The unemployed vocational training is mainly aimed at preventing out of the labor market by enhancing the unemployed ability of the unemployed through training. However, it is difficult to grasp the detailed messages hidden in the evaluation items bec...
The unemployed vocational training is mainly aimed at preventing out of the labor market by enhancing the unemployed ability of the unemployed through training. However, it is difficult to grasp the detailed messages hidden in the evaluation items because the existing research method only evaluates the quantitative score according to the criteria that the researcher has designed beforehand. The purpose of this study is to analyze the satisfaction and dissatisfaction messages of the trainees in the lecture reviews by using the unstructured data analysis technology. To this end, 119,495 cases of the unemployed vocational training program started in 2015 were collected and the sentiment dictionary was constructed by extracting satisfied and unsatisfied words with Opinion Mining Analysis Software Krkwic.
Based on this, I used NodeXL, a semantic network analysis program, And the semantic structure As a result of analysis, 'class', 'training teacher', 'vocational training institution' and 'trainee' were the main subjects of unemployed vocational training. Contents, teaching methods, class atmosphere are important. Secondly, the role of the training instructor, who is leading the class, was the most important factor. Among them, the part about the competence and attitude of the training teacher was evaluated by the trainees. Particularly, the role of the training teachers, the content of the lessons, and the atmosphere of the classes were affecting the possibility of employment of the trainees. Third, regarding the administrative support service of vocational training institutions, job support program and trainee/training teacher management part are important. Based on these results, suggestions for improvement of training quality, possibility of using Opinion Mining and semantic network analysis method in various perspectives for improvement of training environment were suggested.