Search Results (111)

This study provides a foundational review of work-based learning (WBL) opportunities offered by colleges and universities to students in higher education cybersecurity (CS) programs in the United States, with the goal of mapping the WBL practices across institutional and program contexts. Integrating WBL into CS curricula is widely recognized as an effective way to strengthen essential skills and address employer concerns about the gap between academic preparation and labor market needs. We first outline the characteristics of institutions and CS programs offering WBL. Next, we examine the range of WBL experiences designed to enhance students’ professional competencies. Finally, we explore characteristics of the partnerships between higher education and industry that support these initiatives. Using a status survey approach, we collected responses from 92 higher education institutions offering CS programs. We analyzed the data using descriptive statistics and linear regression models to explore patterns of association between the type and number of WBL opportunities available to students, institutional characteristics related to the total number of WBL offerings, and program features associated with WBL intensity across Awareness, Exploration, and Direct Experience levels of intensity. Findings reveal a diverse array of WBL opportunities, with notable growth across credential levels. Notably, certificates and associate degrees place particular emphasis on WBL. Both institutional characteristics and program features explain, albeit partially, the number of WBL opportunities implemented and the intensity levels of those WBL. However, results also indicate an ambivalent connection to employers, despite their critical role in providing hands-on, problem-solving experiences. Based on these insights, we recommend expanding WBL beyond internships, strengthening institutional–industry partnerships, and fostering employer engagement through structured WBL collaboration models. These strategies aim to improve workforce readiness and create a more inclusive, scalable system of experiential learning in cybersecurity education. Full article

As pharmacy career pathways diversify, professional doctoral programs such as PharmD face increasing pressure to demonstrate measurable workforce readiness outcomes within accreditation-constrained curricula. This study describes and evaluates PharmReaDy, a longitudinal, theory-informed workforce readiness platform embedded within a U.S. PharmD program. Guided by Tinto’s student retention framework, the platform integrates curricular, co-curricular, and experiential elements, including an industry-focused elective course, national professional competitions, targeted skills workshops, micro-credentialing opportunities, and experiential placements. Outcomes were assessed using enrollment trends, aggregate course evaluation data, academic performance indicators, and downstream participation in industry-aligned opportunities. Enrollment in the elective increased from 8 to 20 to 30 students across three offerings. Mean course evaluation scores across seven learning domains remained consistently high, ranging from 3.7 to 3.9 on a 4-point scale, with no statistically significant differences between cohorts (Welch’s t-tests, adjusted p > 0.05) and small positive effect sizes observed over time (Hedges’ g ≈ 0.20–0.29). Students demonstrated strong academic performance and increased participation in industry-focused competitions, scholarships, and post-graduate fellowship pathways. Findings from PharmReaDy indicate that workforce readiness can be meaningfully operationalized as a structured educational function embedded within professional curricula rather than being exclusively deferred to post-graduate training. Full article

Although pharmacist-led vaccination is a global standard for expanding immunization coverage, its adoption in Romania remains at an early stage. While previous studies have focused on early adopters, this research evaluates barriers, perceptions, and readiness among community pharmacies that do not yet provide this service, thereby addressing a critical knowledge gap regarding the “non-vaccinating” majority. A cross-sectional mixed-methods study was conducted among 208 pharmacists representing national chains, regional networks, and independent pharmacies. Quantitative data were analyzed using Chi-square tests and Spearman correlations to identify structural disparities, while a thematic analysis was employed to explore qualitative insights related to professional identity and operational barriers. We identified a clear mismatch between pharmacies’ willingness to provide vaccination services and their practical ability to implement them. Independent pharmacies demonstrated a strong intention to adopt vaccination services (71.4%) but were limited by financial constraints, with high implementation costs identified as a significant barrier (p = 0.014). In contrast, national pharmacy chains had sufficient resources yet faced marked staff resistance, with 43.9% reporting extreme reluctance (p = 0.038). These chains were concentrated in the capital region (p = 0.002), thereby positioning other pharmacies as key providers in underserved areas. Furthermore, thematic analysis revealed a deep-seated “professional identity” crisis, in which pharmacists struggle with the transition from medication specialists to clinical practitioners. The expansion of vaccination services cannot rely on a “one-size-fits-all” strategy. Successful national implementation requires a segmented policy approach, including financial subsidies to support independent pharmacies, change management strategies to engage the corporate workforce, and targeted regulatory education for regional networks to prevent vaccination deserts. Full article

