Search Results (269)

Background/Objectives: End-of-life care is a vital part of nursing education that has been overlooked until recent years. Advance care planning should be incorporated into the prelicensure nursing curriculum to build student nurses’ confidence in aiding patients and families with their preferred future care plans. Advance care planning tools, such as the Advance Health Care Directive (AHCD) and Five Wishes, provide experiential learning opportunities that bridge theoretical knowledge with real-world patient advocacy. In this study, students were asked to complete either the AHCD or Five Wishes document as though planning for their own end-of-life care, encouraging personal reflection and professional insight. Embedding these assignments into nursing education strengthens students’ confidence in facilitating end-of-life discussions. This study applied Kolb’s experiential learning theory, including concrete experience, reflective observation, abstract conceptualization, and active experimentation, to explore student nurses’ perspectives on the Advance Health Care Directive and Five Wishes assignments, as well as their understanding of end-of-life care. Methods: This study used an exploratory–descriptive qualitative design featuring one open-ended question to collect students’ views on the assignments. Results: The final sample comprised 67 prelicensure student nurses from Bachelor of Science and Entry-Level Master’s programs. The Advance Health Care Directive and/or Five Wishes assignment enhanced students’ understanding of end-of-life decision-making. Conclusions: It is essential to complete the assignment and immerse oneself in an end-of-life situation to grasp patients’ perspectives and concerns regarding when to engage in difficult conversations with their patients. Full article

Medical education is the paradigm of 21st century education and the current changes involve the adoption of integrative and comprehensive patient-centered teaching and learning approaches. Thus, curricular developers from George Emil Palade University of Medicine, Pharmacy, Sciences, and Technology of Targu Mures (G.E. Palade UMPhST of Targu Mures) have recently designed and implemented an innovative medical curriculum, as well as two valuable assessment tools for both theoretical knowledge and practical skills. Thus, during the first three preclinical years, the students will benefit from an organ- and system-centered block teaching approach, while the clinical years will focus on enabling students to achieve the most important practical skills in clinical practice, based on a patient bedside teaching system. In terms of theoretical knowledge assessment, the UNiX center at G.E. Palade UMPhST of Targu Mures, a recently designed center endowed with the latest next-generation technology, enables individualized, secured multiple-choice question-based assessments of the student’s learning outcomes. Moreover, an intelligent assessment tool for practical skills was also recently implemented in our branch in Hamburg, the Objective Structured Clinical Examination (O.S.C.E). This system uses direct observations for testing the student’s practical skills regarding anamnesis, clinical exams, procedures/maneuvers, the interpretation of laboratory tests and paraclinical investigations, differential diagnosis, management plans, communication, and medical counselling. The integrative, comprehensive, patient-centered curriculum and the intelligent assessment system, implemented in G.E Palade UMPhST of Targu Mures, help define innovation in education and enable the students to benefit from a high-quality medical education. Full article

Objectives: This study aimed to analyze the critical and reflective self-assessment capacity of dentistry students based on two clinical courses that employ self-assessment processes as a strategy to foster autonomy in health care. Materials and Methods: Reflections from third- and fifth-year students were evaluated over a three-year period. The methodology sought to identify the presence of critical reflections, perceptions of strengths and weaknesses, and the formulation of improvement plans. Results: The results revealed low levels of continuous reflection, with only 20.0% of third-year students and 24.1% of fifth-year students engaging in reflection in at least half of their clinical activities. However, 78.7% of third-year students and 90.8% of fifth-year students completed at least one reflection during the academic year. The ability to sustain continuous critical reflection was observed in only 22.1% of the 453 students evaluated. These findings present a concerning scenario, as critical reflection is directly linked to competence in health care and informed decision-making. Conclusions: The study concludes that formative assessment processes requiring critical and reflective self-assessment must be broadly integrated into the curriculum to foster significant gains in the development of professional competencies. Full article

