텍스트 마이닝을 활용한 종교교육학 연구동향 분석: 불교교육학과 기독교교육학을 중심으로

초록

[Objective] The purpose of this study is to analyze research trends in Buddhist and Christian education using text mining techniques. [Contents] This study applied Python text mining techniques to automate much of the research process and utilized ChatGPT's API for tasks such as summarizing papers and extracting topics. Academic papers and theses were automatically collected from riss.kr using keywords ‘Buddhist education’ and ‘Christian education’, followed by preprocessing to remove duplicate and irrelevant papers. Trends in research by year and academic society were visualized and analyzed. Through processes such as morphological analysis, noun extraction, and paper summarization, the study identified research trends using keyword analysis, text network analysis, and topic modeling techniques. [Conclusion] Research in Christian education was approximately ten times more abundant than in Buddhist education. While research in Christian education is conducted diversely by the KSCRE and various Christian universities, Buddhist education is mainly led by the KASRE and Dongguk University. Keyword analysis and topic modeling revealed that research in Buddhist education focuses on philosophical and abstract topics such as intellectual practice, meditation, ethics, and death, whereas research in Christian education tends to focus on concrete and practical dimensions such as faith in the family, educational curriculum, and career guidance.

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