Search Results (4,563)

Background: The digitization of health records was expected to improve data quality and accessibility, yet incompleteness remains a widespread challenge that undermines clinical care, interoperability, and downstream analytics. Problem: Evidence shows that missing and under-recorded elements in electronic health records (EHRs) are largely driven by process gaps across patients, providers, technology, and policy—not solely by technical limitations. Objective: This perspective integrates conceptual foundations of incompleteness, synthesizes cross-country evidence, and examines process-level drivers and consequences, with an emphasis on how missingness propagates bias in AI and machine learning systems. Contribution: We present a unifying taxonomy, highlight complementary approaches (e.g., Record Strength Score, distributional testing, and workflow studies), and we propose a pragmatic agenda for mitigation through technical, organizational, governance, and patient-centered levers. Conclusions: While EHR incompleteness cannot be fully eliminated, it can be systematically mitigated through standards, workflow redesign, patient engagement, and governance—essential steps toward building safe, equitable, and effective learning health systems. Full article

Providing equitable, high-quality education to all children, including those with intellectual disabilities (ID), remains a critical global challenge. Traditional learning environments often fail to address the unique cognitive needs of children with mild and moderate ID. In response, this study explores the potential of tablet-based game applications to enhance educational outcomes through an interactive, engaging, and accessible digital platform. The proposed solution, GrowMore, is a tablet-based educational game specifically designed for children aged 8 to 12 with mild intellectual disabilities. The application integrates adaptive learning strategies, vibrant visuals, and interactive feedback mechanisms to foster improvements in object recognition, color identification, and counting skills. Additionally, the system supports cognitive rehabilitation by enhancing attention, working memory, and problem-solving abilities, which caregivers reported transferring to daily functional tasks. The system’s usability was rigorously evaluated using quality standards, focusing on effectiveness, efficiency, and user satisfaction. Experimental results demonstrate that approximately 88% of participants were able to correctly identify learning elements after engaging with the application, with notable improvements in attention span and learning retention. Informal interviews with parents further validated the positive cognitive, behavioral, and rehabilitative impact of the application. These findings underscore the value of digital game-based learning tools in special education and highlight the need for continued development of inclusive educational technologies. Full article

The achievement of sustainability goals depends on local actions, highlighting the need for educational approaches that engage learners with locally relevant content within Education for Sustainable Development. This study used a mixed-methods approach to examine the suitability of location-based mobile learning to highlight the local relevance of sustainability issues and explore its potential and challenges in the context of Education for Sustainable Development. For this purpose, a location-based mobile learning unit on climate change adaptation on the BIPARCOURS app was completed by 63 pre-service teachers, who answered a questionnaire before and after the unit to capture their experiences, perceived learning outcomes, and attitudes, also including an evaluation of the unit. The results indicated that the unit enhanced participants’ awareness of individual and everyday opportunities for climate change adaptation. In the evaluation, the pre-service teachers cited the following factors for the successful use of location-based mobile learning: increased motivation, real-world relevance, the connection between local examples and theoretical knowledge, and the development of digital skills. Critical remarks were made regarding technical and organisational aspects. Although the unit’s generalisability and long-term impact require further investigation, the results point to the potential of location-based mobile learning to support Education for Sustainable Development. Full article

The introduction of large language models (LLMs) has significantly influenced learning and learning assessments, dividing the academic community with arguments for and against their implementation. This study investigates how LLMs can be effectively incorporated into student assignments on sustainable development in local communities. In that regard, the study pairs traditional, community-oriented tasks with emerging frameworks for structured LLM use, emphasizing that output quality depends on prompt quality. Accordingly, several prompting frameworks were outlined, and the suitability of ChatGPT and Gemini for specific assignment tasks was assessed. The effectiveness of the approach was evaluated with a survey of two student groups: one using supervised LLM support (23 students) and another using LLMs independently (17 students). Compared to the unsupervised group, the supervised group reported that the frameworks enhanced project preparedness, fostered critical thinking, and reduced reliance on mentors. The supervising mentor noted a slightly lower workload than in earlier projects, while the mentor of the unsupervised group reported higher effort in guiding and refining outcomes. Overall, the findings suggest that guided LLM integration has the potential to improve learning, deepen critical engagement, foster independence, and reduce mentor workload when compared to those who do not provide structured guidance in LLM use. Full article