Metacognition and self-regulated learning are widely understood to offer significant benefits for pupils’ mathematical problem solving; however, the existing literature highlights that the under-representation of these concepts in curriculum, policy, and teacher professional development means that their potential for impact remains unfulfilled. This article, therefore, examines the potential value of an innovative fading professional development programme—“Stepping Stones”—in enhancing teachers’ understanding and use of metacognitive strategies for mathematical problem solving. Adopting a convergent mixed methods design, this pilot evaluation involved Year 2 teachers across five primary schools. The results from both qualitative and quantitative data demonstrate that, as the scaffolding provided by programme materials faded and teachers assumed greater responsibility for session planning, they incorporated metacognitive strategies into their planning and delivery with increased independence. The results also indicate the acceptability of this professional development model, suggesting that, when combined with peer collaboration, the fading design was associated with improvements in knowledge and confidence regarding both metacognition and mathematical problem solving, alongside increased ownership and buy in. The conclusions advocate further examination and implementation of fading models of professional development to promote the understanding and use of metacognition for mathematical problem solving and recommend exploration into different professional development contexts. Full article

The UI GreenMetric World University Ranking has become a widely adopted instrument for benchmarking institutional sustainability performance; nevertheless, empirically grounded evidence from universities in diverse regional contexts remains scarce. This study undertakes a rigorous appraisal of the extent to which Mahasarakham University (MSU) has institutionalized the United Nations Sustainable Development Goals (SDGs) within its pedagogical offerings, research portfolio, community outreach, and governance arrangements during the 2021–2024 strategic cycle. Employing a mixed-methods design and guided by the 2024 UI GreenMetric Education and Research indicators, this investigation analyzed institutional datasets pertaining to curriculum provision, ring-fenced research funding, 574 peer-reviewed sustainability publications, student-led community initiatives, and supporting governance mechanisms; the analysis was interpreted through a Plan–Do–Check–Act management lens. The number of sustainability-oriented academic programs expanded from 49 to 58. Student participation in community service activities strongly recovered following the COVID-19 pandemic, and MSU’s GreenMetric score increased from 7575 to 8475, thereby elevating the institution to the 100th position globally. These gains were facilitated by strategic SDG-aligned investment, cross-sector collaboration, and the consolidation of international partnerships anchored in Thailand’s Isaan region. The MSU case provides a transferable model for universities—particularly those operating in resource-constrained contexts—endeavoring to align institutional development with the SDGs and internationally recognized quality benchmarks. The findings substantiate the capacity of transformative education and applied research to engender enduring societal and environmental benefits. Full article

Introduction: The escalating scarcity of skilled healthcare professionals is particularly pronounced within surgical specialties, where the prospect of attracting prospective medical practitioners poses formidable challenges. Throughout their academic journey, students exhibit diminishing enthusiasm and motivation to pursue careers in surgery, including trauma surgery. It is postulated that the caliber of teaching plays a pivotal role in influencing students’ subsequent specialization choices. Methods: This prospective observational study was conducted among a cohort of third-year medical students at the German University Medicine Greifswald. The methodology encompassed the utilization of a self-administered questionnaire to procure data. Results: The study encompassed 177 participants, of whom 34.7% expressed an inclination toward a career in surgery (22.7% in trauma surgery). Participants who reported a favorable impact from the examination course displayed a significantly heightened interest in clinical clerkships within trauma surgery (p < 0.001), and even expressed a contemplation of specializing in orthopedics and trauma surgery (p = 0.001). Logistic regression analysis highlighted that the convergence of practical training and positive role modeling emerged as the most influential factors augmenting the allure of trauma surgery. Conclusions: Evidently, students who gleaned substantial benefits from high-quality practical instruction in trauma surgery exhibited a significantly heightened likelihood of pursuing this domain in their future endeavors. Surgical academic institutions stand to leverage this insight in their strategic planning for attracting and retaining potential residents. Cultivating a positive affinity for trauma surgery should be instilled early in the curriculum, subsequently sustained through ongoing immersive engagement that encompasses professional as well as interpersonal dimensions. Full article