The content and career cluster of agriculture, food, and natural resources (AFNR) provides opportunities for K-12 teachers to engage students to solve complex authentic problems that blend science, technology, engineering, and mathematics (STEM), yet limited research has been conducted on how to effectively leverage teaching and learning to integrate STEM using the context of AFNR through the school-based agricultural education program. This conceptual paper was developed through a collaborative sensemaking process focused on systems thinking as a way of knowing to integrate STEM within the contexts of AFNR, utilizing the SBAE program in the United States. A comprehensive career and technical education (CTE) program model of SBAE develops secondary education students’ career readiness skills through classroom and laboratory instruction, leadership development, and supervised agricultural experiences. The literature was reviewed to describe the current status of integrated STEM in SBAE, including learning by doing, solving real-world problems, application of content knowledge in out-of-school and community-based settings, learner-centered pedagogies, and development of career readiness skills for the workforce. By employing systems thinking as the theoretical framework and integrated STEM as a conceptual framework, the authors engaged in collaborative sensemaking of their professional and scholarly experiences and proposed findings and discussion of a three-model framework (i.e., teacher, program, and learning approach) to support integrated STEM education through AFNR and SBAE. Limitations of the framework are also discussed. The AFNR career cluster was used as the context to discuss how the three-model framework (i.e., teacher, program, and learning approach) of integrated STEM through AFNR could be operationalized for SBAE. Discussion and implications of the three-model framework for other career clusters in career and technical education (CTE) and non-formal education in community settings are presented. Conclusions and recommendations are provided for advancing STEM integration in SBAE for teacher development, program development, and research. Full article

Sustaining Ghana’s construction workforce requires more than expanding training as it requires integrating apprenticeships into a coherent skills system that links education, industry, and employability. This study tests how institutional integration, practical training, and industry collaboration jointly shape the effectiveness of apprenticeship training as a pathway to a sustainable construction workforce. Using survey data from 212 students, 36 instructors, and 129 industry and policy stakeholders, the study applies Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) to validate a latent construct of Effective Apprenticeship Strategies and quantify how its components explain training and workforce outcomes. A first-order measurement SEM was estimated to examine the causal relationships between the latent strategy construct and its observed indicators across the three respondent groups within a single analytical framework. The model shows strong construct validity (CFI = 0.904; RMSEA = 0.032) and reveals that structured workplace learning, institutional support, SME engagement, and technology-oriented training are the most influential components of effective apprenticeship integration, together explaining a substantial proportion of variance in apprenticeship quality and workforce readiness. The results further reveal a highly gender-polarised training pipeline (87.7% of students and 94.4% of instructors are male), indicating that current apprenticeship structures risk constraining Ghana’s future skilled labour supply and undermining long-term workforce sustainability. The study demonstrates that apprenticeship integration is not merely a training reform but a workforce sustainability mechanism. By empirically identifying which integration strategies matter most and showing how gender exclusion limits future labour capacity, the study provides a quantitative basis for redesigning Ghana’s apprenticeship system toward a more inclusive, industry-aligned, and sustainable construction workforce. Full article

