Science Editing

Most-read articles are from the articles published in 2023 during the last three month.

Reviews

Research ethics and issues regarding the use of ChatGPT-like artificial intelligence platforms by authors and reviewers: a narrative review: Sang-Jun Kim; Sci Ed. 2024;11(2):96-106. Published online August 20, 2024; DOI: https://doi.org/10.6087/kcse.343

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While generative artificial intelligence (AI) technology has become increasingly competitive since OpenAI introduced ChatGPT, its widespread use poses significant ethical challenges in research. Excessive reliance on tools like ChatGPT may intensify ethical concerns in scholarly articles. Therefore, this article aims to provide a comprehensive narrative review of the ethical issues associated with using AI in academic writing and to inform researchers of current trends. Our methodology involved a detailed examination of literature on ChatGPT and related research trends. We conducted searches in major databases to identify additional relevant articles and cited literature, from which we collected and analyzed papers. We identified major issues from the literature, categorized into problems faced by authors using nonacademic AI platforms in writing and challenges related to the detection and acceptance of AI-generated content by reviewers and editors. We explored eight specific ethical problems highlighted by authors and reviewers and conducted a thorough review of five key topics in research ethics. Given that nonacademic AI platforms like ChatGPT often do not disclose their training data sources, there is a substantial risk of unattributed content and plagiarism. Therefore, researchers must verify the accuracy and authenticity of AI-generated content before incorporating it into their article, ensuring adherence to principles of research integrity and ethics, including avoidance of fabrication, falsification, and plagiarism.

Citations

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Generative Artificial Intelligence Tools in Journal Article Preparation: A Preliminary Catalog of Ethical Considerations, Opportunities, and Pitfalls
Robin R. White
JDS Communications.2025;[Epub] CrossRef
Ethics For Responsible Data Research: Integrating Cybersecurity Perspectives In Digital Era
Sheetal Temara
SSRN Electronic Journal.2025;[Epub] CrossRef
Ethical guidelines for the use of generative artificial intelligence and artificial intelligence-assisted tools in scholarly publishing: a thematic analysis
Adéle da Veiga
Science Editing.2025; 12(1): 28. CrossRef
Understanding haze data contestations in Singapore: between accuracy and affect
Nurul Amillin Hussain
Environmental Sociology.2025; : 1. CrossRef
Artificial intelligence-assisted academic writing: recommendations for ethical use
Adam Cheng, Aaron Calhoun, Gabriel Reedy
Advances in Simulation.2025;[Epub] CrossRef
How is ChatGPT acknowledged in academic publications?
Kayvan Kousha
Scientometrics.2024; 129(12): 7959. CrossRef
Appliances of Generative AI-Powered Language Tools in Academic Writing: A Scoping Review
Lilia Raitskaya, Elena Tikhonova
Journal of Language and Education.2024; 10(4): 5. CrossRef

The current state of graphical abstracts and how to create good graphical abstracts: Jieun Lee, Jeong-Ju Yoo; Sci Ed. 2023;10(1):19-26. Published online February 16, 2023; DOI: https://doi.org/10.6087/kcse.293

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677 Download
7 Web of Science
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Abstract PDF

Graphical abstracts (GAs), also known as visual abstracts, are powerful tools for communicating complex information and ideas clearly and concisely. These visual representations aim to capture the essential findings and central message of a research study, allowing the audience to understand and remember its content quickly. This review article describes the current state of GAs, including their benefits, limitations, and future directions in the development of GAs. It also presents methods and tips for producing a GA. In Korea, more than 10 medical journals have introduced GAs from 2021 to 2022. The number of citations was higher in articles with GAs than in those without GAs in the top 10 gastroenterology journals. There are five types of GAs: conceptual diagrams, flowcharts, infographics, iconographic abstracts, and photograph-like illustrations. A limitation of the GA system is the absence of a universal standard for GAs. The key steps for creating a GA are as follows: (1) start by identifying the main message; (2) choose an appropriate visual style; (3) draw an easy-to-understand graphic; (4) use colors and other design elements; and (5) request feedback. Available tools that are useful for creating GAs include Microsoft PowerPoint, Mind the Graph, Biorender, and Canva. Another effective method is collaborating with experts. Artificial intelligence will soon be able to produce GAs more efficiently from raw data or manuscripts, which will help researchers draw GAs more easily. GAs have become a crucial art for researchers to master, and their use is expected to expand in the future.

