역사 교육에 있어서 주제학습 방법론의 이론과 적용

최정순 ( Jung Sun Choi ) 역사교육학회 2004 역사교육논집 Vol.32 No.-

The studying with topics is the method that students can take the lead in class, and can know synthetically the mutual relation of historical facts. Because they can apply fragmentary knowledge to a topic. That method is distinguished from the studying with the theme which is extracted from inclusively, scientifically, and structurally important concepts. It means that students themselves select, and study something with historical value among topics they are interested in. The procedure of the studying with topics is firstly that teachers select a central topic among topics students decided in order to know the general historical feature. Secondly, students compose small topics on the basis of a central topic, and draw up the topic network Thirdly, they form a unit, and make a plan for the studying with topics. The studying with topics is required a close attention in a project. Because it means that together teachers with students should reconstitute a education substance, while subject education means that a education substance is already decided in accordance with units. The lesson hours is not fixed fifty minutes. Teachers should regard the total studying hours for some topics as a unit. They should give notice of a central topic to students before a week Only if it is that way, students can rehearsal. Teachers should inform students of a bibliography, a data, etc. It is effective that students utilize the audio-visual materials such as slide, movie, video, and OHP. It is desirable that teachers mark continually in class. The standard of an assessment is whether students achieve a subject with human and material resources or not. To form the positive self it should be graded and commented positively. To be effective the studying with topics, teachers should know a topic which students are concerned about, and are interested in. And they should research various studying methods, and should have a profound knowledge about all of the history.

독후감 텍스트의 토픽모델링 적용에 관한 탐색적 연구

이수상 한국도서관·정보학회 2016 한국도서관정보학회지 Vol.47 No.4

The purpose of this study is to explore application of topic modeling for topic analysis of book report. Topic modeling can be understood as one method of topic analysis. This analysis was conducted with texts in 23 book reports using LDA function of the “topicmodels” package provided by R. According to the result of topic modeling, 16 topics were extracted. The topic network was constructed by the relation between the topics and keywords, and the book report network was constructed by the relation between book report cases and topics. Next, Centrality analysis was conducted targeting the topic network and book report network. The result of this study is following these. First, 16 topics are shown as network which has one component. In other words, 16 topics are interrelated. Second, book report was divided into 2 groups, book reports with high centrality and book reports with low centrality. The former group has similarities with others, the latter group has differences with others in aspect of the topics of book reports. The result of topic modeling is useful to identify book reports’ topics combining with network analysis. 이 연구는 독후감 텍스트의 주제분석에 토픽모델링의 활용방안을 탐색하는 것을 목적으로 하고 있다. 텍스트의 주제분석 방안으로서 토픽모델링 분석방법을 이해하고, R에서 제공하는 “topicmodels” 패키지의 LDA 함수를 사용하여 23건의 사례 독후감 텍스트들을 대상으로 실제의 분석작업을 수행하였다. 토픽모델링 분석결과 16개의 토픽들을 추출하였고, 토픽과 구성 단어들의 관계에서 토픽 네트워크, 사례 독후감과 토픽들의 관계에서 독후감 네트워크를 구성하였다. 이후 토픽 네트워크와 독후감 네트워크를 대상으로 중심성 분석을 수행하였으며, 분석결과는 다음과 같다. 첫째, 16개의 토픽들이 1개의 컴포넌트를 가지는 네트워크로 나타났다. 이것은 16개 토픽들이 상호 연관되어 있다는 것을 의미한다. 둘째, 독후감 네트워크에서는 연결정도 중심성이 높은 독후감들과 낮은 독후감들로 구분이 되었다. 전자의 독후감들은 다른 독후감들과 주제적으로 유사성을 가지며, 후자의 독후감들은 다른 독후감들과 주제적으로 상이성을 가지는 것으로 해석하였다. 토픽모델링의 결과를 네트워크 분석과 결합함으로써 독후감의 주제파악에 유용한 결과들을 얻게 되었다.

