• Journal of Fisheries and Marine Sciences Education
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• v.29 no.1
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• pp.224-233
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• 2017

This study aims to analyze the research trend of lifelong education in Korea over the last 10 years based on social network analysis. To do this, a dataset has been collected from KCI (Korea Citation Index) database. According to the results of the study, firstly, the current status of lifelong education research by the year in the last 10 years showed a relatively high ratio between 2008 and 2009 and 2014 ~ 2015. Secondly, the most active networks between authors and journals constitute a key group in the order of 'Lifelong Education Study' and 'Lifelong Learning Society'. Thirdly, the research institutes with the largest number of lifelong education research papers are Soongsil University, Dong-Eui University, and Korea National Open University. In the network with the authors' network, the only authors were K8 working at Chonbuk National University, and the co-authors, H4, who works at Kyungpook National University, showed the most active network. Finally, the core keyword network based on the thesis topic was analyzed as having higher connection centrality in the order of 'lifelong education', 'lifelong educator', and 'university lifelong education'.

• Human Ecology Research
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• v.56 no.6
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• pp.603-617
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• 2018

This study analyzed research trends in the field of Practical Arts (Technology & Home Economics) education. From 958 articles published between 2010 and 2018 in the Journal of Korean Practical Arts Education (JKPAE), Journal of Korean Home Economics Education Association (JHEEA), and Korean Journal of Technology Education Association (KJTEA), 958 keywords were extracted and analyzed using NetMiner 4. When the general network structure was analyzed, keywords such as practical arts education, curriculum, textbook, home economics education, and students were high in the degree centrality and closeness centrality, and textbook, practical arts education, curriculum, student, home economics education, and invention were high in the node betweenness centrality. The cluster analysis showed that a four-cluster solution was most appropriate: cluster 1, technology and experiential learning activities; cluster 2, curriculum studies and practical problem; cluster 3, relationships; and cluster 4, creativity and character education. The three journals showed differences in the knowledge network structure: The topics of JKPAE and JKHEEA focused on general content knowledge and curriculum, while the topics of KJTEA were spread across invention and creativity education, and curriculum studies.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.4
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• pp.27-31
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• 2023

Purpose: This study analyzed papers identified by entering the two keywords 'unification education' and 'university' during research from 2013 to 2022 in order to identify trends and key concepts in unification education research at domestic universities. Research design, data, and methodology: The study analyzed 224 papers, excluding those on primary, middle, and high school unification education, as well as unrelated and duplicate papers. The analysis included developing a co-occurrence network of keywords, utilizing topic modeling to categorize research types, and confirming visualizations such as word clouds and sociograms. Results: In the final analysis, the research identified 1,500 keywords, with notable ones like 'Korea,' 'education,' 'unification.' Centrality analysis, measuring influence through connected keywords, revealed that 'Korea,' 'education,' 'north,' and 'unification' held significant positions. Keywords with high centrality compared to their frequency included 'learning,' 'development,' 'training,' 'peace,' and 'language,' in that order. Conclusions: This study investigated trends and structures in university-level unification education by analyzing papers identified with the keywords 'unification education' and 'university.' The use of keyword network analysis aimed to elucidate patterns and structures in university-level unification education. The significance of the study lies in offering foundational data for future research directions in the field of unification education at universities.

• Korean Medical Education Review
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• v.23 no.3
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• pp.176-184
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• 2021

The aim of this study was to analyze the research trends in articles published in the Korean Journal of Medical Education (KJME) and Korean Medical Education Review (KMER) using keyword network analysis. The analyses included 507 papers from 2010 to 2019 published in KJME and KMER. First, keyword frequency analysis showed that the research topics that appeared in both journals were "medical student," "curriculum," "clinical clerkship," and "undergraduate medical education." Second, centrality analysis of a network map of the keywords identified "curriculum" and "medical student" as highly important research topics in both journals. Third, a cluster analysis of 20 core keywords in KMER identified research clusters related to academic motivation, achievement, educational measurement, medical competence, and clinical practice (centered on "learning," while in KJME, clusters were related to educational method and program evaluation, medical competence, and clinical practice (centered on "teaching"). In conclusion, future medical education research needs to expand to encompass other research areas, such as educational methods, student evaluations, the educational environment, student counseling, and curriculum.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.872-880
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• 2016

The purpose of this study is to find the research trends relating to flipped learning through keyword network analysis. For investigating this topic, final 100 papers (removed due to overlap in all 205 papers) were selected as subjects from the result of research databases such as RISS, DBPIA, and KISS. After keyword extraction, coding, and data cleaning, we made a 2-mode network with final 202 keywords. In order to find out the research trends, frequency analysis, social network structural property analysis based on co-keyword network modeling, and social network centrality analysis were used. Followings were the results of the research: (a) Achievement, writing, blended learning, teaching and learning model, learner centered education, cooperative leaning, and learning motivation, and self-regulated learning were found to be the most common keywords except flipped learning. (b) Density was .088, and geodesic distance was 3.150 based on keyword network type 2. (c) Teaching and learning model, blended learning, and satisfaction were centrally located and closed related to other keywords. Satisfaction, teaching and learning model blended learning, motivation, writing, communication, and achievement were playing an intermediary role among other keywords.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.154-163
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• 2022

