essential tool for mineral exploration and subsurface electrical structure imaging. However, persistent cultural noise can severely degrade AMT data quality, particularly in mining areas with strong anthropogenic interference. In this study, we introduce an improved K-Singular Value Decomposition (K-SVD) dictionary learning method for time-domain AMT data denoising, incorporating three key innovations: (1) automatic identification of noise-contaminated segments using local kurtosis; (2) adaptive dictionary initialization combining principal component analysis with Gaussian perturbation, which accelerates convergence and avoids local minima; and (3) online atom screening and updating to maintain the noise specificity of the learned atoms. The proposed method learns noise morphology directly from raw AMT data without requiring reference stations or external training datasets. Synthetic experiments demonstrate that the method more effectively suppresses square-wave and charge-discharge noise compared with wavelet thresholding methods and conventional K-SVD, while better preserving signal morphology. Field applications further show that it significantly enhances the quality of observed data and apparent resistivity-phase curves compared with the widely used robust estimation method. The proposed method provides an efficient, reference-free solution for AMT data denoising in mining areas with strong cultural noise. Full article

The rapid expansion of English-medium instruction (EMI) in transnational education (TNE) has increased the need for evidence-based higher education (HE) curriculum models that support diverse student cohorts in cross-cultural contexts. This exploratory mixed-methods study examines the effectiveness of block models in EMI TNE partnerships by comparing English as an additional language/dialect (EAL/D) student outcomes across traditional semester-based models and immersive block-model delivery in China and Papua New Guinea, and by exploring students’ block-model experiences. Retrospective institutional data on student success (N = 8974) and satisfaction (N = 2067) were analysed alongside focus group data on student experiences. Findings indicate that the block model is associated with significantly higher student success rates in China (76.3–92.2%) and Papua New Guinea (57.3–72.1%; both p < 0.001), while satisfaction remained high and increased significantly in China. In addition, students perceive the model as fostering self-discipline, autonomous learning, and collaborative skills. This study extends the limited evidence base on curriculum innovation in English-medium transnational higher education, indicating that immersive block models can support positive student outcomes while highlighting the importance of local implementation conditions in shaping students’ experiences. Implications emphasise the need for consistent operationalisation of the block model and pedagogical scaffolding to optimise effectiveness in cross-cultural higher education settings. 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

Cultural heritage sites are affected by environmental and anthropogenic pressures that require decision-analysis methods capable of combining heterogeneous datasets while accounting for uncertainty. Multi-Criteria Decision Analysis (MCDA), particularly when integrated with Geographic Information Systems (GIS) and Earth Observation (EO) data, is widely used in geospatial analysis involving multiple, often conflicting criteria. This review examines the evolution, application domains, and methodological challenges of MCDA in cultural heritage risk assessment. The literature indicates a predominant reliance on weighting-based methods, especially the Analytic Hierarchy Process (AHP) combined with GIS-based weighted overlay techniques, while uncertainty treatment, temporal monitoring, validation, and multi-threat applications remain limited. Three illustrative applications show that asset-level, regional susceptibility, and historic-urban frameworks address complementary decision needs but differ in their data, expertise, and institutional requirements. Recent developments show a trend to combine MCDA with fuzzy logic, machine learning, and uncertainty modeling, although methodological consistency across these approaches remains uneven. The findings suggest that multi-criteria risk assessment for cultural heritage may depend less on introducing new analytical techniques and more on improving the integration of existing methods. Incorporating repeatable environmental observations, sensitivity analyses, multi-threat assessment, and stakeholder participation may support a more coherent and reproducible approach to heritage-risk assessment. Full article

