Academic Trends Research Articles

A BIBLIOMETRIC ANALYSIS OF GERONTECHNOLOGY: LITERATURE TRENDS, CITATION DYNAMICS, AND FUTURE PERSPECTIVES

This study examines academic trends within the gerontechnology literature by evaluating core themes, author collaborations, and scientific contributions across countries. A bibliometric analysis was conducted using data retrieved from the Web of Science database and visualized through VOSviewer software. The study identifies prominent themes and influential authors in gerontechnology research, while also mapping the structure of scientific collaborations among countries and institutions. The findings indicate that countries such as China, the United States, and Malaysia have made significant contributions to the field, with institutions like Hong Kong City University and Monash University hosting high-impact research. Keyword analysis reveals that terms such as "aging," "assistive technology," "quality of life," and "health promotion" demonstrate the strongest linkages, frequently associated with concepts like "cognitive health," "fall prevention," and "enhancing quality of life." Recent research highlights the growing multidisciplinary nature of gerontechnology, offering researchers meaningful insights and broadening its academic relevance. Moreover, studies focused on developing technological solutions to promote the independence of older adults present valuable resources for both academic and industry stakeholders. By providing a comprehensive overview of the current literature, this study aims to guide future research in gerontechnology and support the development of strategic approaches to better address the evolving needs of aging populations.

Human resource management in decentralized educational contexts: a bibliometric mapping and review of scientific literature

This study aimed to conduct a bibliometric and systematic mapping of the literature on human resource management in decentralized educational contexts, using the Scopus database from 2000 to 2025. The methodology was carried out in two phases: (1) a bibliometric analysis and (2) a systematic literature review incorporating both quantitative and qualitative methods. The first phase identified 104 studies, while the second included eight selected publications. Results show that scientific output in this field grew by 17.3% in 2024, with 14% of the publications originating from the United States. Social sciences accounted for 30% of the thematic areas, and multidisciplinary approaches represented 13.8%. The study concludes that research on human resource management in decentralized education systems has advanced in thematic diversity, international participation, institutional support, and author collaboration. However, challenges remain regarding regulatory supervision, well-defined legislation, and ensuring equity and excellence in education. This research also serves as a foundation for future studies, offering an updated overview of current academic trends and emerging priorities in the intersection of education and public management.

Automotive engine innovation in Francoist Spain through the Sociedad de Técnicos de Automoción (STA), 1949-1974

In Spain, there exists a lack of historical-sociological approaches to the professional association of engineers of all kinds in general, and automotive engineers in concrete, due to the absence of any academic trend or school interested in studying the professions. For this reason, the purpose of this article is to examine the technological changes and development of automobile engines manufactured in Spain during the Francoist regime, based on the innovations of professionals working in the Spanish automotive industry explained by themselves. We part from a theoretical framework stated by Cultural History reflections on collective imaginations, which understands them as a mental or conscious frame that can be studied by researchers, to the extent that they are shared between all people taking part in any kind of human group as an identity issue: in our case, the Spanish automotive engineers. In addition, the methodology chosen is the study of historical scientific press, where the review of 32 articles written by engineers for the journal Revista de la STA and published by the Sociedad de Técnicos de Automoción (STA) between 1949 and 1974, provides a glimpse of these people’s collective imagination as they describe their inventions and the entire procedure to achieve them, bringing to light successful discoveries, problems, ill-fated attempts and concerns of all kinds. During the years of Francoist autarky, automotive engineers grappled with the great challenge of overcoming financial adversity and scarce resources to physically produce their innovations in engines, whereas during the developmentalist period, which enjoyed better socio-economic conditions following the Economic Stabilisation Plan of 1959, they undertook new experiments to produce increasingly sophisticated innovations. In its own way, automotive engineers’ work was therefore essential in promoting economic growth in Francoist Spain, leaving behind the poverty of the 1940s and 1950s for the consumer society of the 1960s and 1970s. Ultimately, the article concludes how the Revista de la STA, used as an historical primary source throughout the research, demonstrated its complete preference for innovations promoted by engineers related to automotive state-owned companies, leaving aside those ones from private companies.

