Search Results (21,274)

This study investigates how community engagement and outreach programs can serve as a vehicle for knowledge co-production between higher educational institutions (HEIs) and industry in developing economies. Despite growing calls for collaboration between HEIs and industry, the existing literature remains policy-driven and largely instrumental, offering a limited understanding of how engagement practices are socially constructed, negotiated, and experienced by diverse stakeholders. There is limited qualitative research on how community voices are integrated into co-creation processes and how these interactions shape sustainable development in emerging economies. The research methodology for the study was developed using the research onion, and an interpretivist research philosophy was adopted. The study employed an inductive research approach to explore actors’ lived experiences and the meanings attached to engagement practices and collected data through in-depth interviews. Participants in the study included representatives from HEIs, industry, and community stakeholders across selected sectors of the economy, and the data were analysed thematically to capture patterns of interactions, power relations, and knowledge and exchange processes underpinning co-production. The study revealed that effective community engagement goes beyond formal partnerships to encompass building lasting relationships which are characterised by trust, mutual learning, and context adaptation. Further, the study also showed that power asymmetries, institutional pressures, and resource constraints have restricted real co-production, resulting in symbolic rather than real engagement. Nevertheless, the use of inclusive and reflective approaches has been shown to foster locally acceptable and essential innovative interventions that can improve sustainable development. The study therefore recommends embedding participatory frameworks within HEIs and industry collaborations to strengthen institutional support for inclusive engagement and to reorient policies towards community-centred knowledge systems. This study, therefore, contributes to the body of knowledge by enhancing theoretical and practical understanding of sustainable higher education–industry collaboration in developing economies by promoting an understanding of engagement as a co-production process. Full article

Personal health and safety are significant concerns across agricultural education, specifically agricultural mechanics. While hearing safety has been discussed for numerous years as a shortcoming in overall safety actions, it has been identified that attitudes and perceptions of sound and noise within agricultural settings are not aligned. This research continues work to focus on students’ understanding of and application of safety culture within an agricultural mechanics environment. Through direct and indirect exposure to noise levels, students reflected on and identified their use and intended use of hearing personal protective equipment (PPE). Pre- and post-instructional data aided in establishing students’ thresholds to use proper personal protective equipment and identify their perceptions of the decibel (dB) outputs for commonly used power tools in an agricultural laboratory setting. Course reflections alarmingly show a disconnect between intention and practice as many students do not utilize hearing PPE. While indicated threshold values and tool-specific PPE use align with the National Institute for Occupational Safety and Health’s recommended hearing PPE guidelines, the self-reported hearing PPE use results are concerning. While knowledge and application gaps still need to be addressed, based on this exploratory study, bounded in a single instructional context, continued exposure through direct and indirect instruction leads to increased knowledge of sound levels. Full article

Background/Objectives: Hispanic adults in the United States seek and access professional mental health services at a disproportionately lower rate than non-Hispanic White adults, despite having similar rates of mental health challenges. Community focus groups held in El Paso, Texas, in 2022 revealed both systemic and individual-level factors that serve as barriers to help-seeking and access. Participant recommendations for overcoming these barriers included increasing mental health education and improving the cultural responsiveness and navigability of mental health services. Stemming from these findings and informed by the literature on trauma-informed practice, culturally responsive interventions, and evidence-informed practices, we developed and pilot-tested a 4-week closed group community-grounded mental health engagement program called Pensamientos y Pláticas. Methods: The program was offered to 82 participants. Paired-sample t-tests were used to analyze differences between pre- and post-intervention data for the outcome variables assessed: stigma and emotional well-being. Analysis was limited to the 39 participants who completed at least half of the modules and had intact pre- and post-intervention data. Results: Data analysis revealed a statistically significant reduction in stigma related to help-seeking with a small-to-moderate effect size, while no statistically significant increase in emotional well-being was supported by the data. Conclusions: Findings from this pilot study reflect preliminary evidence of feasibility, acceptability, and potential benefit at reducing stigma related to seeking help in Hispanic communities and support Pensamientos y Pláticas as a promising culturally responsive stigma-reduction intervention. Full article

