Academia’s Responses to COVID-19: Bibliometric and Visualization Analysis on Online Learning of Medical Students

doi:10.21203/rs.3.rs-3212325/v1

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Academia’s Responses to COVID-19: Bibliometric and Visualization Analysis on Online Learning of Medical Students

https://doi.org/10.21203/rs.3.rs-3212325/v1

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Background

This study aimed to investigate research hotspots and future direction in the online learning of medical students around the globe during COVID-19 via bibliometric and visualization analyses.

Methods

Bibliometric analysis and visual mapping were used to analyze relevant publications. Cite Space 6.1.R3 was used to generate a network visualization map to evaluate cooperation between countries, institutions, and authors.

Results

Since 2020, a total of 2,582 publications were enrolled. The visualization results show that academic achievements in online learning research benefit from a global collaborative foundation. The United States occupies the core position. Another prominent result is that Chinese authors have made outstanding contributions to online learning research. Findings of co-cited references indicated that the most influential co-cited author and academic teams investigated a wide array of topics, such as online learning practice, academic theories and models, redesigned curriculum of different disciplines, psychological impacts of the pandemic, and the future challenge of reshaping lifelong learning. Keyword co-occurrence analysis shows that the research during the COVID-19 pandemic can be roughly divided into three stages.

Conclusion

Given that evolution path of the past three years–and the experience generated during the Covid era–that online learning will be further developed and applied in the post COVID-19 era.There is a trend that all medical subjects will be taught with some hybrid delivery systems. More over, the evolution trajectory of online learning will be direct to more autonomous, more advanced technology and method involved,and more extensive cooperation.

COVID-19

medical education

online learning

medical students

cite space

bibliometric analysis

Since 2020, some of the most discussed topics in medical education academic have been the impact of the pandemic and the exploration of online learning practice. Although Covid is new, the online learing are not. Online learning had been expanding for two decades prior to the COVID-19 pandemic. Distance or asynchronous teaching and learning within higher education in the US, for example, began during the mid to late 1990s and accelerated with MIT’s Open Course Project launched in 2002[1]. It has further blossomed with the development of Massive Open Online Courses (MOOCs) beginning in 2012—especially once some of the most prestigious universities in the US (and worldwide) embraced this technology and shift in learning methodology. However, higher education does not see e-learning as replacing traditional instructor-led training but as a complement to it, forming part of a blended-learning strategy. As COVID-19 has swept the world, face-to-face teaching and learning have been interrupted by the lockdown. Online learning has helped those medical schools to overcome established barriers overnight and make the most rapid online curricular shift in medical education's history[2].

Regarding the concept of online learning, this paper recommends Singh and Thurman’s definition of using the Internet to enhance students’ synchronous or asynchronous learning activities. Online learning relates to the concepts of e-learning, distance learning, remote learning, and tele-learning, which involve the use of technology to facilitate communication between teachers and students, regardless of the student’s physical or virtual location[3]. As a sudden transition brought about by the COVID-19 pandemic, online learning can quickly explore and solve problems in response to impending challenges brought to medical education. Domestic and foreign scholars have devoted themselves to solving these problems and publishing a large number of papers. However,there are few systematic reviews on the changes in online learning practices of medical students. This study reveals the research trends and current status of the publications which focused on COVID-19-related online learning through bibliometric and visualization analysis. It further provides important findings for the future research vision of this subject area.

Data Collection

The data was retrieved from the Web of Science Core Collection (WoSCC) to acquire publications focused on online learning. The search strategies were as follows: TS=(e-learning OR online learning OR distance learning OR tele learning OR remote learning) AND TS=(medical student) NOT TS=(veterinary). All searches were performed on a single day (October 1, 2022) to avoid bias produced by daily database renewal. The slice is one year. A total of 2,751 records published from January 1, 2020, to September 30, 2022, were obtained for further study, including only articles and reviews written in English.There are 2,582 records left by removing the duplicates, news, comments, editorials, and letters.

