This scoping review aims to investigate the current applications of Digital Twin (DT) technology within the field of medical education, evaluating its advantages, limitations, and implications for future research and practice. A comprehensive search was conducted across seven authoritative databases, including PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI), covering the period from the inception of each database until November 20, 2024. Data extraction was carried out using NoteExpress and EndNote software, and studies were selected based on strict inclusion and exclusion criteria. A total of 112 articles were identified in the initial search, of which eight met the criteria for final inclusion in the analysis. These studies predominantly addressed the application of DT in medical imaging education, critical care training, and medical education for individuals with disabilities. The findings reveal that DT technology has shown significant promise in enhancing teaching effectiveness, improving student engagement, and increasing overall satisfaction. However, several limitations were identified, including the nascent stage of the technology, challenges related to system integration, high resource demands, and the difficulties faced by educators in mastering and implementing the technology. Despite these challenges, the application of DT in medical education is progressing, demonstrating substantial potential to advance the modernization of educational practices, improve learning outcomes, and enhance educational efficiency. To fully realize the benefits of DT, further research is needed to address the technological, economic, and pedagogical barriers currently limiting its widespread adoption. Additionally, the development of more effective “digital-physical fusion” teaching models is essential for maximizing the utility and scalability of DT technology in medical education.
An Integer Linear Programming (ILP) model was proposed to optimize academic timetables, with a focus on the School of Management at Western Galilee Academic College. The model was designed to address the dual challenges of course scheduling and faculty availability while incorporating a minor structural adjustment to enhance computational efficiency and accelerate convergence, particularly for large-scale problems. By employing this model, optimal scheduling solutions were generated within minutes, even in scenarios involving over 200 classes and 100 lecturers. The approach effectively minimizes planning time, identifies unavoidable scheduling conflicts, and highlights unschedulable classes due to constraint violations. Furthermore, the model provides actionable insights into staffing requirements, ensuring a comprehensive resource allocation strategy. Results from the application of the model during the 2023 winter semester demonstrated its capability to efficiently schedule 236 classes across multiple programs and instructional modalities. The method achieved adherence to predefined constraints, optimized the utilization of institutional resources, and enhanced overall scheduling efficiency. This case study underscores the potential of the proposed ILP framework to streamline academic timetabling processes, particularly in environments with diverse programmatic needs and complex resource interdependencies. The findings indicate that the model can be readily adapted to other academic institutions seeking to improve the effectiveness and precision of their scheduling systems.
The rapid advancement of artificial intelligence (AI) technology has significantly impacted the higher education sector, creating an urgent demand for composite talents equipped with interdisciplinary knowledge. The cultivation of “AI + X” talents, combining AI expertise with various domain-specific skills, has been increasingly recognized as a critical educational goal. This study explores the development and implementation of teaching practices aimed at fostering such composite talents in higher education institutions. The growing integration of AI into diverse fields necessitates the construction of a robust curriculum that combines AI technology with other disciplines, thereby enhancing students’ interdisciplinary capabilities. A comprehensive literature review and experimental research methods were employed to analyze both domestic and international trends in AI-related talent development. Additionally, a predictive model of student learning performance was developed through exploratory data analysis (EDA) and machine learning (ML), with results validating the efficacy of linear regression models in performance prediction. The research identifies key strategies for enhancing teaching practices, including reinforcing theoretical and technological knowledge, promoting personalized and practical teaching approaches, strengthening foundational disciplinary learning, and encouraging cross-disciplinary synergies. These strategies were designed to enhance students’ critical thinking and practical competencies, with the aim of preparing them for the complex challenges of a rapidly evolving workforce. Furthermore, the paper discusses how AI-driven educational reforms can support the development of key industries, such as smart cities, smart finance, and the broader digital economy. The findings suggest that integrating AI technology into educational practices is essential for the effective cultivation of “AI + X” talents. However, significant challenges remain, including the scarcity of educational resources and the need for more contemporary teaching methodologies. Further research is required to refine talent training systems and to optimize institutional mechanisms, ensuring that higher education institutions can meet the demands of future technological and economic transformations. Through sustained educational innovation, it is envisaged that a new generation of innovative and versatile professionals will be equipped to contribute to societal advancement.
Returnee faculty play a pivotal role in international knowledge transfer and the advancement of scientific research within domestic universities. However, the effectiveness of returnees in enhancing institutional research performance remains inadequately understood. This study seeks to quantify and examine the collaborative academic networks of returnee faculty, assessing their impact on research output and funding performance. Based on an extensive academic dataset, comprehensive scientific collaboration networks (SCN) of returnees were constructed and empirically analyzed to elucidate the influence mechanisms underpinning research performance. The findings indicate that the presence of returnee faculty substantially enhances overall publication output and funding acquisition. Further, within the SCN of returnees, both academic influence and network expansion positively correlate with research productivity and funding success, whereas an increase in cooperation density appears to exert a negative effect. Additionally, the evolution of these collaboration networks was explored, revealing that returnees’ SCN display lower similarity and retention over time compared to those of native faculty. These insights offer a valuable theoretical basis for improving the management and integration of returnee faculty and optimizing the allocation of higher education resources, thereby fostering more effective pathways for enhancing institutional research outcomes.