Introduction: Nursing informatics aims to improve patient care through rapid access to patient data, systematic assessment, a reduction in clinical errors, evidence-based practice, cost-effectiveness, and improved patient outcomes and safety. Background: Despite being the largest workforce in healthcare, nurses are not being adequately prepared to use nursing informatics, and this has been attributed to poor digital literacy, limited professional development, and a lack of undergraduate informatics education. Objectives: This scoping review aims to review contemporary published literature on the benefits, barriers, and enablers for embedding nursing informatics into undergraduate nursing education with a focus on the Australian healthcare context. Methods: A scoping review was conducted using the PRISMA-ScR checklist and the JBI Manual for evidence synthesis in adherence with an a priori scoping review protocol. A comprehensive search of JBI, Cochrane, CINAHL, Ovid, ProQuest, PubMed, and Scopus databases was performed. Two reviewers independently screened the results via Covidence, with discrepancies resolved via a third reviewer. Results: Two searches were conducted for this scoping review. In the first search, a total of 3227 articles were identified through database searches, with an additional 76 articles identified through bibliographic and grey literature searches. Following duplicate removal and screening, 46 articles met the inclusion criteria. In the second search, a total of 1555 articles were identified, and after duplicate removal and screening, 16 articles met the inclusion criteria. Duplicate removal during the second search round included those articles identified in the first search. The combined searches resulted in a total of 62 sources for this review. Conclusions: Despite the early adoption of nursing informatics in Australia in the 1980s, barriers remain to effective nursing informatics engagement and proficiency, including a lack of understanding of nursing informatics, limited infrastructure and resources, inadequate digital literacy of students and faculty, and the evolving nature of nursing informatics. Definitions of nursing informatics and associated fields, development of university faculty competency, access to digital health technologies, competency standards, digital literacy of the student cohort, faculty digital proficiency, and leadership from professional nursing bodies are all viewed as integral foundations for the development of student competency in nursing informatics. Full article

This study provides new evidence on how production digitalization investment affects firm financial performance across diverse European regions. A panel of 14,935 firm-year observations from 30 countries (2012–2022), including a focused Baltic subsample, is used alongside a refined digital capital intensity metric based on depreciated plant and machinery value. The results indicate a positive association between digital investment and operating revenue across Europe, with significantly stronger effects observed in the Baltic region. Interaction models reveal higher marginal returns for Baltic firms, suggesting that digital capital delivers amplified value in economies with lower digital saturation but greater absorptive urgency. Employee-related costs consistently predict revenue outcomes, underscoring their role in translating digital assets into performance. Intangible fixed assets exhibit a positive impact in Baltic labor-scale models but weaker effects elsewhere, indicating that institutional maturity mediates knowledge capital productivity. Implications: (1) digital investment yields asymmetric returns; (2) workforce investment enhances digital ROI; and (3) policy should prioritize organizational readiness alongside infrastructure. This study contributes by introducing a replicable proxy for production-level digitalization and by providing rare comparative evidence on digital returns in transitional versus mature European economies. Full article

Frontline workers across health, emergency, and social care sectors are repeatedly exposed to distressing events and chronic stressors as part of their occupational roles. Unlike single-event trauma, these cumulative exposures accrue over time, generating persistent psychological and physiological strain. Traditional diagnostic frameworks, particularly post-traumatic stress disorder (PTSD), were not designed to capture the layered and ongoing nature of this occupational trauma. This commentary introduces the concept of Persistent Traumatic Stress Exposure (PTSE), a framework that reframes trauma among frontline workers as an exposure arising from organisational and systemic conditions rather than solely an individual disorder. It aims to reorient understanding, responsibility, and intervention from a purely clinical lens toward systems, cultures, and organisational duties of care. PTSE is presented as an integrative paradigm informed by contemporary theory and evidence on trauma, moral injury, organisational stress, and trauma-informed systems. The framework synthesises findings from health, emergency, and social care settings, illustrating how repeated exposure, ethical conflict, and institutional pressures contribute to cumulative psychological harm. PTSE highlights that psychological injury may build across shifts, careers, and lifetimes, requiring preventive, real-time, and sustained responses. The framework emphasises that effective support is dependent on both organisational readiness, the structural conditions that enable trauma-informed work, and organisational preparedness, the practical capability to enact safe, predictable, and stigma-free responses to trauma exposure. PTSE challenges prevailing stigma by framing trauma as a predictable occupational hazard rather than a personal weakness. It aligns with modern occupational health perspectives by advocating for systems that strengthen psychological safety, leadership capability and access to support. By adopting PTSE, organisations can shift from reactive treatment models toward proactive cultural and structural protection, honouring the lived realities of frontline workers and promoting long-term wellbeing and resilience. Full article