Software and Methods

Bibliometrics and visualization are the main methods of our research. Bibliometrics can reduce the distortion and bias caused by subjective information filtering through comprehensive mining and research of basic literature. All the publications included were exported in TEXT format and then imported into Cite Space (6.1.R3), which is visualization software that was developed by Professor Chaomei Chen. The visualization functions of Cite Space, such as cooperative networks, co-cited documents, and keywords, were performed to explore emerging topics and future directions.

There are some terms of Cite Space that need to be explained. In this study, different nodes in visualization represent different research subjects, such as “keyword”. Frequency is used to describe the number of nodes the higher the frequency, the larger the circle of nodes. The purple ring outside the node is used to represent the centrality; the greater the centrality, the more the core is in the relationship. Professor Chaomei Chen believes that nodes with intermediate centrality greater than 0.1 play an important role in bridge connection[4]. A line between nodes refers to a cooperative network; the thicker the lines, the closer the relationship, and the same color represents the same year.

Data Analysis on Publications

The total number of publications related to this study was 2,751 since the outbreak of the pandemic, 702 publications published in 2020, 1,377 in 2021, and 672 in 2022 from January to September. Figure 1 exhibits an overall upward trend, especially at the beginning of 2021. Obviously, the linear fitting of the studies shows a significant positive correlation (R²=0.957**) between the number of global COVID-19 confirmed cases (red curve) of WHO(https://covid19.who.int/) and the number of publications (blue column) of WoSCC. We can see that the two curves show almost the same growth tendency, which shows the efforts made by the medical education academia to rapidly respond to the pandemic[5].

Cooperation Relationship Analysis

We mapped a cooperative relationship network for countries, institutions, and authors of publications by Cite Space (6.1. R3). The analysis of the distribution of publications (Table 1) identifies the top 10 productive countries, institutions, and authors participating in this study, which can help to analyze the leading research frontier.

Table 1

The top 10 countries, institutions, and authors with the highest number of publications.
	Country		Institution			Author
Rank	Count	Country	Count	Institution	Location	Count	Author	Institution of Author	Location
1	721	USA	36	University Calif San Francisco	USA	15	Yunhe Wang	Peking University	CHINA
2	266	UK	33	University of Toronto	AUSTRALIA	13	Lee, Justin S	CDC COVID-19 Response Team	USA
3	204	GERMANY	33	Harvard Medical School	USA	12	Xin Zhang	University of Hong Kong	CHINA
4	213	CHINA	29	University of Michigan	USA	12	Yanfen Zhang	The Second Affiliated Hospital of Harbin Medical University	CHINA
5	136	INDIA	27	Imperial College London	UK	12	Xiaoming Liu	Wuhan University of Science and Technology	CHINA
6	136	AUSTRALIA	26	University of North Carolina	USA	12	Kelly M. Harrell	Virginia Commonwealth University School of Medicine	USA
7	130	CANADA	25	University of Sydney	AUSTRALIA	11	Royer, Danielle	University of Colorado Anschutz Medical Campus	USA
8	109	SAUDI ARABIA	24	University of Colorado	USA	10	Martindale, Jim	University of Virginia	USA
9	66	PAKISTAN	22	University of Stanford	USA	10	Harmon, Derek	University of California, San Francisco	USA
10	56	IRAN	21	University of Washington	USA	10	Jun Wang	The First Affiliated Hospital of Chongqing Medical University	CHINA

Co-institutions Analysis

Some institutions with high frequency and centrality have contributed to the promotion of global online learning research. As the main organization for online learning research, universities have done more work than hospitals and research institutions. Figure 2(A) shows a close cooperative relationship among 252 institutions. Given the long-term history of online learning in the USA, seven of the ten most productive organizations belong to the United States, wherein the University of California San Francisco (count = 36) had the most publications. There are eight institutions with centrality greater than 0.1. Boston University (0.13), McGill University (0.13), Brown University (0.12), and Johns Hopkins University (0.10) belong to the United States; Sydney University (0.12) of Australia; Kings College of London of United Kingdom; Peking University (0.12) of China; King Abdulaziz University (0.12) of Saudi Arabia. These institutions (the nodes are linked by red lines) played an important role in establishing close cooperation between their countries.