This study investigates the differences in the factors contributing to school dropout between rural and urban educational institutions in Romania, focusing on individual, family, school, and community dimensions. A sample of 557 participants, including educational directors, teachers, and administrators, was surveyed to assess the prevalence of various dropout causes. The Mann-Whitney U test was employed to identify statistically significant differences between rural and urban schools in specific dropout factors. The findings indicate that urban schools report higher incidences of individual-level issues such as substance abuse, juvenile delinquency, teenage pregnancy, and health-related problems. At the family level, urban institutions were more likely to encounter students with incarcerated parents or those placed in alternative care. School-related factors also varied, with urban schools being characterised by larger class sizes and insufficient access to counselling and guidance services, while rural schools were more affected by early school start times. In the community dimension, urban schools faced greater challenges with negative peer influences and a lack of educational facilities near students’ homes. These results suggest that the causes of dropout in urban settings are more complex, necessitating tailored interventions and resources. It is recommended that context-specific strategies be developed to address the distinct dropout factors in both rural and urban environments, thereby supporting more inclusive and effective educational policies in Romania.
This study aims to investigate the academic community’s engagement with research on green policies within higher education institutions. The study examines the evolving landscape of green policy research in universities, seeking to elucidate trends in academic interest, key contributors, and thematic developments. Employing bibliometric analysis, this research scrutinizes publications indexed in the Web of Science database from 1994 to 2024, with a particular focus on keywords, co-authorship networks, and institutional affiliations. The findings indicate a notable increase in publications, particularly post-2016, reflecting a transition from broad conceptual themes to more specific applications of green policies, including sustainable management practices and performance evaluation. Central themes identified include “green”, “sustainability”, “performance”, and “management”, highlighting a shift from theoretical exploration to practical implementation. Prominent contributors, such as Wang Y and Zhang Y, alongside institutions like Tsinghua University, have significantly advanced the field. Furthermore, the study underscores a robust correlation between the growth in scientific output and the emergence of specialized sustainability journals, indicating an escalating academic demand for focused publication platforms. The results suggest that research on green policies in universities is increasingly characterized by interdisciplinary collaboration and the integration of innovative technologies and methodologies to effectively address sustainability challenges. The field of green policy application in higher education is rapidly expanding, with a well-connected, collaborative research community generating impactful work that harmonizes modern technologies and methodologies to confront sustainability issues at both global and local levels.
This study aims to explore and analyze the profile of UPGRIS character values within the context of campus culture development. A mixed-method approach, integrating both qualitative and quantitative methodologies, was employed. The quantitative analysis focused on identifying which UPGRIS character values—Unggul (excellence), Peduli (caring), Gigih (persistence), Religius (religion), Integritas (integrity), Sinergis (synergy)—are most prominent among students, utilizing percentage analysis. The qualitative approach involved a more in-depth examination through Focus Group Discussions (FGDs) to elucidate the meaning and manifestation of these values. A purposive sampling technique was used to select 2,554 students from seven faculties. Data were collected through psychological scales and FGDs. The findings indicate that the most pronounced character value, based on quantitative data, is religion, while excellence ranks the lowest. Notably, persistence is the highest-rated value in first-year students, whereas character traits such as excellence, caring, and integrity peak in the fifth semester. Conversely, it was observed that nearly all character values, including excellence, caring, persistence, religion and integrity, show a significant decline by the seventh semester. These results provide crucial insights into the fluctuations in character development across different stages of academic progression, offering implications for future educational and institutional interventions.
This study investigates the intricate relationships among workplace deviance, employee engagement, and research quality within the context of higher education institutions (HEIs) in Nigeria, specifically in Sokoto State. Grounded in dynamic capability theory, the normative perspective, and employee engagement theory, this study posits that workplace deviance detrimentally influences employee engagement, which in turn adversely impacts research quality. A moderated-mediation model was proposed, suggesting that employee engagement mediates the relationship between workplace deviance and research quality, while also being moderated by institutional support mechanisms. The analysis, conducted using SmartPLS 4, includes an examination of response rates, preliminary data assessment, validation of measurement instruments, and hypothesis testing. The findings reveal a complex dynamic where workplace deviance, when moderated by a supportive institutional environment, indirectly enhances research quality through increased employee engagement. This paradoxical outcome underscores the significance of fostering a positive work culture that can mitigate the adverse effects of deviant behavior, thereby promoting research excellence. The study's theoretical and practical implications suggest that mitigating workplace deviance, enhancing employee engagement, and encouraging participatory decision-making are crucial for improving research outcomes. Future research is encouraged to further explore the interplay between workplace deviance and employee engagement and to assess the generalizability of these findings across diverse institutional contexts.