This comprehensive review synthesizes current advances and persistent challenges in integrating worker safety and food safety through human-robot collaboration (HRC) in poultry processing. Rapid industry expansion and rising consumer demand for ready-to-eat poultry products have heightened occupational risks and foodborne contamination concerns, necessitating holistic safety strategies. The review examines ergonomic, microbiological, and regulatory risks specific to poultry lines, and maps how state-of-the-art collaborative robots (“cobots”)—including power and force-limiting arms, adaptive soft grippers, machine vision, and biosensor integration—can support safer, more hygienic, and more productive operations. The authors analyze technical scientific literature (2018–2025) and real-world case studies, highlighting how automation (e.g., vision-guided deboning and intelligent sanitation) can reduce repetitive strain injuries, lower contamination rates, and improve production consistency. The review also addresses the psychological and sociocultural dimensions that affect workforce acceptance, as well as economic and regulatory barriers to adoption, particularly in small- and mid-sized plants. Key research gaps include gripper adaptability, validation of food safety outcomes in mixed human-cobot workflows, and the need for deeper workforce retraining and feedback mechanisms. The authors propose a multidisciplinary roadmap: harmonizing ergonomic, safety, and hygiene standards; developing adaptive food-grade robotic end-effectors; fostering explainable AI for process transparency; and advancing workforce education programs. Ultimately, successful HRC deployment in poultry processing will depend on continuous collaboration among industry, researchers, and regulatory authorities to ensure both safety and competitiveness in a rapidly evolving global food system. Full article

This study examines the relationship between national open educational resource (OER) policies and Sustainable Development Goal 4 (SDG4) outcomes across 187 countries between 2015 and 2024, with particular attention to the moderating role of artificial intelligence (AI) readiness. Despite widespread optimism about digital technologies as catalysts for universal education, systematic evidence linking formal OER policy frameworks to measurable improvements in educational access and completion remains limited. The analysis employs fixed effects and difference-in-differences estimation strategies using an unbalanced panel dataset comprising 435 country-year observations. The research investigates how OER policies associate with primary completion rates and out-of-school rates while testing whether these relationships depend on countries’ technological and institutional capacity for advanced technology deployment. The findings reveal that AI readiness demonstrates consistent positive associations with educational outcomes, with a ten-point increase in the readiness index corresponding to approximately 0.46 percentage point improvements in primary completion rates and 0.31 percentage point reductions in out-of-school rates across fixed effects specifications. The difference-in-differences analysis indicates that OER-adopting countries experienced completion rate increases averaging 0.52 percentage points relative to non-adopting countries in the post-2020 period, though this estimate remains statistically imprecise (p equals 0.440), preventing definitive causal conclusions. Interaction effects between policies and readiness yield consistently positive coefficients across specifications, but these associations similarly fail to achieve conventional significance thresholds given sample size constraints and limited within-country variation. While the directional patterns align with theoretical expectations that policy effectiveness depends on digital capacity, the evidence should be characterized as suggestive rather than conclusive. These findings represent preliminary assessment of policies in early implementation stages. Most frameworks were adopted between 2019 and 2022, providing observation windows of two to five years before data collection ended in 2024. This timeline proves insufficient for educational system transformations to fully materialize in aggregate indicators, as primary education cycles span six to eight years and implementation processes operate gradually through sequential stages of content development, teacher training, and institutional adaptation. The analysis captures policy impacts during formation rather than at equilibrium, establishing baseline patterns that require extended longitudinal observation for definitive evaluation. High-income countries demonstrate interaction coefficients between policies and readiness that approach marginal statistical significance (p less than 0.10), while low-income subsamples show coefficients near zero with wide confidence intervals. These patterns suggest that OER frameworks function as complementary interventions whose effectiveness depends critically on enabling infrastructure including digital connectivity, governance quality, technical workforce capacity, and innovation ecosystems. The results carry important implications for how countries sequence educational technology reforms and how international development organizations design technical assistance programs. The evidence cautions against uniform policy recommendations across diverse contexts, indicating that countries at different stages of digital development require fundamentally different strategies that coordinate policy adoption with foundational capacity building. However, the modest short-term effects and statistical imprecision observed here should not be interpreted as evidence of policy ineffectiveness, but rather as confirmation that immediate transformation is unlikely given implementation complexities and temporal constraints. The study contributes systematic cross-national evidence on aggregate policy associations while highlighting the conditional nature of educational technology effectiveness and establishing the need for continued longitudinal research as policies mature beyond the early implementation phase captured in this analysis. Full article