Nigerian secondary schools face significant challenges integrating fourth industrial revolution (4IR) technologies. Little is known about how contextual factors influence teachers’ familiarity with these technologies and their perceptions of student engagement, learning outcomes, and instructional efficiency. Using a convergent parallel mixed-methods design, this study examined those factors in public and private secondary schools across one Local Government Area within each of four Nigerian states (Imo, Rivers, Osun, and Kogi). The quantitative component surveyed 189 teachers (92 public, 97 private). The qualitative component interviewed nine teachers and conducted two focus groups with 12 teachers (six in each group). Quantitative findings showed that teachers reported moderate familiarity with most 4IR technologies (grand mean = 3.11) and positive perceptions of their influence on student engagement (grand mean = 3.64) and learning outcomes (grand mean = 3.80). Private school teachers reported significantly higher familiarity with six of seven technologies and more positive perceptions of engagement (p < 0.001) and learning outcomes (p < 0.001) than public school teachers, except for WhatsApp (p = 0.332). Qualitative thematic analysis revealed four themes explaining these differences: (1) structural and infrastructural inequities (electricity, internet, devices) shape technology engagement; (2) teachers sustain integration through personal financial sacrifice and informal peer support; (3) professional development is perceived as contextually disconnected; and (4) technological engagement reflects interactions between generational confidence, pedagogical identity, and school culture. The joint display of quantitative and qualitative findings shows convergence on the conclusion that infrastructure, not teacher attitude, is the main barrier to 4IR adoption. Policymakers should prioritise investment in electricity, internet, and devices over blaming teachers. Full article

Distinguishing tuberculous spondylodiscitis (TS) from pyogenic spondylodiscitis (PS) on imaging remains clinically important because the two entities differ in antimicrobial strategy, surgical timing, and the urgency of microbiological workup, yet no single imaging sign is pathognomonic for either diagnosis. When tissue confirmation is delayed, imaging becomes the primary tool that shifts pre-test probability and guides biopsy strategy—a role that is particularly critical in culture-negative disease, in antibiotic-exposed patients, and in settings with limited access to rapid mycobacterial diagnostics. This narrative review maps the imaging evidence most useful for routine TS-versus-PS differentiation, synthesizes recent prediction models and quantitative tools, and evaluates the adjunctive role of ¹⁸F-FDG PET/CT in biopsy-oriented decision-making. PubMed/MEDLINE was searched from inception to 31 March 2026 using pre-specified search terms across three concept blocks. This was a narrative review without formal pooling of quantitative estimates or prospective protocol registration. A secondary Scopus search identified no additional eligible records. Priority was given to comparative TS-versus-PS imaging cohorts, meta-analyses of MRI and CT features, prediction-model studies, and the recent radiomics and PET/CT literature; radiomics and deep-learning studies are appraised as a distinct evidence tier given their retrospective single-center derivation and predominantly internal-only validation. In total, 14 comparative TS-versus-PS imaging cohorts, three meta-analyses, and 14 prediction-model, quantitative-scoring, radiomics, or deep-learning studies formed the core evidence base. MRI yields the greatest differentiating information and is the recommended first-line modality. Features favoring TS include thoracic predominance, multilevel or non-contiguous involvement, relative early disc preservation, subligamentous spread, intraosseous abscesses, thin-walled paravertebral collections, and severe vertebral collapse with kyphotic deformity. Features favoring PS include lumbar predominance, early disc-endplate destruction, homogeneous inflammatory enhancement, facet-joint arthritis, and epidural phlegmon. CT adds osseous detail—including sequestra, subligamentous bone erosion, and paravertebral calcification—and remains the primary guidance modality for biopsy. Recent prediction models combining imaging and laboratory variables have shown high discriminative performance in derivation cohorts; however, most remain internally validated and locally calibrated. Pending external validation, none should be considered ready for unmodified clinical adoption, and they should therefore be used as probability modifiers rather than stand-alone diagnostic rules. ¹⁸F-FDG PET/CT is complementary rather than primary and is most useful when MRI is contraindicated or equivocal, in hardware-associated infection, and for whole-body staging in suspected disseminated tuberculosis. Non-infectious mimics and alternative infectious diagnoses should be considered when the imaging pattern is internally inconsistent or when standard cultures remain negative. Imaging findings should refine etiological probability and guide biopsy strategy, but should not replace tissue confirmation when tissue is feasible. Non-imaging evidence complementing this review is addressed in the companion manuscript, Part I. Full article

