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Korean J Med Educ > Volume 36(2); 2024 > Article
Yune and Park: Analyzing research trends after the international journal transition of the Korean Journal of Medical Education: using topic modeling techniques



This study aimed to analyze the research trends of the Korean Journal of Medical Education (KJME) since it became an English-language journal.


A total of 274 articles published in KJME from 2016 to 2023 were analyzed. All article types were included in the analysis. NetMiner ver. 4.0 (Cyram Inc., Korea) was used for the main keyword and topic modeling analysis.


Of the 274 articles, 170 (62%) and 104 (38%) were by domestic and international authors, respectively. The main keywords with high frequency were “students,” “learning,” “experience,” “pandemic,” and “perception.” Three topics were derived using topic matching analysis: “residents’ perception and attitude of the pandemic,” “assessment of learning and achievement,” and “learning experiences in the pandemic.”


Since the shift to English-language journals, medical education research has witnessed an increase in the number of articles published by international authors. Research on postgraduate education has increased. Research topics are relevant to situations such as the coronavirus disease 2019 pandemic. These findings can help researchers select research topics and encourage them to submit their research to the journal.


Korean Journal of Medical Education (KJME) has become a leading journal in Korea since its founding in 1989. By disseminating research findings to medical educators, KJME has significantly contributed to medical education research and practice in Korea. A major achievement of KJME was its inclusion in the MEDLINE index in 2015 and its transition to English-language publications in 2016, which allowed it to expand its exchanges with international researchers [1]. This was not just a language change to English but the beginning of an effort to gain international recognition and engage in international scholarly exchange [2].
Owing to this development, several studies have been conducted to analyze research trends in KJME publications. Original articles published by KJME from 2000 to 2004 were compared with those published in the major foreign journals the Academic Medicine and the Medical Teacher [3]. Unlike these journals, KJME has consistently published research in the field of educational administration, whereas research on curriculum, faculty development, and evidence-based medicine is relatively rare. In addition, a study, which analyzed 386 articles published from the first issue through 2010, differed from previous studies in that it analyzed trends in research methods [4]. Quantitative research methods and survey research were more prominently published compared with experimental research. Another study used social network analysis to analyze research trends before and after the introduction of the educational system for graduate medical schools in 2005 [5]. After their introduction to graduate medical schools, the research topics were diversified by adding new topic groups, such as patient safety, teaching evaluation, human resources, and educational paradigms. In addition, the research trends of factors related to the cognitive and definitional characteristics of students after the introduction of graduate medical schools increased significantly. Recently, a comparative analysis of articles published between 2010 and 2019 in KJME and the Korean Medical Education Review, two representative journals in Korea, was conducted using keyword network analysis [6]. In both journals, keywords related to curriculum and medical students were identified as highly influential topics in medical education research. Previous research trend analyses of journals have used a variety of approaches, including different publication years, different analysis criteria, and new statistical analysis methods, such as keyword network analysis. The research trend analysis of these journals can be used to predict the development direction of the field by reviewing the research performance and patterns and interpreting their value.
In this study, we analyzed research trends based on articles published between 2016 and 2023, the period when KJME changed to an English-language journal to take a leap forward to become a globally recognized journal, enhance its status as an internationally renowned journal, and explore the future development of the medical education research field.


1. Data collection

The study included 274 articles published between 2016 and 2023, when the KJME was converted to an international journal. All article types were included in the analysis. Due to the small number of articles analyzed, the analysis was not broken down by type. The research fields were analyzed using the subject classifications submitted by the authors at the time of publication, and the frequencies of the Korean and international authors’ research fields were analyzed. The titles of articles were used for network analysis because they most closely represent the content and key themes of the study, which is beneficial for quickly extracting and visualizing important information from complex datasets [7]. For keyword network analysis, we used the NetMiner ver. 4.0 program (Cyram Inc., Seongnam, Korea). A total of 225 keywords were extracted from the titles of articles and preprocessing was performed to prepare the keyword data. Keyword preprocessing is the process of extracting the final 200 words by removing noun-like words that are not suitable for analysis, such as words that appear less than twice or words that are not appropriate for analysis, such as the names of places and organizations. And common words (term frequency-inverse document frequency <0.05) that occurred frequently in all documents were removed.

2. Analysis method

Using NetMiner ver. 4.0 program (Cyram Inc.), 25 words with a high frequency of simple occurrences and number of articles were selected. Topic modeling analysis was then performed using a topic modeling plug-in. Topic modeling is a method to estimate topics from the associations of multiple words. In this study, we exploratively used a plug-in of NetMiner ver. 4.0 (Cyram Inc.) to extract topics using the latent Dirichlet allocation algorithm. Among the topics derived from the topic modeling results, we set five keywords that best described the identity of each topic. We named the topic groups based on the keywords that accounted for the top probability distribution for each topic.