Background/Objectives: The integration of artificial intelligence (AI) into primary health care (PHC) holds significant potential to enhance efficiency, equity, and clinical decision-making. However, its implementation remains uneven across contexts. This study aimed to identify the systemic, contextual, and governance-related determinants influencing AI readiness in PHC, comparing two distinct health systems, Quebec (Canada) and Iran. Methods: A qualitative, comparative design was employed. Data were collected through semi-structured interviews and focus group discussions with key informants in both settings. A framework-guided content analysis was conducted based on the four Primary Care Evaluation Tool (PCET): stewardship, financing, resource generation, and service delivery. The analysis explored shared context-specific challenges and requirements for AI implementation in PHC. Results: Analysis revealed that AI readiness is shaped more by systemic coherence rather than technological availability alone. Across both contexts, governance- and financing-related challenges were reported by the majority of participants, alongside limited data interoperability. In Quebec, challenges were more commonly articulated around operational and ethical concerns, including workflow integration, transparency, and professional trust. In contrast, participants in Iran emphasized foundational deficiencies in governance stability, financing mechanisms, and digital infrastructure as primary barriers. Across both settings, adaptive governance, sustainable investment, data standardization, and workforce capacity-building consistently emerged as key requirements for AI integration in PHC. Conclusions: AI readiness in PHC is a multidimensional process, in which implementation priorities must align with system maturity. This comparative analysis underscores that while high-resource systems must prioritize ethical integration and workflow alignment, middle-resource settings require foundational investments in governance and infrastructure. This reinforces that AI readiness is a context-dependent and phased process rather than a one-size-fits-all endeavor. Full article

As cities pursue smarter, more resilient infrastructure, conventional contractor selection focuses narrowly on cost, which often neglects holistic sustainability. This study addresses a critical gap by introducing a novel, sustainability-oriented contractor evaluation model within Integrated Project Delivery (IPD). While IPD enables early collaboration, its integration with structured sustainability metrics remains underutilized. We develop a Multi-Criteria Decision-Making (MCDM) framework that operationalizes the three pillars of sustainability, economic, social, and environmental sustainability, with the inclusion of the technical pillar through an expanded environmental, social, and economic model incorporating sub-criteria such as constructability, workforce competence, collaborative readiness, etc. The innovative inclusion of technical sustainability deepens contractor assessment and enhances alignment with smart urban priorities. The model is embedded in a custom Decision Support System (DSS), combining Fuzzy AHP for weighting and Fuzzy VIKOR for ranking. A real-world IPD scenario, which is a proposed multi-purpose banquet facility, illustrates the tool’s functionality. Nine experts evaluated four contractors across 16 sub-criteria, with the results reflecting structured, priority-weighted decision logic. The DSS offers a transparent, replicable framework for aligning procurement with smart city goals. Its novelty lies in advancing sustainability through sustainability-oriented contractor selection, supporting policymakers, project teams, and cities in meeting integrated infrastructure objectives. Full article

As quantum technologies advance, there is growing international interest in integrating quantum concepts into secondary education. However, most K-12 quantum education studies rely on self-reported data or informal assessments lacking documented validity. This study aimed to address this gap by developing and validating the Quantum Literacy Test (QLt), a standardized instrument designed to objectively assess upper-secondary students’ understanding of foundational quantum concepts, practices, and perspectives. Grounded in the computational thinking (CT) framework, the QLt was piloted with 819 senior secondary school students in Nigeria and underwent a multi-phase validation process, including expert review, factor analysis, item-response modeling, differential item functioning analysis, and concurrent validity. The QLt demonstrated high internal consistency (α = 0.87) and structural validity. Strong concurrent validity was observed with the Computational Thinking Test (r = 0.65), and moderate validity was observed with a Spatial Ability Test (r = 0.32). However, machine learning models explained less than 40% of QLt score variance, suggesting the domain-specific nature of quantum literacy. We recommend future research to expand the QLt across diverse cultural contexts and to increase item coverage of quantum practices and perspectives. The QLt offers a valuable tool for evaluating curriculum effectiveness and monitoring equity in quantum education, thereby contributing to a more inclusive quantum-ready workforce. Full article

