Search Results (17,099)

Aligning information technology (IT) workforce demands with educational assessments is essential for bridging skills gaps; yet, no prior corpus maps IT task reasoning to Programme for International Student Assessment (PISA) proficiency levels. This paper introduces a large language model (LLM)-powered framework aligning IT competencies with PISA 2022 and the OECD (Organisation for Economic Co-operation and Development) Learning Compass 2030, drawing on O*NET v30.2 (Occupational Information Network), ESCO (European Skills, Competences, Qualifications, and Occupations) v1.2.1, PISA descriptors and OECD definitions. The framework operates in two stages: Stage 1 aligns 562 IT task statements with minimum PISA 2022 proficiency levels via LLM annotation and cross-model validation; and Stage 2 extends this mapping to the OECD Learning Compass 2030 through the semantic clustering of task embeddings and a bidirectional gap analysis of 95 ESCO transversal skills. Using Gemini 2.5 Flash, 562 tasks are annotated with minimum PISA levels across Mathematical, Reading, and Science literacy (first stage). Annotation reliability is assessed through a five-model cross-validation against a blind human domain expert (treated as a reference benchmark, not a gold standard) on a stratified 100-task sample (17.8% of the corpus), with agreement ranging from fair (Gemini 2.5 Flash, κ = 0.29) to moderate (Claude Haiku 4.5, κ = 0.50; LLaMA 3.3 70B, κ = 0.44). A bias-correction sensitivity analysis confirms that distributional findings remain stable after accounting for the primary annotator’s systematic overestimation, and OLS-calibrated alignment against O*NET ability ratings provides directional plausibility support. Validated tasks are embedded and clustered into 25 technical profiles via K-Means, each classified against OECD dimensions. The framework is extended to 95 ESCO transversal skills in 24 clusters. Bidirectional analysis reveals that, while every PISA proficiency level is engaged by at least one transversal cluster, 33% of these clusters, covering creative, ethical, social–emotional, and dispositional competencies, fall entirely outside PISA’s cognitive scope. This boundary mapping identifies where the PISA-based alignment is valid and where complementary tools are required for a full readiness assessment. Full article

As the first generation in their families to pursue higher education, the mental health of first-generation college students has attracted significant attention from the academic community. Self-esteem and academic performance are significant factors influencing anxiety and mental health among first-generation college students. However, longitudinal research evidence specific to this group in China remains scarce. This study utilized two waves data, selecting a sample of 1024 first-generation college students (mean age 21.73; 55.18% male). Through follow-up surveys conducted at one-year intervals, a cross-lagged model was employed to systematically examine the longitudinal predictive relationships among self-esteem, academic performance, and anxiety. The results indicate significant negative correlations among self-esteem, academic performance, and anxiety. Cross-lagged analysis further indicated that self-esteem at T1 (β = −0.098, p < 0.05) and academic performance at T1 (β = −0.067, p < 0.05) were prospectively associated with lower anxiety at T2. This study reveals the longitudinal predictive associations among self-esteem, academic performance, and anxiety among China’s first-generation college students, providing empirical evidence for universities to improve their mental health support systems by focusing on the self-esteem development of this group and offering targeted academic support. Full article

The rapid integration of artificial intelligence (AI) technologies into educational contexts has introduced innovative instructional approaches, particularly within Science, Technology, Engineering, and Mathematics (STEM) education. Although an increasing number of empirical studies have examined AI-supported instruction, existing findings remain heterogeneous, making it difficult to draw firm conclusions about its overall effectiveness. This study aims to systematically synthesize experimental and quasi-experimental research on AI-supported instructional interventions in STEM education, quantify their overall effects on student learning outcomes, and examine potential moderating factors, including educational level, STEM discipline, and intervention duration. A comprehensive systematic literature search was conducted across Web of Science, Scopus, ERIC, ScienceDirect, and Google Scholar, covering studies published between 2005 and 2025. A total of 35 studies meeting predefined inclusion criteria were included in the meta-analysis. Effect sizes were calculated using Hedges’ g, and a Random Effects Model (REM) was employed to account for heterogeneity among studies. Moderator analyses were conducted for educational level, STEM discipline, and intervention duration. Publication bias was assessed using multiple diagnostic methods. The meta-analysis revealed a statistically significant overall positive effect of AI-supported instruction on student learning outcomes in STEM education (g = 0.67, 95% CI [0.49, 0.85], p < 0.001). Moderator analyses indicated that AI interventions were most effective at the high school level. Although Science and Mathematics disciplines showed slightly higher effect sizes, the between-group difference was not statistically significant (Q = 4.85, df = 2, p = 0.088). Regarding intervention duration, the highest effect size was observed in interventions lasting more than one month and up to two months, though no consistent pattern of increasing effectiveness with longer durations was found. Publication bias analyses suggested minimal influence on the overall findings. AI-supported instructional interventions demonstrate a moderately to highly positive impact on student learning outcomes in STEM education. The effectiveness of these interventions varies according to educational level, disciplinary context, and intervention duration. These findings provide robust empirical evidence supporting the pedagogical value of AI in STEM education and offer guidance for educators and policymakers regarding effective implementation. Full article

