텍스트 마이닝과 키워드 네트워크 분석을 활용한 중등 국어교사임용시험 작문 문항 분석
An Analysis on Contents of the Korean Examination writing question for Secondary-School Teacher’s Employment Using Text Mining and Semantic Network Analysis
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초록
The purpose of this study is to objectively analyze the central contents and the tendency of the questions of the writing questions of the Secondary Korean Teachers' Employment Examination (Students 2009-2018) by applying text mining and language network analysis method In systematic diagnosis. As a research method, we analyzed the frequency of key words through text mining and the centrality analysis and visualization of language network. The analysis was conducted based on three centralities, Betweenness Centrality and Closeness Centrality. The top frequency keywords extracted from the 2009-2013 school years were composition, content, data, reader, student, method, and class. Among these higher frequency keywords, the key words of composition, content, and data had a high degree of linkage. The top frequency keywords extracted from 2014 to 2019 were teachers, students, methods, classes, and some. Among them, the key words of teacher showed high values in the centrality analysis. In addition, the mediation of activity keywords was higher than that of teachers. These findings expand the scope of the Korean Language and Item Analysis research on the employment examination for secondary school teachers, and derive ways to improve the research system at the national language level or to improve the employment examination system to be implemented after 2019 since the introduction of the 2015 revised curriculum. It is expected to provide meaningful information for the study.
Abstract
The purpose of this study is to objectively analyze the central contents and the tendency of the questions of the writing questions of the Secondary Korean Teachers' Employment Examination (Students 2009-2018) by applying text mining and language network analysis method In systematic diagnosis. As a research method, we analyzed the frequency of key words through text mining and the centrality analysis and visualization of language network. The analysis was conducted based on three centralities, Betweenness Centrality and Closeness Centrality. The top frequency keywords extracted from the 2009-2013 school years were composition, content, data, reader, student, method, and class. Among these higher frequency keywords, the key words of composition, content, and data had a high degree of linkage. The top frequency keywords extracted from 2014 to 2019 were teachers, students, methods, classes, and some. Among them, the key words of teacher showed high values in the centrality analysis. In addition, the mediation of activity keywords was higher than that of teachers. These findings expand the scope of the Korean Language and Item Analysis research on the employment examination for secondary school teachers, and derive ways to improve the research system at the national language level or to improve the employment examination system to be implemented after 2019 since the introduction of the 2015 revised curriculum. It is expected to provide meaningful information for the study.
참고문헌 (14)
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