A comprehensive Water Conservation Awareness Scale was developed to assess the awareness levels of preschool children regarding water conservation. This scale encompasses four distinct dimensions: personal action awareness, daily activity awareness, outdoor water use awareness, and shared responsibility awareness. The study involved 471 children from four kindergartens located in Uşak Province. The four-factor structure of the scale was validated through both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), confirming its reliability and construct validity. The overall scale demonstrated a Cronbach’s alpha coefficient of 0.79, indicating a high level of internal consistency. The developed scale is intended to serve as a critical tool for evaluating the effectiveness of educational programs aimed at fostering water conservation awareness among young children. Additionally, it provides valuable insights for the design and implementation of early childhood education initiatives focused on environmental sustainability. The findings are expected to contribute significantly to the promotion of water-saving behaviors from an early age.
In an increasingly competitive market landscape, companies must innovate by allocating a significant portion of product sales revenue, specifically at least 22%, towards research and development (R&D). Collaboration between companies and universities, which actively engage in R&D, is crucial in this context. At Andalas University, the Research and Community Service Institute (LPPM) oversees R&D initiatives and community services, including the management of the Science Techno Park. To achieve commercialization objectives, it is imperative to identify and address the factors that inhibit the commercialization of research products at Andalas University. The Fuzzy Analytical Hierarchy Process (FAHP) method has been employed to ascertain the primary factors impeding commercialization. The research findings indicate that the foremost factor inhibiting commercialization is resource availability, assigned a weight of 0.221. This is followed by intellectual property considerations, with a weight of 0.215, and marketing challenges, with a weight of 0.160. These insights provide a foundational basis for the development of strategies aimed at enhancing the commercialization of research products at Andalas University.
The rapid advancement of the internet industry and the emergence of intelligent production models necessitate a transformative approach to talent cultivation in global universities. The Outcomes-Based Education (OBE) model demonstrates distinct advantages and adaptability within this evolving landscape. By defining explicit learning outcomes, incorporating flexible curriculum designs, emphasizing practical skills, adopting a philosophy of continuous improvement, implementing multi-dimensional evaluation mechanisms, and employing student-centered teaching methods, OBE establishes a robust theoretical framework and practical methodology for developing high-quality artificial intelligence (AI) talents suited to the demands of the new era. This study, centered on graduate students at the Capital University of Economics and Business, proposes three strategic dimensions for curriculum reform grounded in the OBE concept: the objectives of curriculum reform, innovative teaching models, and the implementation of the curriculum. The investigation highlights the significance of value cultivation in discipline construction, the establishment of a diversified talent training system, and the optimization of a scientifically integrated teaching framework. This research offers valuable insights, ranging from policy recommendations to practical applications, aimed at advancing the high-quality development of computer science disciplines in a contemporary context.
The purpose of this article is to explore the multifaceted approach required to address the alarming dropout rates and early leavers from education and training in Romanian pre-university education. We emphasize the necessity of collaborative efforts among families, educational institutions, and policymakers to implement effective strategies. As the method used, the bibliographic research was carried out, developed in parallel with the research on the realities in the field in order to provide data for their processing, accumulating data by interviewing stakeholders, analysis and interpretation. By surveying 557 internal stakeholders, primarily teachers, the research identifies critical elements in successful dropout prevention strategies, such as consistent evaluation, clear organizational environments, and strategic communication. The findings reveal significant gaps, particularly in the analysis of external factors and the recruitment and training of stakeholders, suggesting areas for improvement. Implications: Enhancing dropout prevention efforts requires a holistic approach, incorporating thorough environmental analyses, a shared mission and vision among stakeholders, and improved communication and training initiatives. We conclude that a comprehensive and adaptable strategy, inclusive of all educational stakeholders, is crucial for reducing dropout rates and fostering a supportive educational environment.
In the digital age, technological advancements have reshaped the global educational landscape, prompting governments and educational institutions to recognize the critical role of research and innovative talent in driving societal progress and economic growth. Undergraduate education, as a pivotal phase for cultivating future innovators, faces unprecedented opportunities for transformation. The rise of online teaching models has catalyzed a profound pedagogical revolution, offering both flexibility in learning and significant potential for educational innovation. This study investigates the current state and influencing factors of research quality among undergraduates at the Capital University of Economics and Business within the online teaching model. The analysis is structured around four key dimensions: research preparation, research motivation, research communication, and research organization and management. Targeted recommendations are proposed to enhance these aspects, providing valuable insights for the reform of undergraduate education in the context of online learning. The findings underscore the potential of educational transformation as a development opportunity, advocating for the integration of innovative educational models with technological advancements to better align with the talent cultivation needs of the contemporary era.
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