This study analyzed the issues concerning the private education of children using the big data-based Topic Modeling analysis method. We collected text on the private education of children in digital spaces, including the Education Ministry documents, ...
This study analyzed the issues concerning the private education of children using the big data-based Topic Modeling analysis method. We collected text on the private education of children in digital spaces, including the Education Ministry documents, policy research reports, newspaper articles, blogs, Naver and Daum, and analyzed the meaning by analyzing the topic of children's private education through Topic Modeling analysis and analyzing the network between concepts. The study was conducted and the results were interpreted as follows. First, the analysis of media articles and mam cafe showed that six topics were extracted, and the interpretation of the topic shows that media articles and government documents tend to consider infant education in connection with the government's education policy. Among the words, education for gifted children, the free semester system, the connection of the College Scholastic Ability Test, and free child care are key topics and key words for education policy. In deciding on various aspects of infant education, it can be seen that infant education is determined in conjunction with education policy as it tends to be related to the education policy currently pursued by the government. Second, the data analysis of Mam Kafé showed that the main body of education for infants plays a big role among parents. Words related to English such as English proficiency index and English kindergarten are found to be related to infant education. This was similar in word cloud analysis. It is necessary to consider that the contents of infant and child history education are concentrated in English, not scattered by various contents of infant recognition, emotional development, etc. It is interesting to note that the level of private education in infants and toddlers is focused on English, unlike the current policy of lowering the importance of English and covering English in public education.
This study analyzed the issues concerning the private education of children using the big data-based Topic Modeling analysis method. We collected text on the private education of children in digital spaces, including the Education Ministry documents, policy research reports, newspaper articles, blogs, Naver and Daum, and analyzed the meaning by analyzing the topic of children's private education through Topic Modeling analysis and analyzing the network between concepts. The study was conducted and the results were interpreted as follows. First, the analysis of media articles and mamcafes showed that six topics were extracted, and the interpretation of the topic shows that media articles and government documents tend to consider infant education in connection with the government's education policy. Among the words, education for gifted children, the free semester system, the connection of the College Scholastic Ability Test, and free childcare are key topics and keywords for education policy. In deciding on various aspects of infant education, it can be seen that infant education is determined in conjunction with education policy as it tends to be related to the education policy currently pursued by the government. Second, the data analysis of Mam cafe showed that the main body of education for infants plays a big role among parents. Words related to English such as English proficiency index and English kindergarten are found to be related to infant education. This was similar in word cloud analysis. It is necessary to consider that the contents of infant and child history education are concentrated in English, not scattered by various contents of infant recognition, emotional development, etc. It is interesting to note that the level of private education in infants and toddlers is focused on English, unlike the current policy of lowering the importance of English and covering English in public education.
This study analyzed the issues concerning the private education of children using the big data-based Topic Modeling analysis method. We collected text on the private education of children in digital spaces, including the Education Ministry documents, policy research reports, newspaper articles, blogs, Naver and Daum, and analyzed the meaning by analyzing the topic of children's private education through Topic Modeling analysis and analyzing the network between concepts. The study was conducted and the results were interpreted as follows. First, the analysis of media articles and mamcafes showed that six topics were extracted, and the interpretation of the topic shows that media articles and government documents tend to consider infant education in connection with the government's education policy. Among the words, education for gifted children, the free semester system, the connection of the CSAT, the College Scholastic Ability Test, and free childcare are key topics and keywords for education policy. In deciding on various aspects of infant education, it can be seen that infant education is determined in conjunction with education policy as it tends to be related to the education policy currently pursued by the government. Second, the data analysis of Mam Kafé showed that the main body of education for infants plays a big role among parents. Words related to English such as English proficiency index and English kindergarten are found to be related to infant education. This was similar in word cloud analysis. It is necessary to consider that the contents of infant and child history education are concentrated in English, not scattered by various contents of infant recognition, emotional development, etc. It is interesting to note that the level of private education in infants and toddlers is focused on English, unlike the current policy of lowering the importance of English and covering English in public education.