The COVID-19 pandemic and subsequent Emergency Remote Teaching (ERT) response by universities led to the rapid and widespread adoption of learning technologies. There is much to learn about the role of the pandemic as a disruptive influence on technology adoption in higher education. However, despite a great deal of research conducted both during and immediately after the ERT period, there has been limited attention to its longer-term effects on technology usage. This paper addresses a gap in the literature by exploring the lasting influence of ERT on practices at the University of York (UK). Taking a qualitative approach and socio-cultural orientation, we undertook semi-structured interviews with teaching leaders in thirteen departments across a wide range of disciplines. Lasting changes in the adoption of digital tools following ERT were evident in all departments, but the nature and impact of these changes were shaped by longer-term influences, often predating ERT and further shaped by subsequent changes and challenges such as increased student numbers and the widespread adoption of Generative Artificial Intelligence. We conclude that the impact of ERT on technology adoption needs to be placed in context as one influence among other factors in an evolutionary process of pedagogical change. Full article

This article examines how theology can engage meaningfully with secular academic and cultural contexts, focusing on the possibility of public theology within the modern university. Emerging from societies where religion was long marginalized or privatized under communist regimes, the discussion highlights the renewed struggle to reintegrate theological discourse into public intellectual life. It argues that public theology must learn to “speak faith publicly”—that is, to express religious convictions in ways that contribute to shared intellectual and moral discourse without resorting to confessional exclusivity. By comparing public theology to public philosophy, the authors highlight both the similarities and tensions between the two. While both seek to address common human questions concerning truth, value, and meaning, public theology must navigate the added complexity of grounding its insights in faith traditions while remaining open to secular dialogue. The article argues that the Beatitudes and the concept of middle axioms provide complementary theological and methodological resources for communicating Christian faith within secular higher education, as illustrated by a qualitative case study conducted at a public university in Slovakia. Full article

Chengde, China, is famous for its Qing Dynasty imperial gardens, which are a World Heritage Site. In recent years, it has received increasing attention from heritage research scholars. From a tourism perspective, tourists’ visits are important for supporting economic benefits, heritage conservation, and sustainable development. This study integrated the four dimensions of the 4E heritage communication framework—experience, exchange, everyplace, and evangelism—with heritage interpretation quality to develop a model to uncover cultural heritage visiting behavior. Based on the survey data of 887 Chinese tourists who have visited Chengde’s cultural heritage sites, structural equation modeling (SEM) was employed. The results showed that experience, exchange, everyplace, and evangelism, together with heritage interpretation quality, were all positively associated with cultural heritage visiting behavior. Perceived destination image and perceived conservation both significantly predicted cultural heritage visiting behavior and served as significant mediators in most of the proposed indirect relationships; however, the indirect path of evangelism through perceived destination image was not supported. Source credibility strengthened the relationships between the five antecedents and cultural heritage visiting behavior. Therefore, this article encourages the development of high-quality, comprehensive marketing strategies to attract more people to learn about World Cultural Heritage, while simultaneously improving guided tour services and their quality. It also emphasizes building a more positive cultural tourism image and conducting precise public relations to ensure that World Cultural Heritage receives support and attention from governments, educational institutions, and travel agencies. Full article

Human societies depend on prestige hierarchies that confer status on demonstrated competence, alongside the dominance hierarchies that rely on coercion and that humans share with other primates. The same neural processes that support cooperative learning under prestige are hypothesized to participate in rivalry, polarization, and ideological hostility when their operating environments depart from those in which they evolved. This selective narrative review proposes a candidate integrative framework, the Hypothesized Neural Integration Model of Prestige and Pride, drawing on converging but largely indirect evidence from affective neuroscience, neuroeconomics, evolutionary psychology, and social neuroscience. The framework groups five categories of functionally pluripotent processing, each understood as engaging nodes within overlapping large-scale brain networks rather than as a localized regional mechanism: valuation-related processing implicating orbitofrontal and ventromedial prefrontal cortex, reward-learning signals indexed in the ventral striatum, self-referential and identity-relevant processing engaging medial prefrontal cortex within the default-mode network, threat- and salience-related processing involving the amygdala and anterior cingulate cortex within the salience network, and neuroendocrine output regulated through the hypothalamic–pituitary–adrenal axis and modulated by gonadal and neuropeptide systems. Consistent with Poldrack on reverse inference and with Marr on levels of analysis, the framework is presented at an integrative implementational level with candidate algorithmic mappings specified for each category, not as a computational specification of the constructs themselves, and treats high-level constructs such as prestige, status, and sacred value as emergent phenomena arising from dynamic network interactions, bodily states, cultural contexts, and historical contingencies rather than as properties localized to single regions. Because few neuroimaging paradigms isolate freely conferred deference from generic social rank, claims specific to prestige are deliberately restricted throughout, and the evidence base is presented as one concerning social rank unless a paradigm operationalizes prestige directly. Material ownership, sacred values, religious belief, and digital prestige metrics are treated as candidate domains of application, with explicit separation of direct neural evidence, behavioral evidence, and theoretical extrapolation. Symbolic escalation in consumer markets, sacred-value absolutism, and amplified social feedback on digital platforms are interpreted as candidate environmental amplifiers of ancestral status mechanisms rather than demonstrated causal pathways. Nine operational study designs are proposed to guide future preregistered tests, including one designed to establish whether a prestige-specific neural claim can be made at all. Intervention strategies are mapped to candidate processing and network targets using an explicit evidence-grading scheme, with structural and institutional measures weighted equally alongside cognitive and contemplative ones. The framework relies on correlational neuroimaging subject to reverse-inference constraints, draws primarily from samples from Western, educated, industrialized, rich, and democratic populations, and should be evaluated as a hypothesis-generating account rather than as a confirmed neural architecture. Full article