Background/Objectives: Adequate micronutrient intake during pregnancy is critical for fetal development, yet whether pregnant women and healthcare professionals share consistent knowledge, beliefs, and supplementation practices remains poorly characterized. Methods: Two parallel cross-sectional surveys using identical core items were conducted at a German tertiary care center between April and November 2024. Pregnant women (n = 132) and healthcare professionals who initiated the survey (n = 105) completed anonymous QR-code-based questionnaires assessing micronutrient-related knowledge, perceived dietary adequacy, and supplementation practices or recommendation patterns. Comparative analyses were restricted to fully completed healthcare professional questionnaires (n = 80). Group differences were analyzed using chi-square or Fisher’s exact tests. Results: Healthcare professionals demonstrated higher knowledge levels across most micronutrients. Knowledge gaps were most pronounced for vitamin B12, with 53.0% of pregnant women unable to identify any fetal effect compared with 20.0% of providers (p < 0.001). Beliefs about dietary sufficiency were broadly aligned for folic acid (p = 0.452) and vitamin D (p > 0.999), but diverged markedly for vitamin B12, where 79.2% of providers considered dietary intake alone adequate compared with 47.3% of pregnant women (p < 0.001). Substantial differences were observed between patient-reported supplementation practices and provider-reported recommendation patterns: Vitamin B12 (70.0% vs. 3.8%), vitamin D (76.2% vs. 41.3%), omega-3 fatty acids (76.2% vs. 47.5%), and folic acid (98.5% vs. 81.3%; all p < 0.001). The internet was the most frequently cited information source among pregnant women (89.4%), while healthcare professionals reported using both scientific literature (75.0%) and internet-based resources (76.3%), the latter primarily for accessing professional and scientific information. Conclusions: Substantial patient–provider differences in micronutrient knowledge, beliefs, and supplementation practices persist even within a highly educated population at a tertiary care center. These findings suggest potential differences between patient-reported supplementation behavior and provider-reported recommendation practices, particularly for vitamin B12 and vitamin D. These findings suggest that more structured communication regarding micronutrient supplementation during pregnancy is needed. Full article

Social media platforms increasingly function as informal education systems for programming learning, yet the systemic support structures these environments provide remain poorly understood. We analyzed 40,004 comments from programming tutorial videos on a major social media platform (2016–April 2025) to identify patterns of learner support needs at scale. Using BERTopic, we identified twelve discussion themes. We then consolidated these themes into a learner-needs typology based on their dominant support functions: instructional-oriented needs, operational support needs, and knowledge-constructionneeds. We mapped this typology onto the Community of Inquiry (CoI) framework to assess its explanatory coverage. This mapping revealed a critical systemic gap. Operational support needs, covering environment configuration, tool integration, dependency management, and technical troubleshooting, constituted the largest category (44.53% of theme-level discourse), exceeding both knowledge-construction needs (28.42%) and instructional-oriented needs (26.95%). Learners repeatedly described these infrastructure-level challenges as disrupting their attempts to engage with content, execute code for testing ideas, and coordinate with peers, yet these operational readiness needs are not fully specified by CoI’s traditional presences. Social presence did not emerge as a standalone theme at the topic-modeling level; rather, social cues were often embedded within task-oriented troubleshooting. Based on these findings, we propose Technical Presence as a context-sensitive extension to the CoI framework, defined as the extent to which a learning community enables operational readiness through accessible infrastructure support and collaborative troubleshooting. As an infrastructural support condition, Technical Presence supports operational readiness within tool-dependent, practice-based learning: when learners report infrastructure failure, the conditions for enacting instructional design, cognitive inquiry, and peer collaboration are correspondingly weakened. These findings carry implications for content creators, platform developers, and education system designers seeking to strengthen the infrastructural foundations of technology-enhanced learning at scale. Full article