BEYOND THE LENS: A BIBLIOMETRIC JOURNEY THROUGH ARCHITECTURAL PHOTOGRAPHY RESEARCH

This study presents a bibliometric analysis to map academic trends, collaborations, and thematic developments in architectural photography using VOSviewer and Biblioshiny software. Based on 470 publications retrieved from the Web of Science (WoS) database, the analysis explores the intellectual structure of architectural photography research through keyword co-occurrence, citation networks, and bibliometric coupling. The findings reveal a significant increase in academic interest over the past two decades, highlighting the growing interdisciplinary connections of the field with cultural heritage, digital visualization, and artificial intelligence applications. Cluster analysis identified eleven major thematic groups, including cultural heritage documentation, digital photogrammetry, AI-assisted visualization, and media representation. Country-level bibliometric coupling analysis shows that the United States is a dominant research hub with strong links to the United Kingdom, Canada, and Australia. At the same time, China and European countries demonstrate intensive regional collaborations. The study concludes that architectural photography is no longer limited to traditional documentation practices but is increasingly evolving into a research domain shaped by emerging technologies such as 3D modeling, LiDAR, and augmented reality. These findings offer valuable insights into emerging research directions such as computational photography, immersive visual storytelling, and interdisciplinary approaches to architectural documentation.

BioBERT-powered synergy: advanced bibliometric and molecular insights into prostate cancer bone metastasis.

Prostate cancer (PC) is a leading cause of male cancer mortality, with bone metastasis (BM) being a frequent and debilitating complication. Despite therapeutic advancements, the molecular mechanisms underlying BM remain poorly understood. This study aims to bridge this gap by integrating bibliometric analysis with bioinformatics to provide a comprehensive overview of the academic trends and molecular profiles associated with prostate cancer bone metastasis (PCBM). We conducted a bibliometric analysis to identify key contributors in PCBM research from 2004 to 2024 with advanced tools like BioBERT to mine gene and disease entities from the abstracts of relevant articles. Gene expression data from GSE32269 was analyzed to identify differentially expressed genes (DEGs), followed by enrichment analyses for biological functions and pathways. The bibliometric review showed an increasing trend in research output, focusing on therapeutic strategies and biomarkers. Bioinformatics analysis revealed various DEGs, significantly enriched in immune response and cell adhesion pathways. Semantic relationship analysis highlighted potential shared pathways between genes and diseases, offering clues for novel immunotherapy targets. By integrating bibliometric analysis with bioinformatics, this study provides new insights into PCBM. Specifically, our findings emphasize the impact of reprogramming on immune cells and its role in reshaping the tumor microenvironment to support cancer cells' evasion of immune surveillance and promotion of metastasis. These results suggest that targeting immune checkpoints and innovative combination therapies may be critical directions for improving outcomes in prostate cancer patients.

Exploring Academic Trends with Histograms, Linear Regression, and Correlation Matrix

In recent years, the field of education has seen a growing interest in the use of data mining techniques to improve teaching, learning, and administrative decision-making. Data mining refers to the process of uncovering hidden patterns, correlations, and useful information from large volumes of data. It involves applying various computational and statistical methods to analyze datasets that are often too complex or vast for traditional aanalysis methods. In the context of education, it can be used to analyze student performance, predict academic success, identify at-risk students, personalize learning paths, and improve curriculum design. By using classification algorithms, educational institutions can categorize student data and outcomes. This allows educators to develop targeted interventions and support systems that address individual student needs. Clustering techniques can group students by performance or engagement levels, offering insights into effective teaching strategies for different learner groups. Histograms, regression and correlative analysis can reveal broader trends, such as the impact of teaching methods or the effectiveness of online learning tools. These insights help institutions make data-driven decisions that enhance the overall educational experience. The present study analyzes a dataset of student registration numbers and their respective grades across all subjects. Alphabetic grades were converted to numeric values to facilitate analysis. Histograms of all subjects' grades were generated, followed by linear regression and a correlation matrix to identify relationships between subjects. The outputs include scatter plots for linear regression results and a correlation matrix for subject relationships.

Quantum Computing in Data Science and STEM Education: Mapping Academic Trends and Analyzing Practical Tools

Quantum computing is emerging as a key enabler of digital transformation in data science and STEM education. This study investigates how quantum computing can be meaningfully integrated into higher education by combining a dual approach: a structured assessment of the specialized literature and a practical evaluation of educational tools. First, a science mapping study based on 281 peer-reviewed publications indexed in Scopus (2015–2024) identifies growth trends, thematic clusters, and international collaboration networks at the intersection of quantum computing, data science, and education. Second, a comparative analysis of widely used educational platforms—such as Qiskit, Quantum Inspire, QuTiP, and Amazon Braket—is conducted using pedagogical criteria including accessibility, usability, and curriculum integration. The results highlight a growing convergence between quantum technologies, artificial intelligence, and data-driven learning. A strategic framework and roadmap are proposed to support the gradual and scalable adoption of quantum literacy in university-level STEM programs.