Citations

Citations to this article as recorded by

Decoding Research with a Glance: The Power of Graphical Abstracts and Infographics
Madhan Jeyaraman, Naveen Jeyaraman, Swaminathan Ramasubramanian, Abhishek Vaish, Raju Vaishya
Apollo Medicine.2025; 22(2): 144. CrossRef
Visualizing medicine: The case for implementing graphical abstracts in clinical reporting
Naveen Jeyaraman, Madhan Jeyaraman, Swaminathan Ramasubramanian, Sangeetha Balaji, Arulkumar Nallakumarasamy
World Journal of Methodology.2025;[Epub] CrossRef
BİLİMSEL YAYINLARDA KULLANILAN GÖRSEL ÖZETLERİN TASARIM İLKELERİ VE GÖRSEL ALGI KURAMLARI BAĞLAMINDA İNCELENMESİ
Arzu Gürdal
Stratejik ve Sosyal Araştırmalar Dergisi.2025; 9(1): 61. CrossRef
Ideational interplay of textual and visual elements in graphical abstracts of biology research articles
Junqiang Ren, Jiajin Xu
English for Specific Purposes.2025; 78: 156. CrossRef
Science Communication at Historical Biology
Jack A. Cooper
Historical Biology.2025; : 1. CrossRef
Embracing graphical abstracts in European Radiology
Brendan S. Kelly
European Radiology.2025;[Epub] CrossRef
Your message in pictures – Adding a graphical abstract to your paper
Péter Pongrácz, Irene Camerlink
Applied Animal Behaviour Science.2023; 263: 105946. CrossRef
Current status and demand for the advancement of Clinical Endoscopy: a survey-based descriptive study
Tae Hoon Lee, Jimin Han, Gwang Ha Kim, Hyejin Han
Science Editing.2023; 10(2): 135. CrossRef

Influence of artificial intelligence and chatbots on research integrity and publication ethics: Payam Hosseinzadeh Kasani, Kee Hyun Cho, Jae-Won Jang, Cheol-Heui Yun; Sci Ed. 2024;11(1):12-25. Published online January 25, 2024; DOI: https://doi.org/10.6087/kcse.323

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359 Download
7 Web of Science
7 Crossref

Abstract PDF

Artificial intelligence (AI)-powered chatbots are rapidly supplanting human-derived scholarly work in the fast-paced digital age. This necessitates a re-evaluation of our traditional research and publication ethics, which is the focus of this article. We explore the ethical issues that arise when AI chatbots are employed in research and publication. We critically examine the attribution of academic work, strategies for preventing plagiarism, the trustworthiness of AI-generated content, and the integration of empathy into these systems. Current approaches to ethical education, in our opinion, fall short of appropriately addressing these problems. We propose comprehensive initiatives to tackle these emerging ethical concerns. This review also examines the limitations of current chatbot detectors, underscoring the necessity for more sophisticated technology to safeguard academic integrity. The incorporation of AI and chatbots into the research environment is set to transform the way we approach scholarly inquiries. However, our study emphasizes the importance of employing these tools ethically within research and academia. As we move forward, it is of the utmost importance to concentrate on creating robust, flexible strategies and establishing comprehensive regulations that effectively align these potential technological developments with stringent ethical standards. We believe that this is an essential measure to ensure that the advancement of AI chatbots significantly augments the value of scholarly research activities, including publications, rather than introducing potential ethical quandaries.

Citations

Citations to this article as recorded by

Meeting report on the 8th Asian Science Editors’ Conference and Workshop 2024
Eun Jung Park
Science Editing.2025; 12(1): 66. CrossRef
Research and publication ethics with generative artificial intelligence-assisted tools
Cheol-Heui Yun
Science Editing.2025; 12(1): 1. CrossRef
The assisted Technology dilemma: a reflection on AI chatbots use and risks while reshaping the peer review process in scientific research
Helmi Ben Saad, Ismail Dergaa, Hatem Ghouili, Halil İbrahim Ceylan, Karim Chamari, Wissem Dhahbi
AI & SOCIETY.2025;[Epub] CrossRef
Plagiarism in the system of academic integrity in medical research (part 2)
M.V. Krasnoselskyi, N.O. Artamonova, О.М. Sukhina, T.V. Rublova, Yu.V. Pavlichenko
Український радіологічний та онкологічний журнал.2025; 33(1): 113. CrossRef
Generative AI, Research Ethics, and Higher Education Research: Insights from a Scientometric Analysis
Saba Mansoor Qadhi, Ahmed Alduais, Youmen Chaaban, Majeda Khraisheh
Information.2024; 15(6): 325. CrossRef
Publication Ethics in the Era of Artificial Intelligence
Zafer Kocak
Journal of Korean Medical Science.2024;[Epub] CrossRef
Exploring the Impact of Artificial Intelligence on Research Ethics - A Systematic Review
Gabriel Andrade-Hidalgo, Pedro Mio-Cango, Orlando Iparraguirre-Villanueva
Journal of Academic Ethics.2024;[Epub] CrossRef