This paper proposes a KeyBERT-based method for constructing a knowledge graph of the electronic information curriculum system, aiming to enhance the structured representation and relational analysis of educational content. Electronic Information Engineering curricula encompass diverse and rapidly evolving topics; however, existing knowledge graphs often overlook multi-word concepts and more nuanced semantic relationships. To address this gap, this paper presents a KeyBERT-enhanced method for constructing a knowledge graph of the electronic information curriculum system. Utilizing teaching plans, syllabi, and approximately 500,000 words of course materials from 17 courses, we first extracted 500 knowledge points via the Term Frequency–Inverse Document Frequency (TF-IDF) algorithm to build a baseline course–knowledge matrix and visualize the preliminary graph using Graph Convolutional Networks (GCN) and Neo4j. We then applied KeyBERT to extract about 1000 knowledge points—approximately 65% of extracted terms were multi-word phrases—and augment the graph with co-occurrence and semantic-similarity edges. Comparative experiments demonstrate a ~20% increase in non-zero matrix coverage and a ~40% boost in edge count (from 5100 to 7100), significantly enhancing graph connectivity. Moreover, we performed sensitivity analysis on extraction thresholds (co-occurrence ≥ 5, similarity ≥ 0.7), revealing that (5, 0.7) maximizes the F1-score at 0.83. Hyperparameter ablation over n-gram ranges [(1,1),(1,2),(1,3)] and top_n [5, 10, 15] identifies (1,3) + top_n = 10 as optimal (Precision = 0.86, Recall = 0.81, F1 = 0.83). Finally, GCN downstream tests show that, despite higher sparsity (KeyBERT 64% vs. TF-IDF 40%), KeyBERT features achieve Accuracy = 0.78 and F1 = 0.75, outperforming TF-IDF’s 0.66/0.69. This approach offers a novel, rigorously evaluated solution for optimizing the electronic information curriculum system and can be extended through terminology standardization or larger data integration. Full article

Effective resource planning in higher education requires anticipating student demand for courses, especially when dealing with elective programs. Monitoring student preference is a recurring topic in the literature; however, to the authors’ knowledge, no simple methods for estimating student preferences when choosing courses in higher education have been proposed. This study develops and explores the use of a simple questionnaire to capture patterns in student course preferences within a university context. The research is developed in the context of the nine Cross-Over modules offered as part of the curriculum of the master’s programs (MSc) of the Faculty of Civil Engineering and Geosciences of Delft University of Technology (The Netherlands). No prior registration is required far in advance for these courses, making an accurate estimation of student numbers critical for the planning and allocation of educational resources. The developed questionnaire is applied three times in two different academic years to the students’ choice of Cross-Over modules. The questionnaire was shared in 2021, with 225 responses out of 339 students, in 2022, with 159 responses out of 365 students, and in 2024, with 94 responses out of 272 students. Student enrollment in the academic year 2023/2024 is used to assess the performance of the questionnaire. The questionnaire is able to capture general preferences of the students, providing fair estimates of the number of students per course; larger differences are observed in courses with a lower number of students. In addition, some patterns were identified in student preferences: there is a relationship between the first and second choices, and students usually choose modules closer to their own disciplines. The developed questionnaire provides with a reasonable first estimation of the expected number of students in courses, allowing for better planning and allocation of educational resources beforehand. Full article

