Online-Journals.org (International Association of Online Engineering)
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Insight into Trends in Traditional Chinese Medicine Research for Dementia Treatment: A Bibliometric Analysis
Get PDFTraditional Chinese Medicine (TCM) has gained growing global interest in dementia research due to its demonstrated neuroprotective properties—such as antioxidant and anti-inflammatory effects—and its integrative therapeutic approach combining herbal, acupuncture, and lifestyle interventions. This study conducted a bibliometric analysis of 2,497 publications from 1991 to 2024 using the Web of Science database to evaluate trends and future directions in TCM-related dementia research. Results show a steady rise in academic output, increased publication in high-impact journals, and expanding international collaboration. Key developments include the identification of effective herbal treatments, deeper understanding of TCM’s neuroprotective mechanisms, and successful integration of traditional practices with modern scientific methods. The study highlights the increasing influence of TCM in dementia care and emphasizes the need for interdisciplinary cooperation, rigorous scientific validation, and personalized approaches to further enhance its clinical value and global acceptance
Measuring Inclusive Teaching Strategies in Physical Education: A Comparative Analysis of the Student Teams Achievement Divisions Student Combine Social Software Interaction and Direct Teaching Methods on Students’ Learning Performance
Get PDFCompared with direct teaching methods, the Student Teams-Achievement Divisions Combine Social Software (STADSS) can enhance students’ learning behaviors. We investigated whether incorporating the STADSS approach into a physical education curriculum can improve the students’ motor skills, learning behaviors, and enjoyment. We divided 104 university students from two badminton classes into the STADSS group (n = 55) and the direct instruction (control) group (n = 49). Both groups received the same physical education content and skills instruction for 10 weeks, but with curricula manipulated based on the principles of the respective teaching approaches. The following tools were used: Learning Behavior Scale, Enjoyment in Physical Education Scale, and Badminton Skill Assessment. The STADSS group (3.30 and 2.83, respectively) had higher mean scores in enjoyment and learning behaviors than the direct instruction group (3.09 and 2.63, respectively). Moreover, a significant interaction effect was observed between different teaching methods and students with different achievements in learning behavior, with low-achieving students in the STADSS group outperforming all other groups. In conclusion, STADSS-based badminton teaching was more effective in promoting enjoyment and learning behaviors than the direct teaching method, especially for low-achieving students, and should therefore be integrated into physical education programs
Immersive Learning through Virtual Reality Documentaries: Enhancing Engagement with Historical Narratives
Get PDFVirtual reality (VR) enhances engagement by creating a sense of presence that allows youth to interact more meaningfully with content. This study explores the use of immersive VR documentaries as educational tools for teaching history to young audiences. Using a comparative methodology, the research examines differences in youth engagement when historical content is presented in traditional formats versus VR documentaries. Two versions of the same documentary were developed and shown to university students, who were interviewed before and after viewing. Findings indicate that the VR format fosters a stronger sense of presence and is preferred by students for both engagement and retention of historical narratives. The paper argues that immersing users in factual stories through VR cultivates a learning environment where deeper connections form between the viewer, the virtual setting, and the subject matter. In conclusion, VR documentaries show strong potential as educational tools, particularly for historical content, offering an immersive experience that surpasses traditional documentary formats in effectiveness
Health-Lens: A Health Diagnosis Companion
Get PDFThe “Health Lens” application represents a transformative approach to healthcare, leveraging advanced machine learning to enhance accessibility and diagnostic accuracy in dermatology, especially in underserved regions. This abstract outlines the study’s key findings and implications, structured to enhance clarity and provide depth. Machine Learning Model’s Performance: The core of the application is a robust machine learning model trained on the ISIC 2019 dataset [72], achieving an accuracy of 92%, with a precision of 89% and a recall of 90%. These metrics indicate superior performance compared to baseline methods, establishing the efficacy of the model in the diagnosis of skin conditions. Gender Distribution & Localization: Analysis revealed a higher prevalence of certain skin conditions among men, likely influenced by occupational and lifestyle factors. Conditions such as basal cell carcinoma were predominantly localized in body parts exposed to UV radiation, underscoring the need for targeted health interventions. Potential Overfitting & Mitigation Strategies: Initial model tests indicated potential overfitting, addressed through techniques such as dropout and cross-validation during training. This adjustment ensured the robustness of the model, making it reliable for practical use. Application Features & Impact: “Health Lens” is distinguished by its user-friendly interface and real-time diagnostic capabilities, which significantly reduce barriers to accessing dermatological care. The application also supports sustainable healthcare practices, aligning with the Sustainable Development Goals, particularly in promoting good health and reducing inequalities. Limitations & Future Directions: The study acknowledges limitations such as reliance on a singular dataset and potential connectivity problems in remote areas. Future developments will focus on integrating more diverse datasets and expanding the range of conditions covered, enhancing both the accuracy and utility of the application
AI Chatbots in Higher Education: Opportunities and Challenges for Personalized and Mobile Learning
Get PDFThe landscape of higher education is increasingly shaped by the integration of innovative tools such as chatbots, which offer promising solutions to enhance e-learning experiences. As conversational agents, chatbots are being adopted to address challenges in e-learning environments, including low student engagement and lack of personalized support. This literature review explores the current state of e-learning chatbots in higher education, with a particular focus on mobile learning environment. It aims to investigate how these tools contribute to personalize learning, the opportunities they present, and the key limitations and challenges they face. We conducted a comprehensive review of 815 publications from 2018 to 2024 across three major digital databases: Scopus, IEEE Xplore, and Science direct. From these, 39 studies were selected for in-depth analysis. Findings reveal that chatbots enhance personalized learning by adapting content and feedback based on various learner-specific features. In addition, chatbots are particularly effective when integrated into mobile applications and powered by AI technologies. Results show further that e-learning chatbots in higher education support a wide range of educational tasks from language learning to personalized guidance. Despite these advancements, significant challenges need to be addressed, including the technical limitations of both rule-based and AI-based chatbots. These challenges highlight the need for continued research aimed at improving chatbot capabilities. This review aims to inspire and support the effective integration of chatbots in higher education by offering concrete insights for instructors, developers, and researchers