Co-countries (Areas) Analysis

The cooperative relationship between institutions means the corresponding relationship between countries to some extent, as institutions belong to countries. Figure 2 (A) shows the network map between 119 countries (Areas). The United States has made outstanding contributions in the field of online learning in response to the COVID-19 pandemic, as we can inspire from the two indicators of maximum publications (721) and highest centrality (0.3). The second country is the United Kingdom, with 226 publications and 0.11 centrality. They all have purple outer rings, which represent a very important core position (Table 1). Next is Germany (count = 204, centrality = 0.04). China ranked fourth in terms of publications (213) and in terms of 20nd with centrality (0.03) have made great efforts in online learning research. Although some underdeveloped countries appeared in the list,due to the low centrality,they still need to improve the depth and breadth of research by strengthening their communication and cooperation.

Co-authors Analysis

A total of 241 authors were involved in the current work according to Cite Space analysis, but only 170 authors met the minimum publication thresholds(Ni ≥ 2.90),according to the result of Price’s formula Ni = 0.749 m. Nm refers to the number of papers issued by the most productive author. Figure 2 (B) is the author cooperation relationship map which shows a decentralized partnership of online learning. An obvious close cooperative network is composed of the top list authors. This team contains most publications and most authors (more than 30 researchers, most of them are from universities in the United States). Another obvious author cooperation network exists in China. It is clear that three authors (centrality = 0.13)—Kelly M. Harrell, Wenlu Zhang, and Claudia Krebs—have played an important intermediary role in China and America.

Co-cited References Analysis

Co-cited references of Cite Space refer to the phenomenon that two references are cited by the same document, which made significant contributions to a knowledge evolution process. Figure 3(A) is a map of 2,565 co-cited references among authors of online learning.The top 10 co-cited references (Table 2) were all published before 2020, such as Suzanne Rose[6], Samiullah Dost[7], and Hanad Ahmed[8].Which indicated references prior to 2020 received wide attention after the outbreak of COVID-19. Examples are the second most cited article written by Diane O'Doherty (2018)[9] and the fourth cited article written by Leisi Pei (2019)[10]. It needs to be highlighted that the authors in the co-cited reference list are different from the co-authors list, which indicates that a most productive author may not necessarily signify high quality (nor does the quality of the journal).

Table 2

The top 10 co-cited references of online learning.
Rank	Year	Title	Author	Journal	Co-citation
1	2020	Medical Student Education in the Time of COVID-19	Rose S	JAMA-Journal of the American Medical Association	172
2	2018	Barriers and solutions to online learning in medical education - an integrative review	ODoherty D	BMC Medical Education	98
3	2020	Perceptions of medical students towards online teaching during the COVID-19 pandemic: a national cross-sectional survey of 2721 UK medical students	Dost S	BMJ OPEN	72
4	2019	Does online learning work better than offline learning in undergraduate medical education? A systematic review and meta-analysis	Pei LS	Medical Education Online	68
5	2020	COVID-19 and medical education	Ahmed H	LANCET Infectious Diseases	65
6	2020	Impact of the COVID-19 pandemic on medical education: Medical students' knowledge, attitudes, and practices regarding electronic learning	Alsoufi A	PLOS ONE	63
7	2020	The psychological impact of the COVID-19 epidemic on college students in China	Cao WJ	Psychiatry Research	59
8	2020	Distance learning in clinical medical education amid COVID-19 pandemic in Jordan: current situation, challenges, and perspectives	Al-Balas M	BMC Medical Education	58
9	2020	The Impact of COVID-19 on Medical Education	Ferrel MN	Cureus Journal of Medical Science	58
10	2020	Strength, weakness, opportunity, threat analysis of the adaptations to anatomical education in the United Kingdom and Republic of Ireland in response to the Covid-19 pandemic	Longhurst GJ	Anatomical Sciences Education	52