This study explores how Speech and Elocution Training (SET) activates language potential and fosters career-oriented development among higher vocational students through self-efficacy mechanisms. Through qualitative interviews with four vocational graduates who participated in SET 5 to 10 years ago, the research identifies three key findings. First, SET comprises curriculum content (e.g., workplace communication modules such as hosting, storytelling, and sales pitching) and classroom training using multimodal TED resources and Toastmasters International-simulated practices, which spark language potential through skill-focused, realistic exercises. Second, these pedagogies facilitate a progression where initial language potential evolves from nascent career interests into concrete job-seeking intentions and long-term career plans: completing workplace-related speech tasks boosts confidence in career choices, planning, and job competencies, enabling adaptability to professional challenges. Third, SET aligns with Bandura’s four self-efficacy determinants; these are successful experiences (including personalized and virtual skill acquisition and certified affirmation), vicarious experiences (via observation platforms and constructive peer modeling), verbal persuasion (direct instructional feedback and indirect emotional support), and the arousal of optimistic emotions (the cognitive reframing of challenges and direct desensitization to anxieties). These mechanisms collectively create a positive cycle that enhances self-efficacy, amplifies language potential, and clarifies career intentions. While highlighting SET’s efficacy, this study notes a small sample size limitation, urging future mixed-methods studies with diverse samples to validate these mechanisms across broader vocational contexts and refine understanding of language training’s role in fostering linguistic competence and career readiness. Full article

To address the challenges of real-time decision-making and resource optimization in multi-agent cooperative interception tasks within dynamic environments, this paper proposes a hierarchical framework for reinforcement learning-based interception algorithm (HFRL-IA). By constructing a hierarchical Markov decision process (MDP) model based on dynamic game equilibrium theory, the complex interception task is decomposed into two hierarchically optimized stages: dynamic task allocation and distributed path planning. At the high level, a sequence-to-sequence reinforcement learning approach is employed to achieve dynamic bipartite graph matching, leveraging a graph neural network encoder–decoder architecture to handle dynamically expanding threat targets. At the low level, an improved prioritized experience replay multi-agent deep deterministic policy gradient algorithm (PER-MADDPG) is designed, integrating curriculum learning and prioritized experience replay mechanisms to effectively enhance the interception success rate against complex maneuvering targets. Extensive simulations in diverse scenarios and comparisons with conventional task assignment strategies demonstrate the superiority of the proposed algorithm. Taking a typical scenario of 10 agents intercepting as an example, the HFRL-IA algorithm achieves a 22.51% increase in training rewards compared to the traditional end-to-end MADDPG algorithm, and the interception success rate is improved by 26.37%. This study provides a new methodological framework for distributed cooperative decision-making in dynamic adversarial environments, with significant application potential in areas such as maritime multi-agent security defense and marine environment monitoring. Full article

Data visualization has empowered analyzing, exploring, and communicating data effectively. It has been widely adopted across diverse disciplines. However, research indicates that data visualization in education is mainly favored in distance learning environments, leaving traditional classroom settings largely unexplored. Moreover, despite the growing emphasis on data-driven decision-making in education, a notable gap exists in using visualized assessment data to develop curriculum planning in language classrooms. Therefore, we developed a model for syllabus design and material development in an EFL classroom in Taiwan based on diagnostic test results. An online adaptive diagnostic test was used to gather visualized assessment data, which was analyzed with an AI tool to identify language learning needs and to develop the syllabus design and materials. By incorporating visualized diagnostic assessment data into the decision-making process, educators can design responsive and individualized syllabi that meet the needs of students. This approach enhances the effectiveness of language teaching and makes curriculum development more accessible and manageable for educators. Full article