While reading habits strongly correlate with academic success, empirical data regarding higher education (HE) literacy in Portugal remains scarce, particularly across the private sector. This study addresses this gap through a cross-institutional analysis comparing public and private HEIs alongside the island regions of Madeira and the Azores, challenging the assumption that digital natives universally reject print. A survey was administered to 558 students across 140 study cycles from 33 public and private HEIs, with data evaluated via non-parametric inferential methodologies. The sample displayed high reading appreciation, yielding a mean enjoyment score of 7.54 out of 10 (SD = 2.29) and an annual median of 4 books. Significant demographic variations (p < 0.05) emerged: female and older (23+) students demonstrated a significantly higher love of reading and voluntary book consumption, whereas males and younger cohorts gravitated toward technical texts and digital periodicals. Conversely, groups converged regarding internet usage and the primary structural barrier to literacy: an acute lack of time (67.9%). Crucially, while HEI type did not impact genre or platform choices, public university students reported significantly higher reading enjoyment and read more books annually than their private-sector peers (p < 0.05). These findings underscore that individual literacy is actively moderated by institutional micro-climates, providing administrators with precise empirical targets to design tailored reading initiatives. Full article

Despite a large number of African-born individuals residing in the United States, there is a significant disparity in how this community accesses and utilizes mental health treatment. Low screening rates for common mental health concerns is one crucial part of ongoing inequities in mental healthcare access. Willingness to engage in screening is negatively impacted by a lack of culturally responsive ways to make screening more acceptable and stigma with mental health. This study therefore aimed to examine the perceived acceptability and utility of community-developed patient vignettes created to increase willingness to be screened for common mental health concerns. Employing a qualitative approach, a community advisory board (CAB) (n = 5) was enlisted to co-develop vignettes outlining an African community member’s symptoms of anxiety and subsequent help-seeking behavior. Two focus groups of community members (n = 18) provided qualitative feedback on the vignettes and shared their general attitudes towards mental health and recommendations for mental health screening and treatment in the African community. Using a hybrid inductive and deductive qualitative descriptive approach and classifying responses based on the socioecological model, four major themes emerged from the data: (1) between support and strain: the role of family; (2) reducing stigma: community voices as education; (3) culture as a barrier and a bridge; and (4) the importance of stories that reflect lived experience. Overall, participants were receptive to the culturally-responsive mental health vignettes and provided fruitful suggestions for how these stories can be used to reduce stigma and increase willingness to seek screening and treatment in African-born residents of the United States. Full article

Introduction: Remote education is increasingly used in ostomy care, but its components, timing, governance, and evaluation remain inconsistently defined. This study aimed to develop practice-oriented recommendations for implementing remote patient education for people living with an ostomy. Methods: An Italian expert consensus using a modified Delphi method and reported according to the ACCORD guidelines was conducted. An expert panel (n = 11), recruited nationally, included stomatherapists (n = 6) and people living with an ostomy (n = 5). Round 1 comprised a remotely conducted focus group to generate and refine statements informed by a targeted literature search. Rounds 2 and 3 were anonymous online surveys in which panelists rated statements on a four-point Likert scale and could provide comments or propose additional items. Consensus was predefined as ≥75% agreement. Results: Response rates were 100% across the three rounds (October–November 2025). The panel achieved consensus on 8 definitions and 14 statements, organized into six domains: (1) model of care and eligibility; (2) privacy and data protection; (3) program structure, outcomes, and evaluation; (4) educational content and teaching strategies; (5) timing, intensity, follow-up, and caregiver involvement; and (6) dignity, relational quality, and professional and organizational requirements. Recommendations supported a hybrid-by-default model with eligibility criteria, privacy-by-design using secure platforms and traceable documentation, structured programs with tailored multimodal content, staged pathways lasting 2–6 months after an initial in-person foundation, dignity-preserving options during remote encounters, professional training in communication and digital empathy, and integration into clinical planning and records. Conclusions: This consensus provides the first ostomy-specific, implementation-focused recommendations for standardizing remote patient education in Italy, with an emphasis on equity, privacy, dignity, evaluation, and workforce competencies. Full article