The cited reference clustering label can be used to infer the core academic ideas and research frontiers of major academic teams. Figure 3(B) showed that flipped classroom was frequently cited in the 2020 online learning research. Some major references were cited during 2021, including online teaching, surgical education, online learning experience, anatomy education, mental health, dental education, and cognitive load theory. The academic began to pay attention to online learning of postgraduate education at 2022. There is a clear clue that online learning has changed from the initial focus on a certain learning form (flipped curriculum) to the whole stage of medical education, which shows an evolution path of research in the past three years.

Documents on online learning practice

The first theme focused on online learning and education, including online teaching (cluster#0), flipped classroom (cluster#1), and online learning experience (cluster#3). Rose S (2020) and Dost S (2020) published the most valuable references, which provide a solid research foundation for solving the global pandemic. Some authors have paid attention to some underdeveloped countries that lack digital infrastructure and students' e-learning capabilities[11] so as to prevent e-learning from becoming a propeller of the educational gap. Al-Balas M (2020)[12] introduced Jordan's experience; Khalil and Rehana (2020)[13] explored Saudi Arabia's experience.

Documents on learning theory and model

After the outbreak of the epidemic, theories and models related to pedagogy, psychology, and organizational behavior were applied to analyze online learning behavior and motivation (Hadie Rajeh MT, 2021)[14], including self-determination theory, cognitive load theory (cluster#7)[15], and planned behavior theory. Other models, such as structural equation modeling (Almarzouqi A, 2022) and expectation-confirmation model (Cheng YM, 2020), are cited to assess user satisfaction and willingness to continue using online learning[16].

Documents on medical disciplines

Some medical disciplines (cluster#2, cluster #4, cluster #6) are widely concerned with online learning research because they face greater challenges. Longhurst GJ (2020)[17] and Pather N (2020) research anatomy education which is the most concerning subject among all disciplines; Wilcha R-J (2020) and Dedeilia A (2020) committed to surgical education; Amir LR (2020) and Schlenz MA (2020) engaged in dental education. These academic groups are devoted to adapting the traditional, synchronous course to online learning mode. In addition, some advanced technology and tools, such as virtual auscultation[18], augmented reality[19], and simulation, were applied to these disciplines and achieved desirable results.

Documents on mental health

The third theme (Cluster #5) of mental health with 36 nodes, such as depression, stress, and anxiety, was addressed by Cao WJ (2020) and Hodges CB (2021). The COVID-19 pandemic has exposed the need to address mental health issues for the future adoption of e-learning among a massive number of students in medical education. Some strategies have been proposed to address the mental health damage factors to medical students' online learning[20].

Documents on lifelong learning

The final theme (cluster#7) is postgraduate medical education with 14 nodes. Papapanou M (2022) suggests that the quality of postgraduate medical education can be improved through online learning[21]. Researchers have designed a series of online medical courses to meet the learning needs of all stages of medical education. At the beginning of the outbreak, undergraduate medical education focused initially on continuing medical education (namely, continuing professional development) and postgraduate medical education has attracted the attention of academic researchers as well as practitioners.

Keyword Co-occurrence Analysis

The keyword co-occurrence result shows no burst keyword nor keywords with centrality greater than 0.1, which indicates that there is no obvious research center and core hotspot in the online learning field. Instead, there are decentralized themes and tendencies. Most of the high-frequency keywords appeared in the first year of the outbreak, and with increasingly lower frequency and centrality in the following years. However, this does not mean that the academic has lost interest in this field. We are pleased to see that these studies are moving toward a more refined and in-depth direction over time. Table 3 shows the top 10% keywords from 2020 to 2022. There are 198 keywords appearing for the first time in 2020, and these keywords include almost all of the research on online learning to date. 2021 had 154 keywords with lower word frequency and centrality. There were only 53 keywords in 2022.

