Saqr Mohammed, Raspopovic Milic Miroslava, Pancheva Katina, Jovic Jovana, Peltekova Elitsa V, Conde Miguel Á
School of Computing, University of Eastern Finland, Joensuu Campus, Yliopistokatu 2, 80100 Joensuu, Finland.
Faculty of Information Technology, Belgrade Metropolitan University, Tadeuša Košćuška 63, 11000 Belgrade, Serbia.
Univers Access Inf Soc. 2023 Mar 21:1-14. doi: 10.1007/s10209-023-00989-w.
This study offers a comprehensive analysis of COVID-19 research in education. A multi-methods approach was used to capture the full breadth of educational research. As such, a bibliometric analysis, structural topic modeling, and qualitative synthesis of top papers were combined. A total of 4,201 articles were retrieved from Scopus, mostly published from 2019 to 2021. In this work special attention is paid to analyzing and synthesizing findings about: (i) status of research about COVID-19 regarding frequencies, venues, publishing countries, (ii) identification of main topics in the COVID-19 research, and (iii) identification of the major themes in most cited articles and their impact on the educational community. Structural topic modeling identified three main groups of topics that related to education in general, moving to online education, or diverse topics (e.g., perceptions, inclusion, medical education, engagement and motivation, well-being, and equality). A deeper analysis of the papers that received most attention revealed that problem understanding was the dominating theme of papers, followed by challenges, impact, guidance, online migration, and tools and resources. A vast number of papers were produced. However, thoughtful, well-planned, and meaningful research was hard to conceptualize or implement, and a sense of urgency led to a deluge of research with thin contributions in a time of dire need to genuine insights.
本研究对教育领域中关于新冠疫情的研究进行了全面分析。采用了多种方法来涵盖教育研究的全貌。具体而言，结合了文献计量分析、结构主题建模以及对顶级论文的定性综合分析。从Scopus数据库中检索到4201篇文章，大部分发表于2019年至2021年。在这项工作中，特别关注分析和综合以下方面的研究结果：（i）关于新冠疫情研究的频率、发表渠道、发表国家等方面的研究现状，（ii）新冠疫情研究中的主要主题识别，以及（iii）被引用次数最多的文章中的主要主题识别及其对教育界的影响。结构主题建模确定了与一般教育、转向在线教育或多样主题（如认知、包容、医学教育、参与和动机、幸福感和平等）相关的三大主题组。对最受关注的论文进行的深入分析表明，问题理解是论文的主导主题，其次是挑战、影响、指导、向在线迁移以及工具和资源。虽然产生了大量论文。然而，经过深思熟虑、精心规划且有意义的研究很难构思或实施，紧迫感导致在急需真正见解之时出现了大量贡献微薄的研究。