1. Research fields of Korean and international authors

Of the 274 papers published, 170 (62%) were published by domestic authors and 104 (38%) by international authors. Among international authors, Indonesia (21, 7.7%), India (15, 5.5%), Singapore (11, 4.0%), and Iran (9, 3.3%) published the highest number of articles in KJME. Overall, except for “others,” both Korean and international authors were more interested in “professionalism,” “educational curriculum,” “educational evaluation,” and “e-learning.” Korean authors were more interested in “team-based learning (TBL),” “problem-based learning (PBL),” and “communication” than international authors (Table 1).

2. Topic modeling

The 25 words with the highest frequency and number of articles are listed in Table 2. “Student,” “learning,” “experience,” “pandemic,” and “awareness” were the most frequent words, in that order. The number of topics in the articles published in KJME was determined to be three for interpretability. The predominant keywords for Topic 1 included “pandemic,” “perception,” “resident,” and “attitude,” correlating with 39 studies. In contrast, Topic 2 featured “learning,” “experience,” “pandemic,” “perspective,” and “relationship,” associated with 50 studies, while Topic 3 comprised “learning,” “performance,” “health,” “assessment,” and “examination,” linked to 191 studies. We named the topic groups by their core keywords: Topic 1 as “residents’ perception and attitude towards the pandemic”; Topic 2 as “assessment of learning and achievement”; and Topic 3 as “learning experiences during the pandemic.” The visualization of the network incorporating seven central keywords from these topics, presented as a spring map (topic-keyword map), is depicted in Fig. 1.


This study analyzed the changes in authors’ research fields, areas, and topics since KJME switched to an English-language journal in 2016.
Of the 274 articles, 170 (62%) were published by domestic authors and 104 (38%) by international authors. In particular, the number of articles written by international authors surpassed that of domestic authors after 2023, indicating that the journal is gradually becoming an international journal with authors of different nationalities. This suggests that in the early stages of an international journal, the contributions and interests of local authors can be beneficial for publication [8].
In terms of research fields, there have been many studies on “professionalism,” “educational curricula,” “educational evaluations,” and “e-learning.” This is partially consistent with previous findings that curricula, methods, and educational evaluations accounted for approximately 67% of all articles [4]. This trend did not significantly change after switching to an English journal. However, communication-related research has increased dramatically since 2006 [4,6], and this trend continues. However, in contrast to previous studies, we found that the field of e-learning began to grow gradually after 2019. This may be because the shift to online education as an alternative to ensuring the continuity of the teaching-learning process in medical education during the coronavirus disease 2019 (COVID-19) crisis was essential [9]. This paradigm shift may have been reflected in both domestic and international research topics. Conversely, domestic authors mainly conducted research on “TBL,” “PBL,” and “communication.” Even before the transition to English-language journals, research on the application of educational methods, such as TBL and PBL, and the field of communication was conducted extensively [4,6], indicating that these topics continue to be of interest to researchers.
The main keywords with high frequency were “students,” “learning,” “experience,” “pandemic,” and “perception.” Since 2016, medical education research has largely focused on medical students and their learning. Studies investigating their experiences and perceptions remain important. However, compared with research topics in international journals, faculty development for faculty members is an important research topic yet to receive significant attention in KJME [3]. Therefore, given the internationalization of journals, research in this area needs to be expanded.
For a more meaningful interpretation through the combination of the main keywords, topic modeling analysis was conducted, and three topics were derived. Topic modeling is a statistical inference method that extracts topics from large amounts of unstructured text using contextual cues [10]. Topic 1 is “residents’ perception and attitude of the pandemic.” This represents an expansion of research topics in the field of postgraduate education, which have been understudied in previous studies [4]. Topic 2 was “assessment of learning and achievement,” which is primarily related to the assessment of medical students’ learning and performance. This is a basic research topic even after the transition to English-language papers, and is an important topic of interest for all researchers. Finally, Topic 3 is “learning experiences in the pandemic,” which is about the COVID-19 pandemic and learning experiences. The analysis of global research trends in the COVID-19 era is consistent with the finding that most research has been published on education [11]. The COVID-19 pandemic has caused changes in the field of education, which has become a major topic of interest for researchers. Based on these research trends, it would be beneficial for KJME to develop into an internationally renowned journal by attracting the interest of domestic and international researchers and increasing its visibility through strategies such as publishing special issues focusing on the latest research topics including special situations such as the COVID-19 pandemic, new models of medical education, and innovative teaching and learning methods; Inviting internationally renowned scholars in these fields to contribute would also be beneficial.
This study analyzed research trends in the early stages of KJME’s development into an internationally renowned journal; it is necessary to further refine and compare research trends in the period after the number of publications increased. These results can help medical education researchers select research topics and encourage their submissions to journals. In the future, an integrated analysis of the journal’s publishing operations, including citation analysis and measures to increase the number of published articles, could help prepare the journal for internationalization.