Trends in research on ChatGPT and adoption-related issues discussed in articles: a narrative review: Sang-Jun Kim; Sci Ed. 2024;11(1):3-11. Published online December 18, 2023; DOI: https://doi.org/10.6087/kcse.321

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Abstract PDF Supplementary Material

This review aims to provide guidance for those contemplating the use of ChatGPT, by sharing research trends and evaluation results discussed in various articles. For an objective and quantitative analysis, 1,105 articles published over a 7-month period, from December 2022 to June 2023, following the release of ChatGPT were collected. These articles were sourced from PubMed, Scopus, and Web of Science. Additionally, 140 research articles were selected, including archived preprints and Korean articles, to evaluate the performance of ChatGPT. The analysis of research trends revealed that related communities are rapidly and actively responding: the educational community is redefining its directions, the copyright and patent community is monitoring lawsuits related to artificial intelligence creations, the government is establishing laws to regulate and prevent potential harm, the journal publishing community is setting standards for whether artificial intelligence can be considered an author, and the medical community is publishing numerous articles exploring the potential of ChatGPT to support medical experts. A comparative analysis of research articles on ChatGPT’s performance suggests that it could serve as a valuable assistant in human intellectual activities and academic processes. However, its practical application requires careful consideration to overcome certain limitations. Both the general public and researchers should assess the adoption of ChatGPT based on accurate information, such as that provided in this review.

Citations

Citations to this article as recorded by

Does ChatGPT affect users’ continuous knowledge contributions in online Q&A communities?
Guo Li, Mark Xuefang Zhu
Aslib Journal of Information Management.2025;[Epub] CrossRef
Prediction of the Use of Generative Artificial Intelligence Through ChatGPT Among Costa Rican University Students: A PLS Model Based on UTAUT2
Julio Cabero-Almenara, Antonio Palacios-Rodríguez, Hazel de los Ángeles Rojas Guzmán, Victoria Fernández-Scagliusi
Applied Sciences.2025; 15(6): 3363. CrossRef
Artificial intelligence-assisted academic writing: recommendations for ethical use
Adam Cheng, Aaron Calhoun, Gabriel Reedy
Advances in Simulation.2025;[Epub] CrossRef
The emergence of generative artificial intelligence platforms in 2023, journal metrics, appreciation to reviewers and volunteers, and obituary
Sun Huh
Journal of Educational Evaluation for Health Professions.2024; 21: 9. CrossRef
Explosive increase and decrease in articles, citations, impact factor, and immediacy index during the COVID-19 pandemic: a bibliometric study
Sang-Jun Kim
Science Editing.2024; 11(2): 107. CrossRef
Research ethics and issues regarding the use of ChatGPT-like artificial intelligence platforms by authors and reviewers: a narrative review
Sang-Jun Kim
Science Editing.2024; 11(2): 96. CrossRef
Evaluating AI Excellence: A Comparative Analysis of Generative Models in Library and Information Science
Raiyan Bin Reza, Md. Rifat Mahmud, S.M. Zabed Ahmed
Science & Technology Libraries.2024; : 1. CrossRef
Appliances of Generative AI-Powered Language Tools in Academic Writing: A Scoping Review
Lilia Raitskaya, Elena Tikhonova
Journal of Language and Education.2024; 10(4): 5. CrossRef

Original Articles

Trends, causes, and collaboration patterns of retracted Taiwanese medical research: a bibliometric study: Joshua Wang; Sci Ed. 2025;12(1):35-42. Published online February 11, 2025; DOI: https://doi.org/10.6087/kcse.360