The purpose of this paper is to illuminate the role and importance of National Research & Education Network (NREN) in the national research and education field and to establish the future strategy of KREONET in Korea. To this end, we first carefully analyze the footsteps of NREN in major overseas countries, KREONET achievements, and future demand for KREONET. The history of NREN's development is divided into the 2000s, 2010s, and present by era, and classified into network infrastructure, network service, and next-generation network technology by subject. KREONET achievements are divided into advanced research support, network backbone and operation, and network service. Future demand analysis of users who use KREONET was conducted through Korea Research International Incorporation, a survey company. This paper presents the future development strategy of KREONET by analyzing KREONET achievements and future demand.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.21-45
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• 2023

This study presents a machine learning program designed to identify impactful papers in the field of mathematics education. To achieve this objective, we examined the impact of papers from a scientific econometrics perspective, developed a mathematics education research network, and defined the impact of mathematics education research using PageRank, a network centrality index. We developed a machine learning model to determine the impact of mathematics education research and identified the journals with the highest percentage of impactful articles to be the Journal for Research in Mathematics Education (25.66%), Educational Studies in Mathematics (22.12%), Zentralblatt für Didaktik der Mathematik (8.46%), Journal of Mathematics Teacher Education (5.8%), and Journal of Mathematical Behaviour (5.51%). The results of the machine learning program were similar to the findings of previous studies that were read and evaluated qualitatively by experts in mathematics education. Significantly, the AI-assisted impact evaluation of mathematics education research, which typically requires significant human resources and time, was carried out efficiently in this study.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.145-152
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• 2022

One of the impacts of Covid-19 on education systems has been the shift to online education. This shift has changed the way education is consumed and perceived by students. However, the exact nature of student perception about online education is not known. The aim of this study was to understand the perceptions of Saudi higher education students (e.g., post-school students) about online education during the Covid-19 pandemic. Various aspects of online education including benefits, features and cybersecurity were explored. The data collected were analysed using statistical techniques, especially artificial neural networks, to address the research aims. The key findings were that benefits of online education was perceived by students with positive experience or when ensured of safe use of online platforms without the fear cyber security breaches for which recruitment of a cyber security officer was an important predictor. The issue of whether perception of online education as a necessity only for Covid situation or a lasting option beyond the pandemic is a topic for future research.

• The Mathematical Education
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• v.52 no.4
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• pp.483-496
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• 2013

In this study, we investigated the structure of the mathematics education scholars' co-authorship relationship in papers registered at the National Research Foundation of Korea by social network analysis. The data were 354 scholars from 257 papers in 4 journals from 2009 to 2013 based on 'the 2009 revised Korean National Curriculum'. For the analysis, Pajek3 and UCINET6.3 were used. The results of this study were as follows: First, each of the mathematics education scholars is connected on average with about 5 paths of intermediate collaborators. Second, Analyses of the first component group found distinguishable scholar groups' characteristics depending on their affiliations, majors, and job statuses. Third, there were scholars having high values in network degree centrality measures despite not having high numbers in published papers. On the contrary, there sere scholars having high numbers in published papers despite not having high values in network analysis. Finally, I suggested the directions for the future research with the limitations of this study.

• Korean Journal of Childcare and Education
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• v.20 no.1
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• pp.91-111
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• 2024

Objective: The purpose of this study is to explore trends in institutional evaluation research in early childhood education through keyword network analysis. This aims to understand trends in academic discourse on institutional evaluation and gain implications for follow-up research and related policy directions. Methods: A total of 6,629 keywords were extracted from 572 dissertations and journal articles published from January 2006 to October 2023 for the purpose of analyzing and visualizing the frequency and centrality of keywords, as well as the structural properties of keyword networks. The analysis and visualization were conducted using the TEXTOM, UCINET6, and NetDraw programs. Results: First, the number of institutional evaluation studies increased steadily from 2006 to 2010 and then decreased, with a higher frequency of studies on daycare centers compared to kindergartens. Second, the most frequently occurring keyword in the analysis was 'daycare center,' and the highest connection strength was found in the term 'daycare-center-evaluation.' Third, network analysis revealed that key terms for institutional evaluation research included 'evaluation certification,' 'recognition,' 'evaluation indicators,' 'teacher,' 'daycare center,' and 'kindergarten.' In the ego network analysis for each institution, 'parent' emerged as a highly ranked keyword. Conclusion/Implications: This study confirmed the perspectives of previous studies by revealing the structure of core concepts in early childhood education institution evaluation research, and provided implications for follow-up and direction of institution evaluation