토픽모델링을 활용한 농촌연구 동향분석

김가은,정유경,임영훈 한국농촌계획학회 2023 농촌계획 Vol.29 No.4

The purpose of this study is to identify rural research topics, differences in research topics over time, and key mediators through the analysis of academic research trends using topic modeling. This study analyzed a total of 1,183 articles published in the Journal of Rural Planning and Rural Society over a 23-year period (2000-2022). We categorized rural research topics into 30, examined the proportion of research in each topic, and identified major changes in research topics over time. We also identified key words that mediate between research topics. The study found that, first, rural research trends can be categorized into five types (resources and utilization, area/space, people, ecosystem/environment, and tourism), with area/space being the most studied. Subtopics include rural amenities, rural disappearance/village miniaturization, and rural landscape management. Second, the research topics for each period were different. In the first period(2003-2007), the main research topics were rural amenities and Agricultural production- based climate vulnerability assessment. In the second period(2008-2012), the main research topics were Rural extinction and village depopulation, and rural landscape management, and in the third period(2013-2017), the main research topics were rural sixth industrialization and rural ecotourism. In the fourth period(2018-2022), rural development planning and rural life services(life SOC) were the main research topics. The significance of this study is that it extends the existing method of analyzing research trends and provides basic data to enhance comprehensive insights and understanding of rural research.

텍스트 마이닝과 소셜 네트워크 기법을 활용한 국제무역 키워드, 중심성과 토픽에 대한 빅데이터 분석

이재득 한국무역학회 2022 貿易學會誌 Vol.47 No.4

This study aims to analyze international trade papers published in Korea during the past 2002-2022 years. Through this study, it is possible to understand the main subject and direction of research in Korea’s international trade field. As the research mythologies, this study uses the big data analysis such as the text mining and Social Network Analysis such as frequency analysis, several centrality analysis, and topic analysis. After analyzing the empirical results, the frequency of key word is very high in trade, export, tariff, market, industry, and the performance of firm. However, there has been a tendency to include logistics, e-business, value and chain, and innovation over the time. The degree and closeness centrality analyses also show that the higher frequency key words also have been higher in the degree and closeness centrality. In contrast, the order of eigenvector centrality seems to be different from those of the degree and closeness centrality. The ego network shows the density of business, sale, exchange, and integration appears to be high in order unlike the frequency analysis. The topic analysis shows that the export, trade, tariff, logstics, innovation, industry, value, and chain seem to have high the probabilities of included in several topics.

한국의 중남미 지역연구 네트워크와 중심성 및 무역과 경제에 대한 토픽 변동분석

이재득 한국무역학회 2022 貿易學會誌 Vol.47 No.6

This study aims to analyze Latin America and the Caribbean papers published in Korea during the past 2000-2020 years. Through this study, it is possible to understand the main subject and direction of research in Korea’s Latin America and the Caribbean area. As the research mythologies, this study uses the text mining and Social Network Analysis such as frequency analysis, several centrality analyses, and topic analysis. After analyzing the empirical results, there has been a tendency to change the key words and centrality coefficients between 2000-2010 and 2011-2020 years. During 2011-2020 years, the most frequent keywords were changed from Neoliberalism and culture to policy education, and economy related words. The degree and closeness centrality analyses appeared the higher frequency key words. However, the eigenvector centrality appeared very different from the order of frequency key words. The topic analysis shows that the culture, language, and Neoliberalism were the most important keywords during 2000-2010 years but economy, labor trade, industry, development became the most important keywords during 2011-2020 years in topics.

한국의 동남아 연구에 대한 텍스트 마이닝과 네트워크 및 토픽 분석

이재득,서지민 한국무역학회 2023 貿易學會誌 Vol.48 No.5

본 연구는 2000년부터 2020년까지 동남아 연구들을 추정하면 첫째, 텍스트 마이닝 기법으로 추정한 결과, 2000-2010년 동안은 주로 동남아 국가들과 그 국가정책 등 정치적인 키워드가 높게 나타난 반면, 2011-2020년 동안은 언어와 교육 그리고 경제 및 사회와 교육 등에 대한 연구가 더 많이 나타났다. 둘째, 2000-2010년에는 연결 중심성 추정결과, 중국과 베트남, 필리핀. 태국과 한국등에 대한 순위가 높게 나타났다. 셋째, 2011-2020년에는 연결과 아이겐벡터 중심성 추정결과, 경제발전, 사회, 정부, 정책, 시간, 교육, 언어, 인간 등에 대한 키워드의 순위가 높게 나타났다. 넷째, 2000-2010년에는 태국, 베트남, 인도네시아, 필리핀 등과 중국, 정치와 정당, 시스템이 주요한 토픽으로 났다. 그러나 2011-2020년에는 개인과 여성, 사회, 삶과 변화, 언어와 학생과 교육, 경제개발과 지역 정체성 등 문화와 사회와 개인과 여성 등으로 다양한 토픽으로 변동되어 나타났다. This paper analyzes the studies on Korea’s t Asia during the past 2000-2020 years using the text mining and Social Network and topic modeling analysis. While the frequent keywords were regional countries’ policies during 2000-2010 years, the main keywords were changed to the languages, education, and development during 2011-2020 years. According to the degree and closeness centrality analyses, the main keywords were the ASEAN, China, Vietnam, Philippine, Thailand. and Korea. However, the eigenvector centrality results show differently from the degree and closeness centrality. While the political factors were more important keywords during 2000-2010, the soft power issues such as education, language, society and time appeared more interesting keywords during 2011-2020. The topic modeling analysis also shows the changes over period. While the policy, party, and system are important topics during 2000-2010, the relatively soft issues appeared as more important topics such as individual, woman, society, life, languages, education, student, and economic development during 2011-2020.