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Abstract PDF: Purpose
Retraction of published literature is an increasingly important mechanism for protecting the scholarly record in today’s accelerated publishing environment. Analyzing retracted articles offers unique insights into how research communities maintain academic integrity. Taiwan is a major contributor to global medical research and has sustained public and media interest in academic integrity. Yet, no comprehensive analysis of retractions involving Taiwan-affiliated authors has been conducted. This paper therefore aimed to systematically examine retractions in Taiwanese medical research.
Methods
Data extracted from both PubMed and the Retraction Watch Database were analyzed to determine the number of retracted articles and their reasons for retraction.
Results
In total, 181 retractions of medical research articles with at least one Taiwan-affiliated author were included in the analysis, with the number of retractions steadily increasing since the first retracted article was published in 1992. Taiwanese medical research has the 9th highest retraction rate among the top 21 countries in medical research publications (6.08 retractions per 10,000 publications). However, this rate is lower than those of other highly productive Asian countries, including China, Korea, Japan, and India. Fifty-eight (32.04%) of the retractions involved international collaboration, most commonly with authors affiliated with the United States and China. Over the past 33 years, the reasons for retraction have gradually shifted from plagiarism or data manipulation to compromised peer review systems, ethical issues, and authorship disputes.
Conclusion
The results reveal that retractions in Taiwanese medical research are evolving and distinct from those in neighboring regions. This finding highlights the need to examine Taiwanese medical researchers’ perspectives on academic integrity and current publishing trends.

Ethical guidelines for the use of generative artificial intelligence and artificial intelligence-assisted tools in scholarly publishing: a thematic analysis: Adéle da Veiga; Sci Ed. 2025;12(1):28-34. Published online February 5, 2025; DOI: https://doi.org/10.6087/kcse.352

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Abstract PDF Supplementary Material: Purpose
This analysis aims to propose guidelines for artificial intelligence (AI) research ethics in scientific publications, intending to inform publishers and academic institutional policies in order to guide them toward a coherent and consistent approach to AI research ethics.
Methods
A literature-based thematic analysis was conducted. The study reviewed the publication policies of the top 10 journal publishers addressing the use of AI in scholarly publications as of October 2024. Thematic analysis using Atlas.ti identified themes and subthemes across the documents, which were consolidated into proposed research ethics guidelines for using generative AI and AI-assisted tools in scholarly publications.
Results
The analysis revealed inconsistencies among publishers’ policies on AI use in research and publications. AI-assisted tools for grammar and formatting are generally accepted, but positions vary regarding generative AI tools used in pre-writing and research methods. Key themes identified include author accountability, human oversight, recognized and unrecognized uses of AI tools, and the necessity for transparency in disclosing AI usage. All publishers agree that AI tools cannot be listed as authors. Concerns involve biases, quality and reliability issues, compliance with intellectual property rights, and limitations of AI detection tools.
Conclusion
The article highlights the significant knowledge gap and inconsistencies in guidelines for AI use in scientific research. There is an urgent need for unified ethical standards, and guidelines are proposed for distinguishing between the accepted use of AI-assisted tools and the cautious use of generative AI tools.

Impact and perceived value of the revolutionary advent of artificial intelligence in research and publishing among researchers: a survey-based descriptive study: Riya Thomas, Uttkarsha Bhosale, Kriti Shukla, Anupama Kapadia; Sci Ed. 2023;10(1):27-34. Published online February 16, 2023; DOI: https://doi.org/10.6087/kcse.294

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475 Download
8 Web of Science
8 Crossref

Abstract PDF Supplementary Material

Purpose
This study was conducted to understand the perceptions and awareness of artificial intelligence (AI) in the academic publishing landscape.
Methods
We conducted a global survey entitled “Role and impact of AI on the future of academic publishing” to understand the impact of the AI wave in the scholarly publishing domain. This English-language survey was open to all researchers, authors, editors, publishers, and other stakeholders in the scholarly community. Conducted between August and October 2021, the survey received responses from around 212 universities across 54 countries.
Results
Out of 365 respondents, about 93% belonged to the age groups of 18–34 and 35–54 years. While 50% of the respondents selected plagiarism detection as the most widely known AI-based application, image recognition (42%), data analytics (40%), and language enhancement (39%) were some other known applications of AI. The respondents also expressed the opinion that the academic publishing landscape will significantly benefit from AI. However, the major challenges restraining the large-scale adoption of AI, as expressed by 93% of the respondents, were limited knowledge and expertise, as well as difficulties in integrating AI-based solutions into existing IT infrastructure.
Conclusion
The survey responses reflected the necessity of AI in research and publishing. This study suggests possible ways to support a smooth transition. This can be best achieved by educating and creating awareness to ease possible fears and hesitation, and to actualize the promising benefits of AI.