This study focuses on the adaptation and psychometric validation of the Spanish versions of the Agentic Engagement Scale (AES) and the Enlarged Version of the Agentic Engagement Scale (EVAES) in Spanish undergraduate students. Agentic engagement, denoting the educational insights provided by students during classroom instruction, has garnered attention for its potential impact on teaching and learning. Reeve initially developed the AES in 2013, which Mameli and Passini extended from 5 to 10 items in 2019 to create the EVAES. In a sample of 278 undergraduate students, this study thoroughly examined various psychometric properties, including item response distribution, factor structure, internal consistency, test–retest reliability, and validity evidence. The results consistently demonstrated high item-total correlations, a one-factor structure, good internal consistency, and satisfactory test–retest reliability for both scales. Additionally, the study established validity evidence through positive and significant correlations between agentic engagement and academic engagement, as well as with personality traits such as extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience. In conclusion, the Spanish versions of the AES and EVAES emerge as promising tools for assessing agentic engagement among Spanish-speaking undergraduate students, offering valuable insights into their active participation and contributions to the instructional process. Full article

Animal welfare education requires pedagogical models that bridge conceptual knowledge with practice. This study presents GamifyWELL, a biomimetic, gamified learning environment for students, farmers, and veterinary technicians. Grounded in ecological principles of adaptation, diversification, and niche specialization, the design emulates how living systems evolve through feedback and cooperation. These principles were translated into an instructional model that integrates a core pathway (Pre-Test, Levels 1–4, Post-Test) with optional enrichment tasks and a role-specific Reward Marketplace. Question formats are constant across levels (MCQ, image-based, video-based) while cognitive difficulty increases, culminating in Positive Welfare scenarios. We describe the learning design structure and report preliminary implementation observations using a mixed-methods evaluation plan (pre/post knowledge assessments and engagement indicators). Results from early deployment indicate strong usability and engagement, with high voluntary uptake of enrichment tasks and positive learner feedback on role-tailored rewards; full empirical testing is in progress. Findings support the feasibility and pedagogical promise of biomimetic gamification to enhance knowledge, motivation, and intended practice in animal welfare education. GamifyWELL offers a replicable framework for nature-inspired instructional design that can be extended to allied sustainability domains. Full article

We introduce a novel, privacy-preserving AI authoring copilot designed for educational content creation, which uniquely combines a Markov Decision Process (MDP) as a reinforcement learning orchestrator with a locally deployed Qwen3-1.7B-ONNX large language model to iteratively refine text for clarity, unity, and engagement—all running on a modest CPU-only system (Intel i7, 16 GB RAM). Unlike cloud-dependent models, our agent treats writing as a sequential decision problem, selecting refinement actions (e.g., simplification, elaboration) based on real-time LLM and sentiment feedback, ensuring pedagogically sound outputs without internet dependency. Evaluated across five diverse topics, our MDP-orchestrated agent achieved an overall average quality score of 4.23 (on a 0–5 scale), statistically equivalent to leading cloud-based LLMs like ChatGPT and DeepSeek. This performance was validated through blind evaluations by four independent LLMs and human raters, supported by statistical consistency analysis. Our work demonstrates that lightweight local LLMs, when guided by principled MDP policies, can deliver high-quality, context-aware educational content, bridging the gap between powerful AI generation and ethical, on-device deployment. This advancement empowers educators, researchers, and curriculum designers with a trustworthy, accessible tool for intelligent content augmentation aligning with the Quality Education Sustainable Development Goal through innovations in educational technology, inclusive education, equity in education, and lifelong learning. Full article

Augmented reality (AR) offers a novel way to enrich museum visits by deepening engagement and enhancing learning. This study presents the development of a mobile application for the Abylkhan Kasteyev State Museum of Arts (Almaty, Kazakhstan), designed to recognize and visualize exhibits through AR. Using computer vision and machine learning, the application identifies artifacts via a smartphone camera and overlays interactive 3D models in an augmented environment. The system architecture integrates Flutter plugins for AR rendering, YOLOv8 for exhibit recognition, and a cloud database for dynamic content updates. This combination enables an immersive educational experience, allowing visitors to interact with digital reconstructions and multimedia resources linked to the exhibits. Pilot testing in the museum demonstrated recognition accuracy above 97% and received positive feedback on usability and engagement. These results highlight the potential of AR-based mobile applications to increase accessibility to cultural heritage and enhance visitor interaction. Future work will focus on enlarging the exhibit database, refining performance, and incorporating additional interactive features such as multi-user collaboration, remote access, and gamified experiences. Full article