The accelerating integration of Artificial Intelligence (AI) in Industrial Automation has established Reinforcement Learning (RL) as a transformative paradigm for adaptive control, intelligent optimization, and autonomous decision-making in smart factories. Despite the growing literature, existing reviews often emphasize algorithmic performance or domain-specific applications, neglecting broader links between methodological evolution, technological maturity, and industrial readiness. To address this gap, this study presents a bibliometric review mapping the development of RL and Deep Reinforcement Learning (DRL) research in Industrial Automation and robotics. Following the PRISMA 2020 protocol to guide the data collection procedures and inclusion criteria, 672 peer-reviewed journal articles published between 2017 and 2026 were retrieved from Scopus, ensuring high-quality, interdisciplinary coverage. Quantitative bibliometric analyses were conducted in R using Bibliometrix and Biblioshiny, including co-authorship, co-citation, keyword co-occurrence, and thematic network analyses, to reveal collaboration patterns, influential works, and emerging research trends. Results indicate that 42% of studies employed DRL, 27% focused on Multi-Agent RL (MARL), and 31% relied on classical RL, with applications concentrated in robotic control (33%), process optimization (28%), and predictive maintenance (19%). However, only 22% of the studies reported real-world or pilot implementations, highlighting persistent challenges in scalability, safety validation, interpretability, and deployment readiness. By integrating a review with bibliometric mapping, this study provides a comprehensive taxonomy and a strategic roadmap linking theoretical RL research with practical industrial applications. This roadmap is structured across four critical dimensions: (1) Algorithmic Development (e.g., safe, explainable, and data-efficient RL), (2) Integration Technologies (e.g., digital twins and IoT), (3) Validation Maturity (from simulation to real-world pilots), and (4) Human-Centricity (addressing trust, collaboration, and workforce transition). These insights can guide researchers, engineers, and policymakers in developing scalable, safe, and human-centric RL solutions, prioritizing research directions, and informing the implementation of Industry 5.0–aligned intelligent automation systems emphasizing transparency, sustainability, and operational resilience. Full article

Background: The transition from student to registered nurse is a vulnerable period characterised by emotional strain, role ambiguity, and transition shock. Although Graduate Nurse Transition Programs (GNTPs) aim to strengthen early practice readiness, few evaluations use longitudinal, theory-informed approaches or validated tools. Aim: To examine the professional role development of new graduate nurses (NGNs) across three transition stages within a major Australian health service. Design and Methods: A longitudinal quantitative study guided by Duchscher’s Stages of Transition Theory and the Transition Shock Model. A customised 75-item questionnaire—adapted from the Professional Role Transition Risk Assessment Instrument and the Professional and Graduate Capability Framework—was administered at three transition points (March 2020–March 2021). Four domains were assessed: Responsibilities, Role Orientation, Relationships, and Knowledge and Confidence. Descriptive statistics, Principal Component Analysis (PCA), chi-square tests, and multinomial logistic regression identified developmental patterns and predictors of transition stage. Results: PCA supported a four-factor structure consistent with the theoretical domains, explaining 62% of variance. Significant stage-based improvements were found in clinical decision-making (RS6, p = 0.005), managing pressure (RS11, p = 0.003), leadership perception (RO5, p = 0.001), and emotional regulation (RL20, p < 0.001). Regression analysis identified role confusion (RS7, χ² = 18.112, p = 0.001), leadership potential (RL1, χ² = 25.590, p < 0.001), workplace support (RL16, χ² = 12.760, p = 0.013), and critical thinking confidence (KN13, χ² = 10.858, p = 0.028) as strong predictors of transition stage. By Stage 3, most NGNs demonstrated increased autonomy, confidence, and professional integration. A coordinator-to-graduate ratio of 1:12 facilitated personalised mentorship. Conclusions: Findings provide robust evidence for theoretically grounded GNTPs. Tailored interventions—such as early mentorship, mid-stage stress support, and late-stage leadership development—can enhance role clarity, confidence, and workforce sustainability. Full article