Citations

Citations to this article as recorded by

Between Shortcut and Ethics: Navigating the Use of Artificial Intelligence in Academic Writing Among Indonesian Doctoral Students
Hardiyanti Pratiwi, Suherman, Hasruddin, Muhammad Ridha
European Journal of Education.2025;[Epub] CrossRef
Examining predictors of generative-AI acceptance and usage in academic research: a sequential mixed-methods approach
Sushma Verma, Neerja Kashive, Ashish Gupta
Benchmarking: An International Journal.2025;[Epub] CrossRef
The impact of generative AI tools on researchers and research: Implications for academia in higher education
Abdulrahman M. Al-Zahrani
Innovations in Education and Teaching International.2024; 61(5): 1029. CrossRef
Evaluating the Influence of Artificial Intelligence on Scholarly Research: A Study Focused on Academics
Tosin Ekundayo, Zafarullah Khan, Sabiha Nuzhat, Tze Wei Liew
Human Behavior and Emerging Technologies.2024;[Epub] CrossRef
Publish or perish in the era of artificial intelligence: which way for the Kenyan research community?
Stephen Oloo Ajwang, Anselimo Peters Ikoha
Library Hi Tech News.2024; 41(9): 7. CrossRef
Is Artificial Intelligence against/for Better Ethical Scientific Research?
Huriye Yaşar, Vasif Karagücük
Experimental and Applied Medical Science.2024; 5(2): 49. CrossRef
Evaluating the significance of artificial intelligence (AI) in academic platforms by using PIPRECIA-S method
Tijana Đukić, Srđan Novaković, Kristina Jauković-Jocić
Ekonomika.2024; 70(3): 11. CrossRef
Scholarly Discourse on GenAI’s Impact on Academic Publishing
Yogesh K. Dwivedi, Tegwen Malik, Laurie Hughes, Mousa Ahmed Albashrawi
Journal of Computer Information Systems.2024; : 1. CrossRef

Reviews

Can an artificial intelligence chatbot be the author of a scholarly article?: Ju Yoen Lee; Sci Ed. 2023;10(1):7-12. Published online February 16, 2023; DOI: https://doi.org/10.6087/kcse.292

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489 Download
5 Web of Science
13 Crossref

Abstract PDF

At the end of 2022, the appearance of ChatGPT, an artificial intelligence (AI) chatbot with amazing writing ability, caused a great sensation in academia. The chatbot turned out to be very capable, but also capable of deception, and the news broke that several researchers had listed the chatbot (including its earlier version) as co-authors of their academic papers. In response, Nature and Science expressed their position that this chatbot cannot be listed as an author in the papers they publish. Since an AI chatbot is not a human being, in the current legal system, the text automatically generated by an AI chatbot cannot be a copyrighted work; thus, an AI chatbot cannot be an author of a copyrighted work. Current AI chatbots such as ChatGPT are much more advanced than search engines in that they produce original text, but they still remain at the level of a search engine in that they cannot take responsibility for their writing. For this reason, they also cannot be authors from the perspective of research ethics.