The rapid integration of artificial intelligence (AI) in education has transformed traditional teaching methodologies, particularly within Outcome-Based Education (OBE), in higher education. Based on the Technological Pedagogical Content Knowledge (TPACK) model and the OBE system, this present study investigates how teachers perceive AI applications, specifically ChatGPT, in enhancing instructional design and student performance. The research develops a new AI-based instructional planning model, incorporating AI ChatGPT capabilities, teacher competencies, and their direct and indirect effects on student outcomes. This study employs quantitative research design using Structural Equation Modeling (SEM) to validate the proposed model. Data were collected from 320 university teachers in Pakistan using a structured survey distributed through WhatsApp and email. Findings from the direct path analysis indicate that AI ChatGPT capabilities significantly enhance instructional planning (β = 0.33, p < 0.001) and directly impact student performance (β = 0.20, p < 0.001). Teacher competencies also play an important role in instructional planning (β = 0.37, p < 0.001) and student performance (β = 0.16, p = 0.020). The indirect path analysis reveals that instructional planning mediates the relationship between AI ChatGPT capabilities and student performance (β = 0.160, p < 0.001), as well as between teacher competencies and student performance (β = 0.180, p < 0.001). The R-square values indicate that instructional planning explains 41% of its variance, while student performance accounts for 56%. These findings provide theoretical contributions by extending AI adoption models in education and offer practical implications for integrating AI tools in teaching. This study emphasizes the need for professional development programs to enhance educators’ AI proficiency and suggests policy recommendations for AI-driven curriculum development. Full article

This study investigates how pre-service Earth science teachers used ChatGPT in designing lessons based on the 5E instructional model and what educational opportunities and challenges emerged. As generative AI tools gain traction in education, understanding their integration into science lesson planning is increasingly important. Eight pre-service teachers from a South Korean university participated in a four-week instructional design project. They developed 5E-aligned Earth science lessons while interacting with ChatGPT for idea generation, explanation, activity development, and assessment. Data sources included lesson plans, ChatGPT interaction logs, reflective journals, and interviews. Thematic analysis was used to examine instructional uses of AI and the adaptations required during the process. Findings showed that ChatGPT supported different phases of the 5E model—providing metaphors and analogies in Engage, activity ideas in Explore, draft explanations in Explain, task prompts in Elaborate, and assessment questions in Evaluate. However, participants frequently revised or rejected AI-generated content to match inquiry goals, student readiness, and curriculum standards. The study highlights the importance of pedagogical reasoning in AI-supported lesson design. It contributes to the growing literature on teacher education and AI by offering a phase-specific view of GenAI use and underscoring the instructional mediation needed for effective application. Full article

Soft skills such as client-oriented communication, leadership, and teamwork skills are essential for veterinary clinicians. However, they are rarely addressed in the academic curriculum of most veterinary schools. Role-playing has been previously used to train and evaluate communication skills in veterinary students, but leadership and teamwork are difficult to implement in this methodology. In this study, we designed a novel role-playing activity where groups of undergraduate veterinary students faced simulated pre-planned clinical consultations portraying different roles in a hierarchically structured group (leader, two veterinarians, and one client). We tested the performance of the participants before and after receiving a focused lecture on soft skills. While the overall performance of the students in veterinary roles was significantly better after the lecture, the number of mistakes related to leadership did not significantly vary. Students rated the role of leader consistently lower than the rest. Participants considered that this novel design was useful to train and evaluate these competences. Hierarchically structured role-playing is a suitable tool to improve soft skills in veterinary students, allowing for self-learning and training in a controlled environment. Full article

Sustainable development goals aim to build a sustainable and prosperous world for future generations. Education, one of the sustainable development goals, is also an important predictor of other development goals. The aim of this study is to analyze the views and suggestions of students and teachers on sustainable development goals. In this context, semi-structured interviews were conducted with 30 students and three teachers who participated in the study and the interview form prepared by the researchers as a data collection tool was analyzed with content analysis. As a result of the analysis, students’ answers were concentrated on the themes of environmental pollution, social equality, renewable energy sources, natural habitats, and improvement of the economy regarding sustainable development goals; teachers’ answers were concentrated on the themes of changes in curriculum and textbooks, in-school/outside-school activities, and collaborations that schools will establish with institutions. As a result of this study, it was concluded that students’ views and teachers’ solution suggestions regarding sustainable development goals were limited. Since this study is a qualitative study covering both students and teachers, it is expected to provide a good starting point in planning and developing educational strategies for sustainable development goals. Full article