This systematic review examines how students and teachers acquire, reproduce, and transform essentialist beliefs about social categories such as gender, race, class, and disability. These beliefs attribute fixed and natural characteristics to social groups, thereby contributing to the legitimization of social hierarchies from an early age. Unlike studies that focus on measuring these beliefs or analyzing their effects, this review examines the processes through which they emerge, circulate, and stabilize, especially in educational contexts. I analyzed 29 empirical studies published between 2014 and 2024, identified through a systematic search in Web of Science and Scopus and reported according to PRISMA guidelines. The corpus includes experimental, quasi-experimental, correlational, descriptive-comparative, and non-experimental studies, most of which use cross-sectional data. The findings were organized into three analytical dimensions: trajectories in the production of essentialist beliefs; sociocultural–institutional mechanisms of circulation and stabilization; and categorical approaches across social groups. The review shows that essentialist beliefs are not only individual cognitive dispositions, but are also shaped by educational practices, family narratives, media representations, scientific explanations, and broader sociocultural contexts. Overcoming essentialism requires not only new educational content, but also critical attention to the classificatory and epistemic frameworks through which social differences are made to appear natural, stable, and teachable. Full article

In an increasingly complex financial landscape, individual financial behavior is shaped by a range of cognitive, technological, and psychological factors. Existing research on financial behavior often examines financial literacy, FinTech adoption, and financial attitude separately, with limited attention to their combined effects or to whether these relationships remain consistent across contrasting economic environments. To address this gap, this study examines the associations of financial literacy and FinTech adoption with financial behavior, both directly and indirectly through the mediating role of financial attitude. Grounded in the Theory of Planned Behavior and the Technology Acceptance Model, the study proposes an integrated behavioral model using primary data from two contrasting contexts: Lebanon, a financially constrained and unstable environment, and the United Arab Emirates (UAE), a stable, high-income country with advanced FinTech infrastructure. Data were collected through a survey of 400 respondents and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that financial literacy and FinTech adoption are positively associated with financial behavior in both countries. Moreover, financial attitude significantly mediates both relationships. Measurement invariance was established prior to cross-country comparisons, and the multi-group analysis indicated that the structural relationships were generally comparable across Lebanon and the UAE despite descriptive differences in several path coefficients. The study contributes to the behavioral finance and sustainable finance literature by integrating cognitive, technological, and psychological predictors within a unified framework, validating the mediating role of financial attitude, and providing cross-national evidence from two contrasting economic contexts. The findings suggest that strengthening financial literacy alongside responsible FinTech adoption may support more sustainable and inclusive financial behaviors, particularly in environments characterized by economic instability and unequal access to financial services. Practical and policy implications are offered for educators, FinTech providers, financial institutions, and policymakers, emphasizing the importance of context-sensitive initiatives that promote financial resilience, financial inclusion, and the development of sustainable financial systems. Full article

Wild edible plants play a crucial role in supporting rural livelihoods, yet knowledge about their use remains under documented, particularly among younger generations and across gender lines. This study examined the distribution of ethnobotanical knowledge of wild edible plants across age and gender groups in four municipalities of the Vhembe District, South Africa. Data were collected through semi-structured interviews conducted with 160 participants, primarily in the Venda region. Gendered patterns emerged, where women were more familiar with wild vegetables, while men demonstrated greater knowledge of wild fruits. Promisingly, some female youth demonstrated greater knowledge than older women and male participants. Voucher specimens of the cited plants were verified at the University of Venda Herbarium, and data were analysed using qualitative methods and generalised linear models. Results of this study suggest the need to document and conserve Indigenous knowledge, promote intergenerational knowledge transfer, and empower women and youth in traditional food systems to enhance food security and cultural heritage. The study further provides a foundation for future research on knowledge transmission pathways and supports the development of targeted, community-based conservation and educational initiatives to enhance food security and cultural heritage. Full article

Students are frequently assigned factual readings to learn disciplinary knowledge, yet such readings are often experienced as effortful, externally imposed, and assessment-driven. By contrast, fiction read for pleasure can absorb readers so deeply that they voluntarily learn characters, histories, places, rules, and lore from imaginary worlds. This contrast is not simply a matter of facts versus fiction. It reflects several overlapping dimensions, including narrative versus expository structure, assigned versus self-chosen reading, assessment pressure versus voluntary engagement, and isolated information versus richly connected worlds. In this Perspective paper, I provide: (1) an examination of why fictional worlds and fiction more generally can be so engaging, (2) an overview of mechanisms that support engagement, comprehension, and memory, and (3) design principles for making assigned factual readings more engaging. This is a conceptual synthesis rather than a systematic review or report of new empirical data. I distinguish less-mutable differences between pleasure reading and assigned reading from mutable design levers that educators and authors can use. My goal is not to suggest that educational readings should become fiction, nor that pleasure is a substitute for rigour, but rather to identify how factual readings can be made more engaging by leveraging narrative schema, mental imagery, prior knowledge, self-relevance, topic interest, and social reading, alongside assessments that reward meaningful understanding. Full article