Universities serve as catalysts for knowledge creation across territories, promoting innovation and economic development through different channels. This paper investigates the role of university graduates as a location determinant of new green-tech-based firms (NGTBFs) across Italian NUTS-3 regions over the period 2011–2017. We examine whether universities, as providers of high-skilled human capital, affect the spatial distribution of new green ventures. Adopting a patent-based definition of NGTBFs and an econometric framework accounting for regional heterogeneity, we analyse the impact of university graduates on green firm creation. The results show that higher education fosters green entrepreneurship primarily through the channel of producing doctoral and STEM-oriented graduates, who serve as key drivers of NGTBF formation. Interestingly, the analysis reveals marked spatial heterogeneity across Italy’s North–South divide, with stronger associations of PhD and STEM graduates in Southern regions, where specialised human capital appears to compensate for weaker innovation systems. These findings deliver clear policy implications, suggesting that strategies aimed at promoting green entrepreneurship should prioritise advanced, STEM-oriented human capital and explicitly account for regional contexts, rather than relying on uniform higher education expansion approaches. Full article

Food waste research often applies the Motivation–Opportunity–Ability (MOA) framework, yet conventional aggregate measures may obscure the distinct roles of physical context and cognition-related capacity. Using a macro-contextual, micro-primary dual-layer design, this study first uses World Bank data from 176 countries to provide structural context; this macro layer is not statistically linked to the student-level model. The main behavioral inference comes from matched plate-weighing and questionnaire data from 170 students across two purposively selected ordinary higher education institutions in northern and southern China. Within this exploratory and context-specific micro-level sample, the baseline three-dimensional MOA model explains only 4.1% of variance in log-transformed plate waste, whereas decomposing Opportunity into social and physical components and representing the Ability extension through behavioral ability and a two-item cognitive-capacity proxy improves model fit. The five-dimensional model explains 44.1% of variance ($F=26.2$, $p<0.001$). Johnson relative weight analysis indicates that Physical Opportunity (51.1%) and the two-item cognitive-capacity proxy (46.3%) account for most explained MOA variance in this sample. Item-level sensitivity checks further suggest that portion estimation and nutrition knowledge should be interpreted as distinct cognition-related indicators rather than as a validated latent scale. Robustness checks across raw, log-transformed, winsorized, logistic, and quantile specifications indicate consistent positive associations for Physical Opportunity and consistent negative associations for cognition-related indicators. Because the design is cross-sectional, these findings identify associations rather than causal effects; physical-environment redesign and cognitive-capacity support should therefore be treated as candidate directions for future intervention testing rather than as confirmed intervention effects. By linking objectively measured plate waste to institutional dining conditions, the study contributes to sustainability research on responsible consumption, resource efficiency, low-carbon campus operations, and practical pathways for reducing avoidable food-related environmental burdens in university settings. Full article

This article examines the medium to long-term enrollment patterns of an AI-based platform designed to support children in learning robotics and participating in a national robotics competition in Romania. Drawing on registration and participation data covering students and teachers across urban and rural schools between 2020 and 2025, the study documents a consistent pattern: an initial period of high enrollment and rapid adoption followed by a steady decline over time. A key feature of the initiative is that hardware, platform access, and learning resources were provided entirely free of charge, allowing cost-related explanations for the decline to be set aside and structural and human factors to be examined directly. The paper makes two primary contributions. First, it proposes a System Dynamics framework grounded in innovation diffusion theory as a first-generation calibration model for understanding AI-enabled educational robotics adoption in a resource-constrained national context. The model is designed to be progressively tested and refined as anonymized aggregate data accumulates, and it relies exclusively on anonymized aggregated public data in accordance with GDPR requirements. Second, it advances the hypothesis that an AI-based educational platform, even one from which all financial barriers have been removed, will experience sustained enrollment decline in the absence of adequate human teacher involvement. The empirical trajectory and model outputs are consistent with this hypothesis and motivate further investigation. This represents a hypothesis-generating and framework-building paper. The framework reveals pronounced urban-rural disparities and differential outcomes by age of entry. All findings are presented as model-generated hypotheses rather than empirically demonstrated conclusions. The paper invites researchers gathering comparable data from similar initiatives in other countries to collaborate in testing and refining the model. The central conclusion is cautiously optimistic: AI may support robotics education adoption, but it is not a substitute for dedicated teachers, and without sustained investment in human capital, even a financially accessible platform is insufficient to maintain long-term enrollments. Full article