Table 3

Top high-frequency keywords in online learning from 2020 to 2022.
Year	Count	Centrality	Keywords	Year	Count	Centrality	Keywords
2020	775	0.01	medical education	2021	42	0.01	stress
	605	0.03	medical student		25	0.02	resident
	175	0	online learning		23	0.02	challenge
	155	0	covid-19		21	0.01	feedback
	145	0.01	impact		17	0.03	faculty development
	143	0.02	health care		16	0.02	perspective
	111	0	undergraduate medical education		15	0.02	validity
	104	0	distance learning		14	0.01	virtual education
	98	0.01	performance		13	0.01	student engagement
	98	0.05	skill		13	0.02	dental student
	95	0.04	perception		12	0.01	adolescent
	88	0.03	curriculum		11	0.01	self-efficacy
	86	0.02	anatomy		11	0.01	nurse
	76	0.01	online education		11	0.02	disorder
	73	0.01	technology		11	0.02	integration
	67	0.01	knowledge	2022	7	0	retention
	66	0.01	mental health		6	0	cardiopulmonary resuscitation
	62	0.02	experience		6	0.1	structured clinical examination
	61	0	blended learning		5	0	neurosurgery education
	60	0.01	medical school		5	0	digital education

Clusters for research hotspots were identified with the keyword timeline view by Cite Space (6.1.R3). Seven clusters in total were formed, including dental education, virtual reality, mental health, surgical education, self-directed learning, blended learning, and collaborative learning. According to a timeline view (Fig. 4) and the co-occurrence of keywords (Table 3)—combined with the number of chronological documents—the research oriented toward online learning during the COVID-19 pandemic can be roughly divided into three stages.

Rapid development stage

As the largest distance learning practice in the history of human civilization, online learning developed rapidly in 2020, accompanied by the deterioration of COVID-19. The top four keywords should not be analyzed because they are search strategy terms. This period has the most frequent keywords, including health care, impact, perception, etc. These keywords demonstrate the efforts made by the medical education community to ensure the effectiveness of online learning during the lockdown. In order to achieve substantial equivalence, the research in 2020 mainly focuses on the effect and factors of online learning. Some studies have developed appropriate policies and initiatives to promote the effectiveness of e-learning[22].

Flourish stage

The study of online learning flourished in 2021, meanwhile, the COVID-19 pandemic maintained a stable deterioration trend. Compared with 2020, the keyword frequency and centrality decreased significantly. The largest number of publications possessed an increasing keyword and decreasing keyword frequency in this year. However, the reduced frequency indicates that scholars are committed to improving the depth and breadth of research, trying to calm down after a rapid pace in 2020. The high-frequency keywords in 2021 mainly include stress, resident, challenge, feedback, faculty development, perspective, validity, etc. The research direction has also changed from an online learning guarantee to quality improvement. Other studies demonstrate the possibility of changing the learning path from real teaching to virtual online learning during the pandemic[23].

Stable stage

After two years of rapid development, online learning has ushered in a stable stage with more mature theory and more diverse methods. The gradually reduced frequency of keywords, such as retention, cardiopulmonary resuscitation, neurosurgery, and structured clinical examination. It is indicated that the attention to some important topics within the existing research is gradually reduced, replaced by a variety of contextualized situational micro-topics, which is a manifestation of more in-depth research. The new stage focused on topics such as self-regulated learning, advanced technology application, teaching model, etc. Moreover, scholars pay more attention to exploring a hybrid teaching method that combines traditional classroom and online learning and are committed to transforming and retaining online learning results and experiences, even in the post-pandemic era.

Medical education may divide into pre-pandemic and post-pandemic eras[24] by the COVID-19 outbreak. This study attempts to identify the changes in online medical education during these eras and whether such changes can adequately serve the needs of training future medical practitioners.

