Visualization analysis of CBL application in Chinese and international medical education based on big data mining

Abstract

Objective

To employ big data mining to provide a visualization analysis of Case-Based Learning (CBL) application in Chinese and international medical education, with the aim of observing the potential applications of CBL.

Methods

All included literature was obtained from the Web of Science (WoS) core collection database, Chinese core periodicals database, Chinese Social Sciences Citation Index (CSSCI), Chinese Science Citation Database of China National Knowledge Infrastructure (CNKI), Wangfang Database, and CQVIP Database. CiteSpace software (6.1.6R6) was used to conduct an in-depth investigation from four perspectives: quantitative analysis of literature, network analysis of co-occurring authors, network analysis of co-occurring research institutions, keyword clustering and burst analysis.

Results

A total of 721 Chinese articles and 537 English articles were included, demonstrating an exponential growth trend. Notably, no author exhibited a prolific publication rate within a short timeframe. Bursting keywords in English literature encompassed topics related to students' learning, teaching curriculum, methods, and location. In contrast, Chinese literature focused on students' learning, teaching methods, courses, application fields as well as national policy and the Ministry of Education of the People’s Republic of China (MOE) guidance. The keyword clusters include research on care, community practice, special projects and groups, teaching methods, and capacity development of participants in English literature. For Chinese literature, the clusters include research national policy guidance, teaching reform, mode and evaluation and various disciplines.

Conclusion

CBL holds immense potential for implementation across diverse disciplines, community practices, and special projects within medical education. The practical application of CBL is continuously evolving in response to changing times and can be seamlessly integrated into different contexts influenced by environmental factors and policies.