키워드 네트워크 분석을 활용한 직업교육연구 학회지의 연구동향 분석

Abstract

The purpose of this study is to identify the research trends and characteristics related to domestic vocational education and training through a keyword network analysis method of papers published in the Journal of Vocational Education Research to find the direction in which vocational education should proceed. For the 577 publications published from 2008 to 2020, the frequency analysis of key words in the government period and their network structure were analyzed. In frequency analysis, words such as self-efficacy, satisfaction and specialized high schools are common keywords in the top 20 of each period. The results of keyword network analysis showed that the Degree centrality of the Lee Myung-bak administration was high in the keywords of self-efficacy and career maturity. In the case of Betweenness centrality, the keywords of self-efficacy and career maturity were high. In the Degree centrality of the Park Geun-hye administration, the keywords of self-efficacy and career maturity were high. In the case of Betweenness centrality, the keywords of self-efficacy and college student were high. As for the Degree centrality of the Moon Jae-in administration, the keywords of satisfaction and self-efficacy were high. In the case of Betweenness centrality, the keywords of job satisfaction and satisfaction were high. Based on the results of this study, the future direction and implications of vocational education and training are as follows. There was a quantitative increase in the number of key words in the papers, and keywords attracting attention were found in each government. However, I think that the lack or absence of keywords that have recently shown a lot of interest, such as the Fourth Industrial Revolution or Corona-19, is an issue that should be explored for future research and vocational education research. I hope that there will be active research in new fields such as big data, AI, non-face-to-face classes, and blended learning in the future.