Autonomy online learning Ideology

Spatiotemporal asynchrony induced by the COVID-19 pandemic requires a higher autonomy of medical students[25]. The theory of autonomous learning, self- directed learning, self-regulated learning, self-reflective learning, and so on, which are related to the initiative, came into being in this unprecedented large-scale online education practice and led to a fundamental change in the learning ideology. In an online teaching and learning context, knowledge is transferred from passive infusion to positive acquisition and promoted the application of knowledge in clinical practice through self-reflection. Although this change took place in a relatively short period of time, it was enough to produce an active learning “habitus” of the practitioner (learners and educators) even after the pandemic. Besides, some scholarly literature is devoted to exploring lifelong self-directed learning for medical students and physicians, including undergraduate medical education, postgraduation medical education, and continuing medical education.

Diversified online learning technology

A wide range of methods and tools modalities are widely integrated into online learning. However, what we need to focus on is that medical education research is trying to pursue these advanced technologies. For example, a great deal of research is concerned with exploring the use and effectiveness of various technologies, such as augmented reality, digital simulations, virtual and remote laboratories, and synchronous/asynchronous learning tools. Besides, some advanced science and technology, such as artificial intelligence, cloud computing, blockchain, and some knowledge engineering and software engineering method, have also been tried to apply. However, the use of these technologies has put forward higher requirements for students' online learning ability, including the ability to apply information technology, self-control, and pressure regulation. For policymakers, researchers and practitioners, it is more important to focus on technology in innovative pedagogy than on technology solely.

In-depth integration of blended learning modes

The blended learning mode of online and offline in-depth integration is becoming the direction and goal in the post-pandemic era. Blended learning or hybrid learning cannot simply represent Online Merge Offline activities, nor can it be considered a return to pre- pandemic blended learning. As a deep integration, it draws on the experiences and practices that occurred during the pandemic and provides students with ubiquitous, personalized, and targeted learning support[26]. In addition, efforts are reflected in the improvement of blended learning strategies and quality. Some studies have attempted to explore the application of the blended teaching model based on Small Private Online Courses (SPOC), Massive Open Online Courses (MOOC)[27], Problem-based Learning (PBL), Team-based Learning (TBL)[28], and Case-based Learning (CBL). Finally, academia believes that the evaluation criteria need to be redefined as multi- dimensional evaluation[29].

Cooperative online learning strategies

The study shows that countries, institutions, and authors are more deeply interconnected than we knew, and all depend on a network of cooperation and exchanges. The Internet provides an opportunity for underdeveloped countries to acquire medical, educational resources, which is why these countries are so keen to participate in online learning research. After all, one of the purposes of international exchanges and cooperation is to promote educational equity. An additional analysis— Journal Overlay Map—found that information science, engineering, psychology, and sociology are all involved in online education research, which shows a transcendence for medical and educational disciplines. The reason why online education can overcome the adverse effects of the epidemic is that all educational organizations are striving to produce and share knowledge. In the post-pandemic era, the international first-class curriculum system will be built based on the cooperation and division of labor among countries or institutions. Medical schools around the world will carry out extensive cooperation to train transnational medical and public health students, decision-makers, and clinicians. The form of cooperation has also changed from a single discipline to an interdisciplinary and transdisciplinary direction[30].

The large volume of evolving research reviewed in this study through bibliometrics helps us to understand the level of participation of global scholars in rapidly exploring a wide range of topics related to online learning caused by the pandemic. One conclusion is that online learning will be based on extensive cooperation among countries, institutions, and authors. The co-cited reference revealed that intellectual relatedness between previous and evolving research on online learning was mainly focused on the practice and experience, widely adopted theory and models, redesigned curriculum of different disciplines, psychological problems caused by the pandemic, and challenges of lifelong learning. And there were three obvious stages identified from the list of the most frequently cited keywords annually,which indicates that online learning will be further developed in the post epidemic era. All subjects have experienced online learning practice,even the most challenging anatomy, dentistry, and surgery.Research hotspots and research tendencies were reinforced by the results of keyword co-occurrence and timeline view analysis. The evolution trajectory, discussed in the end, the practice of online learning is expected to more autonomy, more application of advanced technologies and methods, deeper integration of blended learning, and more extensive cooperation in the post-COVID-19 era.