Reflecting on emotionally challenging experiences with caregivers is a critical developmental process through which children learn to identify, express, and regulate emotions. However, much of the existing literature on caregiver–child emotion socialization has centered White, middle-class families, limiting understanding of how these processes unfold within culturally and contextually situated interactions among Black families. Guided by Margaret Beale Spencer’s Phenomenological Variant of Ecological Systems Theory and the Integrative Conceptual Model of Adaptive Racial/Ethnic and Emotion Socialization, the present study explored how Black girls (ages 5–11) described experiences of sadness, stress, and anger during caregiver-guided conversations embedded within a culturally grounded shared book reading activity. Fifteen Black girls (M = 8.27 years, SD = 1.71) and their caregivers participated in a novel video-recorded shared reading activity followed by a guided discussion about emotions. Black girls described sadness in relation to separation from loved ones, social exclusion, and witnessing harm; stress primarily in response to academic pressures; and anger in response to perceived unfairness and injustice. They also identified diverse emotion regulation strategies, including deep breathing, solitude, cognitive reframing, imaginative coping, and seeking social support. Across emotional contexts, caregivers consistently encouraged elaboration, validated children’s emotional experiences, and reinforced adaptive coping strategies, creating supportive opportunities for collaborative emotional meaning-making. Our findings highlight shared reading as a culturally affirming context for caregiver-supported emotion socialization and underscore the importance of centering Black girls’ voices in research on socioemotional development. Full article

The rapid integration of artificial intelligence (AI) into higher education marks a radical epistemic shift, unsettling long-held assumptions about how knowledge is made, taught, and judged. This paper argues that the theory of living structure offers a timely foundation for liberal arts and whole-person education in the era of AI. Living structure—Christopher Alexander’s term for the recurrent hierarchical order that makes environments feel alive—is treated here as two faces of one phenomenon: living, the right-brain perception of wholeness, and structure, the left-brain order that can be computed through fifteen geometric properties, two fundamental laws, two design principles, and the computable L- and B-scores. From this basis the paper develops a Living Structure + AI paradigm, a new episteme for higher education, deliberately so ordered because living structure is held to be more fundamental than AI: structure is the order of nature and culture, while AI is a tool that gives that order new expression. The argument is grounded in teaching practice led by LivableCityLAB, under its own teaching-research project and in partnership with Residential College 1, spanning architecture and city-science courses or theses, an undergraduate whole-person common-core course (Self and Wholeness), and a new postgraduate course (Experiential Learning: Living Structure + AI Inspired Design). Across these settings, students read built environments structurally, declare a skeleton, and use AI as a structural mediator while making and inhabiting real spaces. Across four campus renovations (total N = 33 students) and the two courses (N = 49 undergraduates; N = 7 postgraduates), structural scores (the L- and B-scores) rose in every renovated case, and these architectural and perceptual measures converged with preference tests and visual-attention analysis; course-embedded, rubric-based assignments provide complementary, though not psychometrically validated, evidence of students’ engagement with the paradigm. This paper closes by arguing that the deepest contribution of Living Structure + AI to liberal arts education is not on paper or on screens but down to earth—in the daily life spaces in which students learn to feel, measure, and remake wholeness. Full article