Objective: This study aimed to explore the barriers to and factors influencing the adoption of smart healthcare among Chinese patients with cardiovascular disease (CVD) and their caregivers with medium or low levels of self-care or caregiving ability. Methods: Semi-structured interviews were conducted with fourteen patients with CVD and nine caregivers to determine their needs and suggestions regarding the adoption of smart healthcare in Suzhou, Jiangsu Province, China. Results: The interview data were analyzed using Colaizzi’s seven steps. Two major themes and eleven subthemes were extracted, including facilitating factors (motivation to use, learning and interactive engagement, knowledge translation, and psychological identity) and obstacles (insufficient ease of operation, risk to personal privacy, ambivalence about paying for knowledge, fear of physical and mental injury, mistrust of implementation personnel, and technical or functional limitations of equipment) to the adoption of smart healthcare. Conclusions: Our findings suggest that before implementing smart healthcare interventions for patients with CVD and their caregivers, it is necessary to fully assess their willingness; push precise content based on their learning, interaction, and psychological needs; and address the technical barriers and privacy protection to enhance their willingness to use the system. Full article

Engagement in everyday creative activities is widely considered to be a good way to develop creative thinking ability. Perhaps, by engaging in such activities, creators can learn at which point their work could be acknowledged as novel and useful by peers or experts in the field. However, little is known about the underlying mechanisms of this development process. So, our study aimed to examine the mediating effect of self-rated originality on the relationship between everyday creative activities and AI-rated originality in divergent thinking. In our dataset, the indirect effect of everyday creative activities on AI-rated originality was significant, whereas the direct effect was not significant, indicating full mediation. These results revealed that engaging in everyday creative activities did not directly enhance AI-rated originality but instead indirectly contributed to AI-judged originality through students’ generation of self-perceived original ideas. Our empirical findings will open the door to a better understanding of how incorporating students’ self-evaluations into creative education might facilitate the transition from creative activities to creative thinking, and eventually to domain-specific creative achievements. Full article

A design science framework integrates sustainability into business development across sectors. The framework embeds sustainability, reflected in environmental, social, and governance (ESG) dimensions, within a structured process that links drivers, evaluation components, and outcome indicators. Six principles guide its structure: clarity, integration, adaptability, stakeholder engagement, performance feedback, and scoring consistency. Researchers applied the framework in energy, engineering, and agribusiness cases. Case results show how the framework improves opportunity selection, identifies capability gaps, strengthens prioritization, and structures stakeholder input without adding complexity. Findings confirm that incorporating sustainability factors during the initial stage of business development changes decision patterns, aligns projects with long-term goals, and increases transparency in portfolio planning. This design science approach moves sustainability and its ESG dimensions from a reporting concern to a central element of strategic evaluation and growth planning. Organizations gain a practical structure to align opportunity development with resilience, learning capacity, and sustainability outcomes. In addition, the framework provides a foundation for adaptation, digital tool development, and longitudinal feedback cycles as firms integrate sustainability and ESG dimensions within uncertain policy, market, and stakeholder environments. Full article

Background: This study aimed to develop and evaluate the impact of a virtual reality (VR)-based speak-up program for Korean nursing students to strengthen patient safety management competencies. A nonequivalent control group pretest–posttest quasi-experimental design was employed. Methods: Fifty-six fourth-year nursing students (28 each in the experimental and control groups) were enrolled. The experimental group participated in a VR-based speak-up program, while the control group engaged in a scenario-based speak-up program. Each program consisted of a single 150 min session. The experimental group completed the program individually using a head-mounted display device, whereas the control group participated in small-group sessions. Outcome measures included speak-up, sense of safety control, confidence in clinical decision-making, and patient safety management activities. Data were analyzed using SPSS 26.0, including the χ² test, t-test, Mann–Whitney U test, Wilcoxon signed rank test and repeated measures analysis. Results: Speak-up performance significantly improved in both groups, but the differences between the groups were not significant. In contrast, sense of safety control, confidence in clinical decision-making, and patient safety management activities improved more in the control group, which engaged in discussion-based learning. These findings suggest that VR learning effectively strengthens individual assertiveness and behavioral readiness through immersive, self-directed experiences, whereas the discussion-based approach in the control group enhances collaborative reasoning and confidence related to patient safety. Conclusions: Integrating VR-based Speak-up education with existing learning methods can establish a stepwise program that enhances nursing students’ Speak-up competency and patient safety skills. This approach may bridge the gap between theory and practice, fostering nurses who actively promote patient safety. Full article