Crab traps are commonly used tools in both commercial and recreational fisheries to capture crabs through baited enclosures. However, the existing conventional designs often suffer from reduced catch efficiency, high bycatch rates, and rapid bait deterioration, which undermine their effectiveness and environmental sustainability. This study evaluated the effectiveness of an innovative crab trap setup incorporating an attractor device, designed not only to enhance crab catch rates but also to serve as a localized laboratory simulator for Outcome-Based Education (OBE) in Industrial Arts. Utilizing a developmental research design, this study was conducted in Barangay Caloc-an, Magallanes, Agusan del Norte. The research involved commercial and recreational crab fishermen, as well as electrical and electronics experts, to assist in setting up and evaluating the innovative crab trap device. The key variables examined included the type of attractor device used, the dispersal rate of the liquid bait, and the trap’s overall effectiveness in capturing crabs. Four different bait dispersal intervals were tested: 40 min, 30 min, 10 min, and 30 s. Results showed that shorter dispersal intervals significantly increased catch rates, with the 30 s interval yielding the highest and most consistent results. The developmental research framework enabled iterative testing and refinement of the trap system, allowing for continuous improvement of its components. Importantly, this study’s broader educational aim was to provide students with a practical, culturally relevant, and outcome-focused learning experience, where technical skills and scientific inquiry are applied in real-world contexts. The crab trap device served not only as a fishing tool but also as a simulated laboratory apparatus for Industrial Arts instruction, fostering skill development and engagement. Overall, this study contributes valuable insights into both fisheries management and educational innovation, demonstrating that a well-designed crab trap device can support more effective and sustainable fishing practices while also enhancing Industrial Arts education through hands-on, localized learning experiences. Full article

This paper examines how artificial intelligence can support sustainability assessment in cultural industries, using national film industries as a test case. The Film Industry Sustainability Index (FISI) is introduced as a composite indicator covering cultural diversity, economic resilience, and Sustainable Development Goal (SDG) alignment for 42 national economies from 2005 to 2023. Knowledge-Enhanced Mamba (KE-Mamba), a selective state-space forecasting model, is then proposed to combine annual panel indicators with country-level film-industry knowledge graph (KG) embeddings and large language model (LLM)-derived screenplay-oriented narrative proxies from film synopses. To reduce factual errors in title-level narrative scoring, the LLM is anchored to verified United Nations Educational, Scientific and Cultural Organization (UNESCO) records and the European Audiovisual Observatory’s LUMIERE film-admissions database using rank-one model editing (ROME). On the 2020–2023 held-out test period, KE-Mamba achieves a composite FISI mean absolute error (MAE) of 0.0389, a mean absolute percentage error (MAPE) of 5.61%, and an $R^2$ of 0.934, outperforming autoregressive integrated moving average (ARIMA), tree-based, long short-term memory (LSTM), and base Mamba baselines. Additional robustness checks using a pre-pandemic split, two-way fixed-effects panel regression, alternative FISI weighting schemes, KG embedding ablations, and human validation of LLM narrative scores support the reliability of the proposed framework. Policy simulations are interpreted as model-based projected associations rather than causal estimates. The results show that knowledge-enhanced sequence models can provide transparent forecasting support for sustainable cultural-industry policy. Full article

