http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
중국어 교재분석을 통한 감정표현기능 어법 항목 선정에 대한 고찰
崔?才(Choi, Eun-jae) 중국어문학연구회 2018 중국어문학논집 Vol.0 No.110
As we know, Currently, there are various attempts to recognize and improve the problems of the existing teaching grammar methods in the Chinese educational academy. Among these attempts, the analysis of the rich linguistic phenomena has led to a new interest in grammar education combined with the linguistic function of guiding the learners to the linguistic rules or the sentence structures that constitute the concrete linguistic behaviors. In this paper, As a part of research that combines phonics function and phonetics, I extracted the phonetic rules that constitute these emotional expression functions through the analysis of textbooks, focusing on the frequently used emotional expressions among various phonetic functions. In other words, it is because I think that it is possible to increase the efficiency and interest of the teaching of phonics at the same time by examining what kind of language forms the emotional expressions that are frequently used in everyday life. In addition, when extracting these formats based on language phenomena, using textbooks as a source of data collection would be an effective way to secure both representative and reliability of the data. In this paper, we first examine the previous studies related to phonology and phonology combination, and then, based on this, we extracted the phonetic items that constitute emotional expressive behavior through text analysis. Finally, we discussed how to use these teaching methods in practical teaching and how to use them in education.
빅데이터 기법을 활용한 국내 ‘중국어교육’에 대한 사회 인식 연구
崔?才(Choi, Eun-jae) 중국어문학연구회 2019 중국어문학논집 Vol.0 No.116
Currently, Korea’s Chinese education academia need to make rapid adjustment efforts to switch to a Chinese language education system that trains suitable talent in the era of the fourth industrial revolution demanded by the future society. However, the most important task to precede before attempting these changes and innovations will be to first accurately analyze the needs of the era associated with Chinese language and the current social cognitions and trends of each educational element in our country, and then set the direction and specific methods of change and innovation based on the results. It is the ’big data analysis method’ that has emerged as the most powerful and scientific method of analysis in solving these social cognitions and social issues. In this study, we intend to use these big data analysis methods to accurately analyze the current social awareness of Chinese language in our country and set the pre-preparation and direction of future Chinese education. In order to analyze the concept of our society’s cognitions of Chinese education more specifically and systematically using these text mining techniques and social network analysis methods, we will first conduct a big data collection to include all three aspects of education: ‘Professor,’ ‘student’ and ‘media’. The collection period was set at five years from March 1, 2014 to March 1, 2019, and the data collection channels were included in the collection data from the headquarters of the country’s largest portal sites, ‘NAVER’ and ‘DAUM’, as well as the two-way social media channels, ‘YOUTUBE’ and ‘FACEBOOK’. The collection method set “Chinese” as an essential inclusion word within the above collection channel, selected “education” as a word that could represent “professor,” “learning” as a word that could represent “student,” and “teaching” as a word that could represent “media” to extract all data that contained these words and analyze social networks. Finally, based on this, we discussed the future direction of Chinese education starting from the perspective of social demand for Chinese education.
빅데이터 텍스트 마이닝을 활용한 국내 중국어 교육 관련 학위 논문 동향 분석 - 2009-2019년까지 20년간 연구 성과를 중심으로
崔?才(Choi, Eun-jae) 중국어문학연구회 2019 중국어문학논집 Vol.0 No.119
In this paper, I selected the research achievements of the dissertation papers related to Chinese language education and analyze the research trends of 20 years. As such, we are going to utilize big data analysis methods to identify trends in research related to Chinese education in this paper. By utilizing big data analysis techniques, we want to understand the overall research trends of Chinese education-related dissertations published in Korea from 2000 to 2019. To that end, the paper"s title, publication date and abstracts of the dissertation, which were searched as keywords, were used as analysis data for the main paper. In particular, abstracts was divided into English and Korean literature records, so they were collected by dividing them into English data and Korean data. And I used one of the big data analysis techniques, the text mining technique, to extract key word words and explore the interrelated relationship between words through the n-gram analysis method. In order to analyze the overall research trends of the 20 years of the dissertation on Chinese education and to identify the trend of change in research trends along the time stream, this paper divided the 20 years into four quarters in total and carried out the extraction of key keyword words for each quarter. And through keyword analysis we will consider the characteristics of Chinese education research in each era. Finally, based on the above results, I discussed the direction of future Chinese education research and how to develop.