No financial support was received for this article.
Conflicts of interest
So Jung Yune and Kwi Hwa Parkserve as an Editorial Board members of the Korean Journal of Medical Education but have no role in the decision to publish this article. Except for that, no potential conflict of interest relevant to this article was reported.
Author contributions
SJY and KHP conceptualized the study, developed the proposal, coordinated the project, and completed the initial data entry. SJY wrote the original draft. SJY and KHP analyzed and interpreted the data and editing the final report. KHP participated in the overall supervision of the project and revision of the report.

Fig. 1.
Topic Modeling Network: Topic Keyword Map
Table 1.
Research Fields of Korean and International Authors
Field 2016
Communication 1 (3.6) 1 (6.3) - - 4 (16.0) 0 2 (9.5) 1 (7.7) - 1 (7.7) 1 (5.3) 1 (7.7) 1 (5.6) - - - 9 (5.3) 4 (3.8)
E-learning - 1 (6.3) - 2 (28.6) - - 1 (4.8) 1 (7.7) 1 (4.8) 2 (15.4) 3 (15.8) 3 (23.1) 2 (11.1) 2 (18.2) 3 (18.8) 4 (21.1) 10 (5.9) 15 (14.4)
Educational Curriculum - 3 (18.8) 1 (4.5) - 2 (8.0) 4 (33.3) 3 (14.3) 1 (7.7) 3 (14.3) - 2 (10.5) 1 (7.7) 2 (11.1) 1 (9.1) 2 (12.5) 6 (31.6) 15 (8.8) 16 (15.4)
Educational Evaluation 3 (10.7) 3 (18.8) 1 (4.5) - 2 (8.0) 2 (16.7) 4 (19.0) 3 (23.1) 1 (4.8) 2 (15.4) - - - 2 (18.2) 4 (25.0) 3 (15.8) 15 (8.8) 15 (14.4)
OSCE/CPX/Standardized Patient 4 (14.3) - 1 (4.5) - 1 (4.0) - - - 3 (14.3) - - 1 (7.7) - - - - 9 (5.3) 1 (1.0)
PBL 2 (7.1) 1 (6.3) 2 (9.1) - 1 (4.0) - - 1 (7.7) - - - - - - - - 5 (2.9) 2 (1.9)
TBL - - 1 (4.5) - 1 (4.0) - - - 1 (4.8) - - - - - - - 3 (1.8) -
Professionalism 4 (14.3) 4 (25.0) 3 (13.6) - 2 (8.0) - 6 (28.6) 1 (7.7) - - 2 (10.5) - 3 (16.7) 2 (18.2) 4 (25.0) 6 (31.6) 24 (14.1) 13 (12.5)
Teaching and Learning Methods 3 (10.7) 1 (6.3) 4 (18.2) 1 (14.3) 5 (20.0) 4 (33.3) 2 (9.5) - 4 (19.0) 2 (15.4) 5 (26.3) 2 (15.4) 4 (22.2) 1 (9.1) - - 27 (15.9) 11 (10.6)
Others 11 (39.3) 2 (12.5) 9 (40.9) 4 (57.1) 7 (28.0) 2 (16.7) 3 (14.3) 5 (38.5) 8 (38.1) 6 (46.2) 6 (31.6) 5 (38.5) 6 (33.3) 3 (27.3) 3 (18.8) 0 53 (31.2) 27 (26.0)
Total 28 (100.0) 16 (100.0) 22 (100.0) 7 (100.0) 25 (100.0) 12 (100.0) 21 (100.0) 13 (100.0) 21 (100.0) 13 (100.0) 19 (100.0) 13 (100.0) 18 (100.0) 11 (100.0) 16 (100.0) 19 (100.0) 170 (100.0) 104 (100.0)

Data are presented as number (%).

DA: Domestic author, IA: International author, OSCE: Objective structured clinical examination, CPX: Clinical performance examination, PBL: Problem-based learning, TBL: Team-based learning.

Table 2.
Rank of Keywords by Frequency in Research
No. Keyword Frequency Appearance frequency in research
1 Student 125 121
2 Learning 30 27
3 Experience 19 19
4 Pandemic 17 17
5 Perception 16 16
6 Perspective 14 14
7 Health 12 12
8 Performance 11 11
9 Patient 11 11
10 Development 11 11
11 Training 10 9
12 Resident 10 9
13 Relationship 10 10
14 Effect 10 9
15 Attitude 10 10
16 Skill 9 9
17 Evaluation 9 9
18 Curriculum 9 9
19 Satisfaction 8 8
20 Assessment 8 8
21 Development 8 8
22 Teaching 7 6
23 Need 7 7
24 Model 7 7
25 Examination 7 7


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