Unveiling AI’s impact in Rwandan higher education: navigating trends, challenges, and imperatives at the University of Rwanda

In the wake of the Covid-19 pandemic, which hastened the digitalization of education, the imperative to harness Artificial Intelligence (AI)'s potential has never been more pressing. While studies abound on the broader impact of technology in education, there remains a conspicuous gap in understanding its specific implications for African countries. These nations, historically marginalized in the discourse of technological advancement, confront unique challenges and opportunities in leveraging AI to advance their educational agendas. The objective of this contribution is to assess, and identify AI readiness with a focus on accompanying policy by an exemplary survey of academic practice at a East African higher education institution, the University of Rwanda. It encompasses three pivotal sections: an in-depth analysis of prevailing technological trends in academia, differentiating between AI and e-learning methodologies; an empirical investigation based on 32 responses of a structured online survey, featuring insights from teaching and research staff at the University of Rwanda; and an examination of policy implications informed by its findings, coupled with actionable recommendations to propel e-learning initiatives across Rwanda. The research questions address AI readiness on both the individual and the institutional level. Of exploratory nature, the theoretical framework is informed by the Technology Acceptance Model and constructive learning and interpretive theory. The results show that there is a perceived potential of AI that is particularly relevant for the African higher education context. It can enhance education through targeted and personalized learning, improve access to information, and facilitate research and teaching. There is, however, the need for regulatory frameworks and ethics considerations, more so that two response items are likely AI-generated.

Briefings

Assessing online learning through the community of inquiry lens New Study on Helping Students Master Virtual‐ and Augmented‐Reality Reading Skills Global Perspective on Academic Trends in Leadership Literature Review

Briefings

Assessing Online Learning through the Community of Inquiry LensNew Study on Helping Students Master Virtual‐ and Augmented‐Reality Reading SkillsGlobal Perspective on Academic Trends in Leadership Literature Review

Bibliometric Analysis on Academic Trend of Talent Development in Higher Education Institutions from 1999 – 2023

Talent development is an essential part of enhancing knowledge, engagement, and building a skilled employee that aligns with the organization’s goals. Talent development in higher education institutions focuses on nurturing knowledge, skills, and personal growth for preparing graduates that not only knowledgeable but also adaptable. This study utilizes extensive bibliometric analysis to discover and analyse 725 papers published in SCOPUS-indexed journals from 1999 to 2023. The findings indicate that research on talent development has escalated since 2000. This study delineates the temporal trends in publications and elucidates the prevailing research interests, as well as potential opportunities for future research.

Business translation research from the West and China

Abstract Business translation research has grown in importance worldwide. In the West, we have witnessed significant advances in the teaching and research of the field, broadening our understanding of its key areas and academic trends. However, the landscape of research in business translation in the East remains largely unknown to us. This article addresses this gap in our knowledge and explores the landscape of business translation research in the East, comparing it with Western research production. First, we compiled two bibliographic corpora: one from BITRA for the Western case and another from CNKI and CAOD for the Chinese case. We then analyzed both corpora using a series of bibliometric indicators (production, collaboration, scattering, and content). The results show that research in both corpora aligns to some extent with classical bibliometric laws (exponential growth, publication scattering, and author distribution), but there are also differences in content: while Western research reveals a diversity of objects of study, Chinese research appears to align with national foreign trade strategies.

Bibliometric Analysis of Research on Cyberbullying

The aim of this study is to conduct a bibliometric analysis of domestic theses on cyberbullying in Turkey, examining current academic trends, research methodologies, and key themes related to cyberbullying. The study employs the case study model, one of the qualitative research designs. The population of the study consists of theses on cyberbullying accessible in full text via the YÖK Thesis Database. The sample includes theses published in Turkish and/or English between 2020 and December 2024 (inclusive) and available in full text on the YÖK Thesis Database. A total of 116 theses were included in the analysis. Data were collected using the Academic Publication Assesment Form, and document analysis was applied for data analysis. The results of the study indicate that the majority of these were concentrated in 2024, with a predominance of master’s theses. Most of the theses were written in Turkish and were affiliated with universities such as Istanbul Gelişim, Gazi, Marmara, and Mersin. The findings also reveal that research predominantly focused on psychology, education, and sociology, employing quantitative methods and survey models. Frequently utilized tools included the Cyberbullying and Cyber Victimization Scales. Commonly explored variables were cyber victimization, empathy, academic achievement, and psychological well-being.