Generative artificial intelligence (GenAI) is rapidly transforming teaching, learning, research, and institutional practices in higher education, increasing the need to understand how university professionals engage with AI technologies in both functional and ethical contexts. This study examined AI adoption among sampled Generation Y (Gen Y) and Generation Z (Gen Z) higher education professionals by investigating the relationships among AI Competency Capability (AICC), AI Utilisation Behaviour (AIUB), Perceived Usability (PU), Perceived Strategic Value (PSV), AI Ethical Awareness (AIEA), AI Self-Efficacy (AISE), Responsible AI Utilisation Behaviour (RAIUB), Academic Engagement (AE), Perceived Performance Outcomes (PPO), and AI Adoption Intention (AAI). Adaptive Structuration Theory (AST) and Dual-Process Theory (DPT) were employed as complementary interpretive perspectives rather than as theories directly tested by the structural model. Data were collected from 870 higher education professionals employed at Saudi Arabian universities and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM), Partial Least Squares Multi-Group Analysis (PLS-MGA), and the Measurement Invariance of Composite Models (MICOM) procedure. The PLS-MGA identified statistically significant between-group differences only for the relationships between AICC and AIUB, which were numerically larger among the sampled Gen Z participants, and between AIEA and Responsible AIUB, which were numerically larger among the sampled Gen Y participants. All remaining differences represented sample-specific numerical variations rather than statistically confirmed between-group differences. Given the cross-sectional design and differences in age, career stage, institutional role, and professional experience, the findings should be interpreted as sample-specific associations rather than fixed generational characteristics. This study introduces the Gen-AI Dual Competency Alignment Framework (GADCAF) as a provisional conceptual and interpretive framework, intended to guide future research on AI competency, responsible AI utilisation, and organisational AI integration rather than as a validated theoretical model. The findings advance understanding of the complementary functional and ethical dimensions of AI adoption in higher education. Full article

Generative Artificial Intelligence (GenAI) is rapidly reshaping higher education, especially in technology-oriented programs where critical thinking and complex problem solving are core outcomes. This study triangulates global and local evidence on performance/efficiency, usage, autonomy, critical-thinking engagement, and ethics by combining a systematized review informed by Kitchenham and structured using selected PRISMA 2020 elements (2020–2025; last search: May 2025; 49 studies; Scopus, ACM Digital Library, IEEE Xplore, and SpringerLink; not prospectively registered) with an anonymous survey of 302 computing and engineering students from a single university in Ecuador. The expert-reviewed instrument showed acceptable internal consistency for most scale-based dimensions (McDonald’s $\omega$), whereas institutional and ethics-related items were analyzed primarily at the item level. Results showed near-universal academic GenAI use (96%), with 47% of students reporting weekly use and 26% daily use. Research-related work was the most frequent application (81.5%), followed by homework (48.3%), report writing (43.7%), and exam preparation (41.7%). Although students reported perceived efficiency gains, concerns persisted about reduced analytical engagement and technological dependence (84.1%). Ethical concerns centered on dependence, authenticity, and data privacy, while institutional responses pointed to the need for formal training (96.7%) and clearer guidance. Based on this triangulation, we propose a context-bounded interpretive framework suggesting that GenAI’s educational value depends on instructional and governance conditions that preserve autonomy, critical thinking, integrity, and equity. Full article

