Exploring the Characteristics and Key Topics of the Faculty Learning Community

Purpose: The purpose of the study was to deepen understanding of the Faculty Learning Community by exploring the operational and practical characteristics and the main educational topics. Methods: Text data analysis was conducted on 50 results reports conducted at University A from 2019 to 2024. Using libraries such as KoNLPy(Okt) and Gensim in the Python 3.10 environment, data pre-processing and topic modeling were conducted in two stages. The Latent Dirichlet Allocation(LDA) was applied using the document-word matrix generated through this process as an input value. In addition, case analysis was performed based on the main topics. Results: As a result of the analysis, it was found that about eight teams and approximately five people per team participated in the Faculty Learning Community every year at University A, with the research being mainly conducted by applying the research method of literature analysis and case analysis. As a result of text mining, various keywords were derived every year, and the main topics were also diverse. Conclusion: Based on the research results, the educational implications of the Faculty Learning Community were derived, and the necessity of establishing a university-level support strategy and graduate professional development system were suggested.