通園 兪晩柱의 史書 편찬 기획 및 실행 양상 연구

This study aims to examine Yū Manju's historical orientation contained in Heumyeong in a diachronic manner, and to empirically reveal the actual process and aspects of how he compiled historical texts based on available records. In the early days, the historiographical projects conceived by Yū Manju seems to have been conceived in various ways according to his needs and interests. Among these, Samgogyecheop and Samgang stand out as particularly significant because, unlike other projects, these were not just simple plans but were actually carried out to a meaningful extent. Notably, Yū Manju placed considerable importance on Samgang, and his commitment to it reveals a strong adherence to traditional Neo-Confucian historical views, as he primarily followed Zhu Xi’s Zizhi Tongjian Gangmu and favored the use of the Gangmu-style historiography. While Yū Manju initially focused on Chinese history and Gangmu-style historical writing, by his later years, his interests expanded to include the history of the Eastern Kingdom(Dongguk), and he began to conceive of various types of historical works, such as annals and biographical collections. This shift reflects a broadening of his historiographical scope, moving away from the Gangmu-focused approach of his early work. Notably, Yū Manju revised his earlier negative stance on Shiji, recognizing its historical value, which is evident in his later historiographical plans. Meanwhile, his ongoing exploration and compilation of Gangmu-style historical texts continued to deepen, so the later historiographical projects he planned did not lead to actual compilation. Yū Manju’s fundamental motivation for his dedication to historiography, and his ultimate aim, was to compile good books and leave a name for posterity. His planning of numerous large-scale historical books, including Samgang, stemmed largely from this spiritual environment, and is also related to the erudite academic trend of the 18th century when he lived. Within this spiritual and historical context, Yumanju consistently pursued historical study, creating a trajectory of self-reformation, and it is noteworthy that he eventually escaped from the Neo-Confucian philosophy centrality.

Evolutionary Review of Customary Land Based on Bibliometric Analysis in Scopus from 2000 to 2025

This paper explores the evolution of research on indigenous land from 2000 to 2025, addressing the gap in understanding academic trends, focus, and researcher collaboration. A bibliometric analysis was conducted using data from Scopus, covering 1,342 English-language research papers. The results reveal several key findings: the number of publications on indigenous land increased significantly between 2022 and 2024, with 103 new publications; citation trends showed a decline over several years, with a notable peak in 2017; Kuusaana ED, Azima AM, and Koczberski G emerged as the most prolific authors; major research topics focused on political economy, artisanal mining, livelihoods, urban areas, and government; frequently studied keywords included land tenure, land rights, land management, and landownership. Based on these findings, future research should focus on areas such as Indigenous population studies, forest management, and further exploration of land tenure and management.

Student Result Management System

The Student Result Management System (SRMS) is a web-based application designed to automate and streamline the process of managing and publishing student results efficiently. Traditional result management methods rely heavily on manual data entry, extensive paperwork, and time- consuming verification processes, which often lead to errors and inconsistencies. Our system provides an efficient, secure, and automated approach to handling student records, reducing administrative workload while improving accuracy and accessibility. By integrating a centralized database, the system ensures easy storage, retrieval, and management of academic results. The system is designed to cater to the needs of administrators, faculty, and students by providing role-based access control. Administrators can efficiently manage student data, input marks, and generate reports, while faculty members can update subject-specific scores and analyze student performance. Students can securely access their results online without the need for physical mark sheets, ensuring transparency and convenience. The RMS also includes an automated grading system, which calculates grades based on predefined criteria, minimizing human intervention and ensuring fairness in evaluation. The implementation of robust security measures, including authentication and encryption, ensures data privacy and protection against unauthorized access. Additionally, the RMS provides historical data analysis, allowing institutions to track academic trends and improve decision-making processes. With a user-friendly interface and responsive design, the system ensures seamless access across various devices, improving the overall user experience. Developed using modern web technologies, the Student Result Management System are designed for scalability and adaptability. It can be customized to fit the specific requirements of different educational institutions, making it a versatile solution for schools, colleges, and universities. By digitizing the result management process, this system significantly reduces paperwork, minimizes human errors, enhances operational efficiency, and promotes a more transparent and accessible.