This article formalizes AI-assisted assessment as a discrete-time policy-level design for iterative feedback and evaluates it in a digitally transformed higher-education setting. We integrate an agentic retrieval-augmented generation (RAG) feedback engine—operationalized through planning (rubric-aligned task decomposition), tool use beyond retrieval (tests, static/dynamic analyzers, rubric checker), and self-critique (checklist-based verification)—into a six-iteration dynamic evaluation cycle. Learning trajectories are modeled with three complementary formulations: (i) an interpretable update rule with explicit parameters $\eta$ and $\lambda$ that links next-step gains to feedback quality and the gap-to-target and yields iteration-complexity and stability conditions; (ii) a logistic-convergence model capturing diminishing returns near ceiling; and (iii) a relative-gain regression quantifying the marginal effect of feedback quality on the fraction of the gap closed per iteration. In a Concurrent Programming course ($n=35$), the cohort mean increased from 58.4 to 91.2 (0–100), while dispersion decreased from 9.7 to 5.8 across six iterations; a Greenhouse–Geisser corrected repeated-measures ANOVA indicated significant within-student change. Parameter estimates show that higher-quality, evidence-grounded feedback is associated with larger next-step gains and faster convergence. Beyond performance, we engage the broader pedagogical question of what to value and how to assess in AI-rich settings: we elevate process and provenance—planning artifacts, tool-usage traces, test outcomes, and evidence citations—to first-class assessment signals, and outline defensible formats (trace-based walkthroughs and oral/code defenses) that our controller can instrument. We position this as a design model for feedback policy, complementary to state-estimation approaches such as knowledge tracing. We discuss implications for instrumentation, equity-aware metrics, reproducibility, and epistemically aligned rubrics. Limitations include the observational, single-course design; future work should test causal variants (e.g., stepped-wedge trials) and cross-domain generalization. Full article

A growing international consensus holds that science education must advance beyond content coverage to cultivate robust understanding of the Nature of Science (NoS)—how scientific knowledge is generated, justified, revised, and socially negotiated. Yet naïve conceptions persist among students and teachers, and effective, scalable classroom strategies remain contested. This narrative review synthesizes research and practice on games and playful activities that make epistemic features of science visible and discussable. We organize the repertoire into six families—(i) observation–inference and discrepant-event tasks; (ii) pattern discovery and rule-finding puzzles; (iii) black-box and model-based inquiry; (iv) activities that dramatize tentativeness and anomaly management; (v) deliberately underdetermined mysteries that cultivate warrant-based explanations; and (vi) moderately contextualized games. Across these designs, we analyze how specific mechanics afford core NoS dimensions (e.g., observation vs. inference, creativity, plurality of methods, theory-ladenness and subjectivity, tentativeness) and what scaffolds transform playful engagement into explicit, reflective learning. We conclude with pragmatic guidance for teacher education and curriculum design, highlighting the importance of language supports, structured debriefs, and calibrated contextualization, and outline priorities for future research on equity, assessment, and digital extensions. Full article

Contemporary medical education is shifting from traditional, teacher-centred anatomy instruction toward interactive, student-centred, and clinically integrated approaches. The Jigsaw Method aligns with this shift by fostering collective competence, which is vital for effective clinical practice. This study aimed to introduce the jigsaw model to medical students and explore its perceived effectiveness in teaching anatomy. A phenomenological qualitative design was employed to explore the experiences of second-year medical students (n = 120) at the Faculty of Health-Care Sciences, Eastern University, Sri Lanka. Open-ended questions were used to elicit students’ reflections on the effectiveness of jigsaw learning. Thematic analysis was conducted using NVivo software (ver.14). Students reported generally favourable perceptions of the jigsaw method. Four major themes emerged: two described the positive impact of the approach—enhanced understanding through peer learning and improved interpersonal and communication skills; the remaining themes addressed challenges in implementation and suggestions for refinement. Participants appreciated the structured collaboration and positive interdependence fostered by the method. Moreover, students viewed the jigsaw technique as well-aligned with student-centred learning principles. The jigsaw method was perceived as an effective cooperative learning strategy that enhanced engagement, promoted active participation, and fostered teamwork in anatomy education. These findings support the integration of structured peer-based approaches into medical curricula to enrich students’ learning experiences. Full article