Citations

Citations to this article as recorded by

Locating the Ethics of ChatGPT—Ethical Issues as Affordances in AI Ecosystems
Bernd Carsten Stahl
Information.2025; 16(2): 104. CrossRef
Interpreting text corpora from androids-related stories using large language models: “Machines like me” by Ian McEwan in generative AI
Simona-Vasilica Oprea, Adela Bâra
Humanities and Social Sciences Communications.2025;[Epub] CrossRef
ChatGPT: More Than a “Weapon of Mass Deception” Ethical Challenges and Responses from the Human-Centered Artificial Intelligence (HCAI) Perspective
Alejo José G. Sison, Marco Tulio Daza, Roberto Gozalo-Brizuela, Eduardo C. Garrido-Merchán
International Journal of Human–Computer Interaction.2024; 40(17): 4853. CrossRef
The ethics of ChatGPT – Exploring the ethical issues of an emerging technology
Bernd Carsten Stahl, Damian Eke
International Journal of Information Management.2024; 74: 102700. CrossRef
ChatGPT in healthcare: A taxonomy and systematic review
Jianning Li, Amin Dada, Behrus Puladi, Jens Kleesiek, Jan Egger
Computer Methods and Programs in Biomedicine.2024; 245: 108013. CrossRef
“Brave New World” or not?: A mixed-methods study of the relationship between second language writing learners’ perceptions of ChatGPT, behaviors of using ChatGPT, and writing proficiency
Li Dong
Current Psychology.2024; 43(21): 19481. CrossRef
Evaluating the Influence of Artificial Intelligence on Scholarly Research: A Study Focused on Academics
Tosin Ekundayo, Zafarullah Khan, Sabiha Nuzhat, Tze Wei Liew
Human Behavior and Emerging Technologies.2024;[Epub] CrossRef
Interaction with Artificial Intelligence as a Potential of Foreign Language Teaching Program in Graduate School
T. V. Potemkina, Yu. A. Avdeeva, U. Yu. Ivanova
Vysshee Obrazovanie v Rossii = Higher Education in Russia.2024; 33(5): 67. CrossRef
Did ChatGPT ask or agree to be a (co)author? ChatGPT authorship reflects the wider problem of inappropriate authorship practices
Bor Luen Tang
Science Editing.2024; 11(2): 93. CrossRef
Emergence of the metaverse and ChatGPT in journal publishing after the COVID-19 pandemic
Sun Huh
Science Editing.2023; 10(1): 1. CrossRef
ChatGPT: Systematic Review, Applications, and Agenda for Multidisciplinary Research
Harjit Singh, Avneet Singh
Journal of Chinese Economic and Business Studies.2023; 21(2): 193. CrossRef
Universal skepticism of ChatGPT: a review of early literature on chat generative pre-trained transformer
Casey Watters, Michal K. Lemanski
Frontiers in Big Data.2023;[Epub] CrossRef
ChatGPT, yabancı dil öğrencisinin güvenilir yapay zekâ sohbet arkadaşı mıdır?
Şule ÇINAR YAĞCI, Tugba AYDIN YILDIZ
RumeliDE Dil ve Edebiyat Araştırmaları Dergisi.2023; (37): 1315. CrossRef

Bibliometric characteristics of retracted publications in pediatrics research: a systematic review: Zhi-Yi Yang, Li-Li Yang; Sci Ed. 2025;12(1):4-11. Published online December 11, 2024; DOI: https://doi.org/10.6087/kcse.351

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Abstract PDF: Purpose
In recent years, the number of retractions in biomedical literature has increased. Analyses of retracted publications can provide important information on the characteristics of retractions and may help reduce this trend. This study aimed to systematically analyze the time, source, citations, and reasons for retraction of pediatric research papers.
Methods
A systematic review of retracted articles related to pediatrics was performed in PubMed and Web of Science databases from their inception through December 31, 2023. Excluded from the review were articles unrelated to pediatric studies, conference proceedings, non-English articles, duplicates, and articles that could not be identified. The data extracted and analyzed included the title, publication year, retraction year, country, journal, impact factor, the party who raised the retraction, the reason for retraction, citation count, and the authors of the articles.
Results
The interval between publication and retraction ranged from 0 to 45 years, and the number of retracted papers peaked in 2023. China and the United States had the most retractions, and China had the highest rate of retraction. The proportion of retractions from China increased over time. Several journals published by Hindawi had many retractions compared to other journals. The most frequent reasons were publication issues, errors, and fraud/fabrication.
Conclusion
This study provides a comprehensive overview of retracted articles in pediatric research. Our findings suggest that it is important to scrutinize the process of research and publication, to identify and counter research misconduct, and to make the instructions, procedures, and outcomes of publication more transparent for researchers, publishers and regulators.