Background/Objectives: Sleep health is a key determinant of physical and psychological well-being, yet poor sleep quality remains common, particularly among women. Sociodemographic inequalities and culturally patterned pre-sleep behaviours may contribute to sleep disturbances, but their combined role in Mediterranean populations is still insufficiently understood. This study aimed to examine sleep quality and its associations with sociodemographic characteristics and pre-sleep habits among adult women living in Spain. Methods: A cross-sectional online survey was conducted among 785 Spanish adult women aged 18–64 years. Sleep quality was assessed using the Spanish version of the Pittsburgh Sleep Quality Index (PSQI). Additional questionnaire items collected information on sociodemographic variables and pre-sleep habits, including meal timing, stimulant consumption, physical activity, bedtime routines, screen exposure, and sleeping alone or with company. Data were analysed using chi-square tests, Mann–Whitney U tests, Kruskal–Wallis tests, Spearman’s correlations, and principal component analysis. Results: The mean global PSQI score was 7.5 (SD = 3.01), indicating mildly impaired sleep quality overall. Age showed the largest association with global PSQI score (ε² = 0.052, p < 0.001), followed by income (ε² = 0.010, p = 0.016). Frequent nocturnal awakenings were the most common sleep disturbance, whereas sleep medication use was uncommon. Older age and lower income were associated with poorer sleep outcomes, including shorter sleep duration, lower sleep efficiency, and higher global PSQI scores. Higher education and health-related training were generally associated with more favourable sleep profiles. Pre-sleep habits such as late dinners, stimulant use, and evening screen exposure were highly prevalent but showed weak and non-significant associations with global PSQI scores. Conclusions: In this cross-sectional sample, poorer sleep quality was associated with selected sociodemographic characteristics, whereas isolated pre-sleep behaviours showed weak or non-significant associations with global PSQI scores. Given the study design and non-probability sampling, these findings should be interpreted as associations and generalized with caution. They may inform future studies and support the development of gender-sensitive, non-pharmacological sleep-health strategies that consider socioeconomic and cultural context. Full article

The Ilha Grande National Park region (Brazil) holds one of the most diverse traditional knowledge repositories among Atlantic Forest conservation areas. This study describes the current composition of the medicinal plant knowledge, its taxonomic breadth, and its relevance for conservation. In 2026, this inventory documented 47 species from 33 botanical families cited across a sample of 4 remaining traditional healers. About 27.7% of these specimens are wild/native to nature and 72.3% are cultivated, reflecting both historic management and the residents’ long tradition in household plant acclimatization. The collection includes 25 species of herbs and 11 species of trees, as well as 9 shrubs and 2 climbers. Quantitative analysis at the category level revealed that gastrointestinal disorders had the highest consensus index (ICF = 0.375) after interviews, taxonomic revision, data grouping, and standardizing nomenclature based on the British National Formulary. The results reveal a severe risk of information erosion and a limited representation of younger generations among practitioners, underscoring the need for targeted safeguarding. Strengthening national partnerships, developing cooperative cultivation networks, and improving scientific validation records are proposed as key strategies to enhance the biocultural preservation value of this traditional heritage. Overall, the Ilha Grande healer knowledge serves as an important scientific, educational, and pharmacological resource and plays a central role in advancing the preservation of Brazil’s medicinal plant diversity. Full article

This study aims to accurately predict students’ academic performance trajectories for university entrance examinations by proposing a machine learning framework that explicitly accounts for missing data and uncertainty. Mock examination data are characterized by substantial missing values due to heterogeneous participation in exams, as well as inherent randomness caused by variations in test content and examinee conditions. Conventional single-value imputation methods cannot adequately reconstruct the missing values arising from such heterogeneous participation without introducing strong bias, and existing educational prediction models based on deterministic formulations do not account for the inherent randomness and uncertainty in examination scores, thereby limiting the reliability of their forecasts. To address these challenges, we employ GP-VAE and SAITS, state-of-the-art methods for time-series imputation, to reconstruct incomplete mock examination data. Furthermore, we develop a Bayesian Neural Network (BayesNN) to predict future academic performance while explicitly modeling uncertainty. By integrating temporally aware imputation with probabilistic prediction, the proposed framework aims to provide more accurate and reliable performance forecasts than existing approaches. We evaluate the effectiveness of the proposed method through comparative experiments involving various combinations of imputation techniques and prediction models. Experimental results demonstrate that the proposed framework achieves competitive predictive accuracy: the combination of deep imputation methods and BayesNN yields the lowest average estimation error of 15.98 points, compared with 16.75 points for the conventional combination of mean imputation and linear regression. The contribution of this study does not lie in proposing a new deep learning model itself, but rather in systematically comparing combinations of time-series imputation methods and uncertainty-aware prediction models using real-world mock examination sequence data with missing values, thereby providing effective design guidelines for educational data analysis. Full article