Limitations

This study had several limitations. For example, our data is incomplete and only exported from WoSCC. The second limitation relates to bias. Although it is the most frequently used database in scientific metric research, some different expressions with the same meaning are identified and integrated manually. These problems may be resolved in the future with the development of software updates.

Authors’ contributions

Haihun Zhai and Pei Zhang designed the study, recorded the bibliometric data with the application of different software, edited the data for the statistical work, and wrote the original draft. Xiuyuan Li studied the publications as well as prepared the modified figures and tables. Ying Pan edited and revised the manuscript. Tian Li contributed to the methodology, supervision, and project administration of the study. All authors approved the final manuscript for submission and agreed to be accountable for the work.

Acknowledgments

Thanks also for the assistance with literature retrieval provided by the university library. We thanked https://www.fcedit.com/en/index.aspx for language editing service.

Funding

This study was funded by the Ministry of Education of China 2021 General Program of Humanities and Social Sciences Research (21YJA880081). This publication reflects only the authors’ views. The Commission is not responsible for any use that may be made of the information it contains.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary materials. All data are available on request to the corresponding author [email protected].

Ethical Approval

Ethical approval and participant consent are not applicable for this manuscript.

Author’s declaration

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Lerman, S. and J.P. Potts, Unlocking knowledge, empowering minds: MIT's OpenCourseWare project. Ieee Signal Processing Magazine, 2006. 23(5): p. 11-15.
Binks, A.P., et al., Changing Medical Education, Overnight: The Curricular Response to COVID-19 of Nine Medical Schools. Teaching and Learning in Medicine, 2021. 33(3): p. 334-342.
Singh, V. and A. Thurman, How Many Ways Can We Define Online Learning? A Systematic Literature Review of Definitions of Online Learning (1988-2018). American Journal of Distance Education, 2019. 33(4): p. 289-306.
Chen, C.M., CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 2006. 57(3): p. 359-377.
Yao, S., et al., Research Hotspots and Trend Exploration on the Clinical Translational Outcome of Simulation-Based Medical Education: A 10-Year Scientific Bibliometric Analysis From 2011 to 2021. Frontiers in Medicine, 2022. 8.
Rose, S., Medical Student Education in the Time of COVID-19. Jama-Journal of the American Medical Association, 2020. 323(21): p. 2131-2132.
Dost, S., et al., Perceptions of medical students towards online teaching during the COVID-19 pandemic: a national cross-sectional survey of 2721 UK medical students. Bmj Open, 2020. 10(11): p. 10.
Ahmed, H., M. Allaf, and H. Elghazaly, COVID-19 and medical education. Lancet Infectious Diseases, 2020. 20(7): p. 777-778.
O'Doherty, D., et al., Barriers and solutions to online learning in medical education - an integrative review. Bmc Medical Education, 2018. 18: p. 11.
Pei, L.S. and H.B. Wu, Does online learning work better than offline learning in undergraduate medical education? A systematic review and meta-analysis. Medical Education Online, 2019. 24(1): p. 13.
Gismalla, M.D.A., et al., Medical students' perception towards E-learning during COVID 19 pandemic in a high burden developing country. Bmc Medical Education, 2021. 21(1): p. 7.
Al-Balas, M., et al., Distance learning in clinical medical education amid COVID-19 pandemic in Jordan: current situation, challenges, and perspectives. Bmc Medical Education, 2020. 20(1): p. 7.
Khalil, R., et al., The sudden transition to synchronized online learning during the COVID-19 pandemic in Saudi Arabia: a qualitative study exploring medical students' perspectives. Bmc Medical Education, 2020. 20(1): p. 10.