Original Article

Explosive increase and decrease in articles, citations, impact factor, and immediacy index during the COVID-19 pandemic: a bibliometric study: Sang-Jun Kim; Sci Ed. 2024;11(2):107-113. Published online June 26, 2024; DOI: https://doi.org/10.6087/kcse.334

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Abstract PDF

Purpose
This study investigated how Journal Citation Reports (JCR) metrics changed during the COVID-19 pandemic (2020–2022), with the aim of sharing this information with stakeholders in the publishing community.
Methods
In total, 7,689 journals listed in the JCR-Science Citation Index Expanded (SCIE) from 2016 to 2022 were selected. Data were analyzed using pivot tables in Microsoft Excel. We calculated the compound annual growth rate to investigate changes in JCR-SCIE articles, citations, the journal impact factor, and the immediacy index during the COVID-19 period.
Results
A marked increase was noted in the number of articles and citations during the COVID-19 pandemic from 2020 to 2022. This surge was primarily driven by a significant rise in COVID-19–related articles. Consequently, four JCR metrics exhibited a sharp increase in 2020, followed by an unusually steep decline in 2022. Articles, citations, and the journal impact factor reached their highest recorded levels in 2021, while the immediacy index saw its most significant growth and intense citation activity in 2020 before experiencing notable decreases in 2021 and 2022. Our findings indicate that there was an unprecedented and dramatic shift in these four JCR metrics during the COVID-19 period, with current trends suggesting a reversion to historical compound annual growth rate levels.
Conclusion
The journal publishing and scientific communities should consider these explosive changes when applying JCR metrics to evaluate articles and endeavor to mitigate the adverse effects of the unusual concentration of articles and citations during the COVID-19 period. These results constitute valuable information to be shared among researchers and stakeholders within the journal publishing community.

Citations

Citations to this article as recorded by

The Korea Research Institute of Bioscience and Biotechnology’s number of articles and turnaround time before and after the COVID-19 pandemic: a case study
Sang-Jun Kim
Science Editing.2025; 12(1): 50. CrossRef
Trends in academic research on thirdhand smoke using bibliometric analysis
Joseph K. Ahialey, Yubin Lee, Myung-Bae Park, Jimi Huh
Tobacco Induced Diseases.2025; 23(April): 1. CrossRef
Mental health during and after the COVID-19 pandemic – a longitudinal study over 42 months in five European countries
Irina Zrnić Novaković, Dean Ajduković, Marina Ajduković, Laura Kenntemich, Annett Lotzin, Ingo Schäfer, Xenia Anastassiou-Hadjicharalambous, Eleftheria Evgeniou, Camila Borges, Margarida Figueiredo-Braga, Moritz Russo, Brigitte Lueger-Schuster
European Journal of Psychotraumatology.2025;[Epub] CrossRef

Book Review

The AMA Manual of Style, 11th edition: the ultimate guide to scholarly publishing in the digital age: Yoon Joo Seo; Sci Ed. 2023;10(2):195-196. Published online July 19, 2023; DOI: https://doi.org/10.6087/kcse.307

4,234 View
811 Download

PDF

Editorial

Artificial intelligence–assisted writing: a continuously evolving issue: Jaegyun Park; Sci Ed. 2023;10(2):115-118. Published online August 9, 2023; DOI: https://doi.org/10.6087/kcse.318

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383 Download
2 Web of Science
2 Crossref

PDF Supplementary Material

Citations

Citations to this article as recorded by

Analyzing AI use policy in LIS: association with journal metrics and publisher volume
Eungi Kim
Scientometrics.2024; 129(12): 7623. CrossRef
Assessing the Influence of AI on Modern Student Writing Standards: An Educators' Perspective
Reem Alhajji
Research Journal in Advanced Humanities.2024;[Epub] CrossRef

Training Material

A novel “conceive, design, implement, operate (CDIO)” framework for evaluating artificial intelligence–generated scholarly manuscripts: Aji Prasetya Wibawa, Anik Nur Handayani, Prananda Anugrah, Agung Bella Putra Utama; Sci Ed. 2025;12(1):70-75. Published online November 14, 2024; DOI: https://doi.org/10.6087/kcse.348

