Analyzing International Research Trends on Misinformation in Education Using R Programming

Objectives This study aims to analyze international research trends on misinformation in education using the R programming language. Methods Five hundred fourteen high-quality papers (SCI, SSCI, AHCI) were extracted from the Web of Science database. A big data analysis and literature review were conducted on these papers, focusing on their sources, keywords, and core research. The study was carried out in four stages: data collection, data cleaning, data analysis, and literature review. Results Research on misinformation in education has rapidly increased in recent years. The number of papers published in journals related to educational psychology and medical education was high, while those published in journals related to subject education were relatively few. The keywords related to misinformation appeared in the order of Misinformation, Fake News, and Disinformation. Keywords related to competencies for addressing misinformation appeared in the order of Media Literacy and Digital Literacy. Core research in this field included studies on specific strategies for identifying misinformation, characteristics of students in identifying misinformation, origins of the false memory effect, expansion of the concept of media literacy, and attempts to extend terminology from a science education perspective. Conclusions In Korea, there is a need to diversify international cooperation networks and pay more attention to international-level research on misinformation. Additionally, conducting more active research on dealing with misinformation from various perspectives, including specific perspectives in various subject education fields, is necessary.