Background: The nationally advertised mass media campaign Act-FAST UK, delivered in multiple waves since its launch in 2009, has increased public awareness of stroke symptoms. However, many stroke patients still delay in calling for help and reach the hospital too late to receive emergency treatments. The reasons for this cognitive dissonance between recognition of symptoms and urgent seeking of emergency medical services (EMS) are unclear. Aims: This study aimed to quantify cognitive, psychological, and knowledge-based barriers to help-seeking in patients with acute stroke or transient ischaemic attack (TIA), as well as in intervening witnesses, and to examine their association with the use of EMS as the initial point of contact. Methods: We interviewed patients admitted to a hyperacute stroke unit with a stroke or transient ischaemic attack (TIA) from 2013 to 2016. People who contacted emergency services on the patient’s behalf (intervening witnesses (IWs)) were also interviewed when available. Reasons given for delays in calling for help were related to correct symptom recognition, and whether/at what time, emergency services were contacted after symptoms onset. Results: A total of 602 patients (429 with stroke, 173 with TIA) along with 128 witnesses who intervened in calling for help in those cases (IWs) were interviewed. In the subset of patients with both measures available, there was a strong positive correlation between NIHSS score and number of FAST symptoms (Spearman’s rho = 0.645, p < 0.001), providing supportive evidence for the use of FAST symptom count as a proxy measure of stroke severity. A total of 469 (77.9%) of the patients were aware of a media education campaign about stroke, but only 145 (24.1%) had attributed their own symptoms to stroke at onset. However, correct self-diagnosis of stroke was not associated with direct calls to the EMS (OR 1.43, 95% CI 0.84–2.45). Cognitive, psychological or emotional barriers to help-seeking, as reported by prior published studies, were reported by 463 (81.2%) of the patients we interviewed but in only 63 (53.3%) of the IWs (p < 0.001). Amongst the patient cohort, “not thinking symptoms were serious” (275, 45.7%) and “waiting to see if symptoms would go away” (285, 47.3%) were most strongly negatively associated with EMS use (OR 0.52, 95% CI 0.32–0.84 and OR 0.34, 95% CI 0.21–0.55, respectively). Only 55 (9.1%) of the patients interviewed had been aware of any time-critical stroke treatment prior to their stroke. Eighteen stroke patients (4.2%) reached hospital in time to receive thrombolysis, but an additional 170 (39%) could have been considered for this treatment (i.e., had no apparent other contraindications from a notes review) had they arrived within 4 h of symptom onset. Conclusions: Future public education campaigns may be more effective if they specifically address factors associated with delays in calling for help after stroke symptoms and emphasise the existence of emergency treatments, which are also time-critical. More effective public education may have the potential to increase the proportion of patients arriving in time to benefit from such treatments. Full article

Faculty governance in higher education depends on transparent participation, reliable quorum enforcement, accountable record keeping, and strict alignment with institutional regulations. Conventional departmental council processes provide formal authority and academic deliberation, but they often rely on manual documentation, fragmented records, and procedural enforcement that is difficult to verify after the fact. This work presents an integrated hybrid Decentralized Autonomous Organization (DAO) framework for faculty governance that combines regulatory alignment analysis, a working smart-contract prototype, and scenario-based simulation. The framework is designed for university departmental councils and is structured across three layers: off-chain community governance, on-chain protocol governance, and off-chain execution governance. It expands prior conceptual work by incorporating governance dimensions related to roles, incentives, membership, communication, decision-making, identity, auditability, conflict-of-interest handling, and institutional ratification. The evaluation simulates 1488 proposals across twelve scenarios covering four faculty sizes (15, 30, 50, and 100 members) and three adoption levels (low, moderate, and high). Scenario results indicate that adoption intensity is the dominant driver of governance performance: mean participation increases from about 33% under low usage to about 85% under high usage, quorum achievement rises from about 6% to about 96%, and execution rises from about 19% to about 70%. Relative to a modeled conventional workflow baseline, the DAO-supported process reduces decision-cycle time by about 76%, improves audit completeness by about 30%, and increases traceability from about 0.63 to 1.00. The results indicate that DAO-assisted faculty governance can strengthen transparency, procedural consistency, and auditability while preserving legally mandated university authority, but its practical value depends on sustained participation, privacy safeguards, cost control, and clearly defined hybrid control points. Full article