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Abstract PDF: This paper introduces a novel application of the “conceive, design, implement, operate (CDIO)” framework to improve the thoroughness and organization of academic editorial review processes. It demonstrates that the CDIO framework, originally applied to engineering education, can also be adapted for reviewing creative and interdisciplinary ideas. The adaptation of the CDIO framework for editorial review is already evident in scholarly publications, and this paper extends its application to include reviews of content produced by artificial intelligence (AI) platforms. The “conceive” stage focuses on developing clear research questions and objectives that align with the key moments of article conception. It ensures that content produced by AI begins with an ethical scientific foundation and maintains this integrity throughout the process. The “design” stage emphasizes maintaining scientific accuracy and clarity of presentation. It considers all critical manuscript design elements and incorporates methods to evaluate the originality and rationality of AI-generated data and analysis. The “implementation” stage is concerned with the effective communication of findings, providing insights into how the manuscript is perceived. It is crucial for data generation or tool usage involving AI. The “operate stage” involves analyzing the findings and their overall impact on the field, ensuring a comprehensive assessment from all perspectives when AI-generated content is integrated into academic discourse, which has broader implications. By applying the CDIO framework innovatively, this paper offers a systematic and comprehensive method for conducting editorial reviews. This ensures that manuscripts generated by AI are subjected to the same rigorous scrutiny as those authored by humans. This approach improves the quality, transparency, and reputation of scholarly publications. We examine each stage of the CDIO process, achieving uniformity and clarity, and providing a more precise evaluation of both traditional and AI-assisted academic research.

Case Study

The promotion of university journals published by Universitas Diponegoro, Indonesia, from 2018 to 2024: a descriptive study: Eko Didik Widianto, Hadiyanto, Teddy Mantoro, Raka Sindu Wardoyo; Sci Ed. 2025;12(1):43-49. Published online February 5, 2025; DOI: https://doi.org/10.6087/kcse.353

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Abstract PDF Supplementary Material: This study explores the promotion of university journals published by Universitas Diponegoro (UNDIP), Indonesia, between 2018 and 2024. UNDIP managed 178 active journals spanning various subjects across 13 faculties. The analysis focused on four key indicators: the number of journals accredited by the Akreditasi Jurnal Nasional (ARJUNA), the accreditation grade in the Science and Technology Index (SINTA) database, the number of journals indexed in Scopus, and the number of abstract views and article downloads. Data collection involved searching literature databases, including SINTA and Scopus, and tracking hits and downloads on the web server. The findings indicate that the number of active journals increased from 136 in 2018 to 178 in 2024, with an average annual growth of 7 journals. The mentoring programs at UNDIP led to significant achievements in key performance indicators, with 106.5% of journals becoming accredited and 112.2% being indexed in Scopus. The annual growth rates for accredited and Scopus-indexed journals were 9.33 and 0.83, respectively. Additionally, the cumulative number of abstract views and article downloads increased by 47.14 million annually, attracting visitors from a broad range of countries. The mentoring programs and robust infrastructure at UNDIP have likely played crucial roles in enhancing the promotion and performance of the university’s journals, which are vital for journal promotion and the achievement of key performance indicators.

Original Article

How Spanish educational researchers used Twitter/X as a platform to promote the dissemination of scientific knowledge: a descriptive study: Elias Said-Hung, Sergio Arce-García, Daria Mottareale-Calvanese; Sci Ed. 2024;11(2):123-133. Published online June 26, 2024; DOI: https://doi.org/10.6087/kcse.336

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Abstract PDF Supplementary Material: Purpose
This study aimed to examine how educational researchers in Spain promoted the dissemination of scientific knowledge on Twitter/X as a platform and to contrast their approach with science influencers in the same country.
Methods
Accounts on the Twitter/X service belonging to 210 Spanish researchers were analyzed, and their 2016–2020 tweets were compared to those of 38 Twitter/X influencers. Text mining techniques, sentiment and emotion analysis, network analysis, and the Kardashian index (K-index) were used in the study.
Results
The results indicated a low academic presence of researchers (4.4%) on Twitter/X. The researchers shared 185,020 posts (38.7% original content and 61.3% retweets). A network analysis revealed low interconnectivity among researchers, with distinct clusters based on their interests or affiliations. The top influencers had strong connections with the news media. The researchers focused minimally on academic topics, while the influencers emphasized the dissemination of scientific findings. The impact of the researchers’ posts was minimal, with low K-index values, whereas the influencers had greater reach because of their follower base.
Conclusion
When using Twitter/X, the researchers had a minimal impact on the dissemination of scientific information because they published few original posts and relied instead on retweets unrelated to their academic or research activities. Consequently, the researchers did not use Twitter/X as a tool for scientific communication, which limited the potential for forming new connections beyond their existing social and academic networks. Promoting informal learning that encompasses diverse knowledge and learning levels is crucial to fostering greater engagement and collaboration.

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