Rajeh, M.T., et al., Students' satisfaction and continued intention toward e-learning: a theory-based study. Medical Education Online, 2021. 26(1): p. 8.
Hadie, S.N.H., et al., COVID-19 Disruptions in Health Professional Education: Use of Cognitive Load Theory on Students' Comprehension, Cognitive Load, Engagement, and Motivation. Frontiers in Medicine, 2021. 8: p. 14.
Cheng, Y.M., Students' satisfaction and continuance intention of the cloud-based e-learning system: roles of interactivity and course quality factors. Education and Training: p. 23.
Longhurst, G.J., et al., Strength, Weakness, Opportunity, Threat (SWOT) Analysis of the Adaptations to Anatomical Education in the United Kingdom and Republic of Ireland in Response to the Covid-19 Pandemic. Anatomical Sciences Education, 2020. 13(3): p. 298-308.
Rullmann, N., et al., Virtual auscultation course via video chat in times of COVID-19 improves cardiac auscultation skills compared to literature self-study in third-year medical students: a prospective randomized controlled cross-over study. Gms Journal for Medical Education, 2022. 39(2): p. 11.
Dhar, P., et al., Augmented reality in medical education: students' experiences and learning outcomes. Medical Education Online, 2021. 26(1): p. 9.
Giusti, L., et al., Predictors of academic performance during the covid-19 outbreak: impact of distance education on mental health, social cognition and memory abilities in an Italian university student sample. Bmc Psychology, 2021. 9(1): p. 17.
Kaul, V., et al., Medical Education During the COVID-19 Pandemic. Chest, 2021. 159(5): p. 1949-1960.
Regmi, K. and L. Jones, A systematic review of the factors - enablers and barriers - affecting e-learning in health sciences education. Bmc Medical Education, 2020. 20(1): p. 18.
Rohle, A., H. Horneff, and M.C. Willemer, Practical teaching in undergraduate human and dental medical training during the COVID-19 crisis. Report on the COVID-19-related transformation of peer-based teaching in the skills Lab using an Inverted Classroom Model. Gms Journal for Medical Education, 2021. 38(1): p. 6.
Althwanay, A., et al., Medical Education, Pre- and Post-Pandemic Era: A Review Article. Cureus Journal of Medical Science, 2020. 12(10): p. 6.
Pelikan, E.R., et al., Distance learning in higher education during COVID-19: The role of basic psychological needs and intrinsic motivation for persistence and procrastination-a multi-country study. Plos One, 2021. 16(10): p. 23.
Vallee, A., et al., Blended Learning Compared to Traditional Learning in Medical Education: Systematic Review and Meta-Analysis. Journal of Medical Internet Research, 2020. 22(8): p. 18.
Littenberg-Tobias, J. and J. Reich, Evaluating access, quality, and equity in online learning: A case study of a MOOC-based blended professional degree program. Internet and Higher Education, 2020. 47: p. 11.
Zeng, J.R., et al., Application of blended teaching model based on SPOC and TBL in dermatology and venereology. Bmc Medical Education, 2021. 21(1): p. 7.
Kang, S.H., et al., Validity of OSCE Evaluation Using the FLEX Model of Blended Learning. Journal of Korean Medical Science, 2022. 37(20): p. 6.
Abdelaziz, A., et al., Challenges to Interprofessional Education: will e-Learning be the Magical Stick? Advances in Medical Education and Practice, 2021. 12: p. 329-336.

No competing interests reported.

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Academia’s Responses to COVID-19: Bibliometric and Visualization Analysis on Online Learning of Medical Students

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and Methods

Data Collection

Software and Methods

Results

Data Analysis on Publications

Cooperation Relationship Analysis

Co-cited References Analysis

Discussion

Autonomy online learning Ideology

Diversified online learning technology

In-depth integration of blended learning modes

Cooperative online learning strategies

Conclusion

Limitations

Declarations

References

Additional Declarations

Supplementary Files

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