Background/Objectives: HIV testing is essential for early HIV diagnosis, timely treatment initiation, and HIV prevention. Despite Thailand’s long-standing HIV prevention programs and universal access to HIV testing services, nationally representative evidence on lifetime HIV testing among Thai adults remains limited. This study aimed to estimate the prevalence of lifetime HIV testing and identify factors associated with lifetime HIV testing among Thai adults. Methods: This study was a secondary analysis of data from the 6th Thai National Health Examination Survey. A total of 11,843 Thai adults aged 20–59 years were included. Descriptive statistics were used to estimate the prevalence of lifetime HIV testing. Survey-weighted logistic regression analyses were performed to examine factors associated with lifetime HIV testing. Results: The overall prevalence of lifetime HIV testing was 41.9%, with a prevalence of 42.4% among males, and 41.4% among females. Individuals aged 30–39 years (AOR = 1.64, 95% CI: 1.43–1.87) and 40–49 years (AOR = 1.67, 95% CI: 1.41–1.99), those with secondary education (AOR = 1.64, 95% CI: 1.43–1.87) or certificate/higher education (AOR = 1.74, 95% CI: 1.48–2.05), those currently living with a partner (AOR = 1.60, 95% CI: 1.43–1.79), participants with higher monthly income (10,000–24,999 THB: AOR = 1.13, 95% CI: 1.01–1.27; ≥25,000 THB: AOR = 1.39, 95% CI: 1.13–1.70), residents in the Northern region (AOR = 1.74, 95% CI: 1.45–2.09), and those who had a relative or acquaintance living with HIV/AIDS (AOR = 1.46, 95% CI: 1.34–1.59) were more likely to have lifetime HIV testing. In contrast, Muslim participants (AOR = 0.72, 95% CI: 0.57–0.90), residents of rural areas (AOR = 0.88, 95% CI: 0.79–0.97), residents in the Central (AOR = 0.82, 95% CI: 0.69–0.98) and Southern regions (AOR = 0.83, 95% CI: 0.72–0.94), and those with higher HIV-related stigma (AOR = 0.91, 95% CI: 0.84–0.99) were less likely to have lifetime HIV testing. Conclusions: Lifetime HIV testing among Thai adults remained suboptimal, with geographic and sociodemographic disparities. Full article

Technological progress in metrology provides new opportunities for enhancing the quality and transparency of metrological services, with the Digital Calibration Certificate (DCC) playing a significant role in this development. In contrast to traditional calibration certificates, the DCC enables the transfer of extended machine-readable data and can bring additional technical and metrological information describing the calibration process. This paper focuses on the use of DCC additional information for enhanced expression of calibration results in metrological practice and education. Using the example of pressure transducer calibration, the implementation of extended datasets within the DCC structure and their application in result evaluation are demonstrated, including analytical determination of measurement uncertainty and the application of the Monte Carlo method. The results confirm the contribution of DCC to more transparent interpretation of calibration results and to the support of professional education in metrology. Full article

Self-efficacy, a person’s belief in their capability to carry out a given task, shapes whether teachers attempt, persist with, and transfer new practices. Yet teachers’ perceived capability to use generative AI (GenAI) is often treated as a single general readiness rather than examined across the distinct domains in which it is now used. Guided by Bandura’s self-efficacy theory, this study provides a domain-differentiated account of GenAI competency self-efficacy among university teachers of English as a Foreign Language (EFL) in the Saudi higher-education context. A sample of 232 EFL teachers at Saudi public universities completed a contextually adapted version of the Generative AI Competency Self-Efficacy Scale for Teachers and Researchers (GAICS-TR). Data were analysed using repeated-measures analysis of variance, correlational analyses, and hierarchical multiple regression. Overall self-efficacy was only slightly above the scale midpoint, and the overall score concealed an uneven pattern across domains. Teachers felt most capable in Basic GenAI Understanding and Teaching with GenAI, less so in Professional Engagement, and least confident in Research with GenAI, with the lowest confidence reported for data analysis. Prior AI training and frequency of GenAI use were associated with overall self-efficacy, whereas teaching experience and academic rank were not. The findings suggest that overall measures of GenAI readiness can mask lower-confidence areas within specific domains, especially in research-facing uses such as data analysis. Accordingly, supporting teachers’ development in using GenAI calls for targeted, domain-sensitive professional development that reaches teachers at all career stages rather than broad familiarisation with the tools. Full article