Impacts of Competitive Pressure and Organizational Context on Organizational Structure: A Role of Knowledge Management

Recent trends in academia and the business community have seen a shift in focus in knowledge management (KM) issues from technology adoption to the interplay between organizational and technology management, with a special interest in the integration of KM technology and organizational design. Organizational structure is fundamental in this exploration as it encapsulates how an enterprise manages knowledge, communicates, allocates decision-making power, and implements control mechanisms, thereby portraying the efficacy of an organization’s operations. This study aims to formulate and test a theoretical model based on the Organizational Knowledge/Information Processing Model, examining the relationships between environmental pressure, organizational innovativeness, KM technology, organizational size, centralization, and formalization. Using a structural equation modeling approach, the study analyzed survey data collected from 220 companies to explore how these variables interact and influence each other. The analysis revealed that in response to competitive pressure, organizations primarily employ KM systems, centralization, and formalization. Additionally, KM systems were found to act as mediators, enhancing both centralization and formalization within the organizations. The study concludes that competitive pressure drives organizations to adopt KM systems, which in turn facilitate increased centralization and formalization. This highlights the critical role of KM technology in shaping organizational structure and processes, ultimately impacting the effectiveness of organizational operations.

Can We Measure and Analyze Structural Racism in the Study of Health?

ABSTRACTIn this paper, we critique the concept of structural racism as a determinant of health, as it is operationalized in quantitative research. Our review is not a defense of the concept but a critical examination. From this review, we share several different areas for methodological innovations, including identifying macro‐micro‐macro linkages, and measuring the absence of structural racism, versus assuming it is uniformly present in all social environments. Our review finds that the literature on structural racism is, for the most part, “walking backwards into the future,” rebranding established methods and measures with an innovative term of art, without creating new research designs, measures, methods and analyses. Therefore, we offer the following overarching criticism: researchers have not yet built a study of structural racism around methods that disclose this phenomenon in ways we did not previously understand. We posit that unless researchers can provide clearer and more innovative operationalizations of this concept, it and measurement of the phenomena, is likely to fade into obscurity as academic trends shift.

전공자율선택제도 기반의 트랙 간 관계 및 키워드 간 결합도 가중네트워크 분석: 교육과정 프로파일링 기법(Curriculum Profiling Method)을 활용하여

This study aims to examine whether there have been changes in the evolving interrelationship between tracks (majors) and the extent of interconnectivity among course-related keywords in accordance with the Ministry of Education's policy (2024) to expand the Self-Directed Major Selection, which promotes learner-centered convergence education and enhances the flexibility of the major system in universities. To this end, a comparative analysis was conducted to examine interdisciplinary integration tendencies and the degree of keyword association by analyzing a total of 13,567 major curriculum guides and 1,805 keywords across 6,478 courses from H University’s major curriculum over the 2018 to 2024 academic years. The course profile keywords associated with the tracks for each academic year were used to quantify the thematic connection between tracks, based on the extent to which the same keywords were similarly used across courses within two tracks, employing the “Curriculum Profiling Method.” The principal findings of the study are as follows: First, there was a structural change in the relationships between tracks in accordance with the Self-Directed Major Selection. Second, the study affirms that current academic trends, as well as societal and industrial imperatives, are increasingly reflected in the shared thematic areas across major curricula. Third, it underscores the necessity for a more nuanced, data-driven approach to research, along with the establishment of supportive frameworks to facilitate the interdisciplinary integration of disparate academic fields.

Analyzing Citation Dynamics and Forecasting Academic Trends: A Multi-Criteria Decision-Making Approach Using ARIMA and AHP

and employs forecasting models to predict future publication trends. Citation dynamics are critical in bibliometric studies because they influence research visibility and academic recognition. Using a dataset of 505 academic publications from Scopus, this study applies correlation analysis, time-series forecasting (ARIMA), and multi-criteria decision-making (MCDM) techniques, particularly the Analytic Hierarchy Process (AHP). Pearson’s correlation analysis revealed a weak negative correlation ((r = -0.154)) between publication year and citation count, indicating that older publications tended to have more citations, but other factors significantly influenced citation accumulation. Time-series forecasting using ARIMA (1,1,1) and Holt’s Exponential Smoothing Model evaluated future publication trends, with ARIMA demonstrating higher short-term accuracy. The AHP model ranks research papers based on citation count, publication year, and relevance to MCDM, assigning higher weights to the citation count (63.3%)). This study highlights the evolving role of artificial intelligence and big data analytics in bibliometric analysis and underscores the need for hybrid models that integrate machine learning techniques with traditional decision-support frameworks. Future research should incorporate journal impact factors, author reputation, and open-access status to refine the citation prediction models. The findings contribute to a data-driven understanding of academic influence, providing insights for researchers, policymakers, and institutions aiming to enhance research visibility and scholarly impact.