Immersive and Interactive Learning: A Systematic Review of Virtual Reality in Primary Education
Get PDFVirtual reality (VR) stands for the creation of a simulated environment. Over the last five years, VR, particularly mobile VR technology, has been applied in various educational settings. However, most research has focused on secondary and higher education, while few systematic analyses have focused on the use of VR in primary education. This study systematically reviews VR applications in primary education to address existing research gaps. Using a systematic review approach, we identified and screened studies, assessed their eligibility and inclusion, and used two key academic resources to analyze the data: Web of Science and Scopus. The final number of articles has reached thirty-nine. The results of these databases indicate that VR, particularly mobile VR technology, has a positive impact on learning engagement and teaching effectiveness in primary schools. Nevertheless, further research is needed to explore optimal strategies for integrating VR as an interactive tool in a wider range of educational environments in primary schools and to provide primary school teachers with effective strategies and suggestions for addressing current challenges
Mobile DevOps in Education: Practical Training through Application Development
Get PDFThis paper investigates the effectiveness of teaching DevOps concepts to students through practical mobile application development. We pay particular attention to the challenges specific to the mobile environment. These include the complexity of deploying applications in stores such as Google Play and the App Store and the need to ensure constant and convenient interaction with mobile users. The paper presents a pedagogical model combining project-based learning, containerization, automated CI/CD processes, and cloud platforms. We adapted these elements to the specifics of mobile development. The research presents examples of student projects that implement DevOps practices. In particular, it describes the automation of testing on different types of mobile devices, the setup of build and deployment processes, and the monitoring of application performance in a cloud environment. This study conducts a comparative analysis between the traditional approach to training and the DevOps-oriented methodology. The indicators considered include update cycle duration, number of errors, and adaptation to mobile platforms. The results confirmed that using DevOps in mobile development education improves the quality of students’ technical training, promotes the development of their practical skills, and enhances their competitiveness in the field of mobile technologies
Factors Influencing Mobile Government Adoption in Qatar: An Integrated Model
Get PDFThis study explores the factors influencing the adoption of mobile government applications (MGAs) among Qatari citizens, positioning MGAs as a critical component of mobile learning and mobile interaction technologies within the context of digital governance. Drawing on established technology adoption theories such as the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT), the research aims to develop an integrated model that examines mobile user adoption behavior. A quantitative methodology was employed, incorporating constructs from these frameworks into a structured questionnaire. Data were analyzed using factor analysis and recursive path modeling to identify and test the relationships among key influencing factors. The findings reveal that variables such as age, mobile proficiency and usage frequency, perceived ease of use and usefulness, trust, overall user experience and satisfaction, government communication channels, and personal preferences or hesitations significantly affect the intention to adopt MGAs. These results offer actionable insights for policymakers seeking to increase mobile government service uptake by tailoring strategies to mobile user needs and concerns
The Intensity of Using ChatGPT in Relation to Academic Stress: A Cross-Sectional Study
Get PDFAs the digital world grows rapidly, artificial intelligence (AI) tools such as ChatGPT are transforming how students learn, seek support, and manage academic demands. This study aims to fill a gap in the literature regarding ChatGPT’s role in students’ mental health by exploring the relationship between the intensity of using ChatGPT and academic stress among undergraduate students. A quantitative, cross-sectional correlational design was adopted. Data were collected using an online questionnaire that included the Intensity of Using ChatGPT Scale (IUCS) and the Academic Stress Scale (AAS). The sample consisted of 666 undergraduate students. Descriptive results showed that students use ChatGPT at a moderate level (M = 2.94), while their academic stress levels were low (M = 2.25). Pearson correlation analysis revealed a statistically significant negative relationship between the intensity of using ChatGPT and academic stress (r = −0.637, p < 0.01). Furthermore, regression analysis confirmed that ChatGPT use significantly predicted academic stress levels (β = −0.637, R² = 0.405), with higher use contributing to lower stress. These findings suggest that ChatGPT may serve as a supportive digital tool in reducing academic stress and promoting student well-being in higher education
Dynamic Adjustment of Mobile Ocean Freight Rates Based on Big Data
Get PDFAmidst the intensifying competition in the shipping industry and the ongoing digitalization of global trade, ocean freight rates—characterized as multivariate time series—are influenced by a complex interplay of factors including port network structures, market supply and demand dynamics, and transportation costs. Traditional static pricing strategies have proven inadequate in adapting to the rapidly evolving market conditions. Accurate freight rate forecasting has emerged as a critical prerequisite for enabling dynamic adjustment strategies. However, conventional time series models often fail to capture the spatial correlations among multiple entities. Existing graph neural network (GNN)-based approaches typically rely on either predefined static or dynamic graphs, which lack the capacity to effectively model the interactions between inherent static structures and evolving temporal dependencies in the time series data. In this study, the prediction of mobile ocean freight rates was investigated. The intrinsic data characteristics were first analyzed to uncover the coupling mechanism between static structural features and dynamic temporal patterns in time series. A GNN model based on multivariate time series was then proposed to automatically extract dependencies from both static and dynamic graphs through a datadriven graph learning module. An information interaction mechanism was designed to achieve deep fusion of the two types of graph structures, thereby addressing the subjectivity associated with manually defined graphs and the limitations of single-graph modeling approaches