『한국기록관리학회지』 논문의 연구 주제 분석 - 2001년부터 2017년까지 -

김희섭,강보라 한국기록관리학회 2018 한국기록관리학회지 Vol.18 No.4

본 연구의 목적은 『한국기록관리학회지』에 게재된 논문의 연구 주제를 분석하는 것이다. 연구 목적을 달성하기 위하여 해당 학회지의 창간호(2001년)부터 최근(2017년)까지 발표된 논문 390편을 대상으로 해당 논문의 저자가 부여한 한글 키워드 875개를 수집하였다. 수집된 키워드는 NetMiner V.4를 이용하여 이들 연구 주제의 양적측면, 영향력 측면, 그리고 확장성 측면을 분석하였다. 분석 결과 연구 주제의 양적인 측면에서는 ‘기록정보서비스’, ‘전자기록물’, ‘역사기록물’, ‘아키비스트’, ‘국가기록원’ 순으로 나타났고, 영향력 측면에서는 ‘기록정보서비스’, ‘전자기록물’, ‘평가’, ‘지역기록물’, ‘검색시스템'등의 순으로 나타났고, 확장성 측면에서는 ‘기록정보서비스’, ‘아키비스트’, ‘전자기록물’, ‘아카이브’, ‘메타데이터’등의 순으로 파악되었다. The main purpose of this study was to investigate the research topics of the Journal of Korean Society of Archives and Records Management, which is one of the main academic journals of archival research in Korea. To achieve this objective, a total of 875 author-assigned Korean keywords were collected from the 390 papers published from the first issue (i.e., 2001) to the current issue (i.e., 2017) in the target journal. The collected keywords were analyzed using NetMiner V.4 to discover their frequency, degree centrality, and betweenness centrality. Results showed that “Archival Information Services,” “Electronic Records,” “Historical Archives,” “Archivists,” and “National Archives of Korea” showed the most frequently conducted research topics; whereas “Archival Information Services,” “Electronic Records,” “Evaluation,” “Locality Archives,” and “Retrieval System” were the most influencing research topics. On the other hand, “Archival Information Services,” “Archivists,” “Electronic Records,” “Archive,” and “Metadata” showed the most widely intervening research topics in this research.

빅데이터 분석을 활용한 소비자의 업사이클링 인식에 대한 탐색적 연구

조윤진 국제차세대융합기술학회 2022 차세대융합기술학회논문지 Vol.6 No.2

본 연구의 목적은 빅데이터 분석을 통해 업사이클링에 대한 소비자 인식을 파악하는 것이다. 이를 위해 2020년과 2021년을 구분하여 ‘업사이클링’에 대한 빅데이터를 수집하고, 기간별, 채널별 수집량 추이를 분석하였다. 또한 빈도수, 중심성, 그리고 토픽모델링 분석을 실시하였으며 연구 결과는 다음과 같다. 첫째, 기간별, 채널별 추 이를 분석한 결과 2021년의 검색 건수가 2020년에 비해 증가하였고, 채널 중에서는 블로그의 검색 건수가 다른 채널에 비해 많이 나타났다. 둘째, 두 기간 모두 ‘업사이클링’, ‘활용’, ‘리사이클링’, ‘친환경’, ‘제품’ 등의 단어들이 높은 빈도를 보였다. TF-IDF, 연결중심성을 빈도와 비교한 결과, 빈도와 중심성 수치에서 차이를 보이는 단어들 을 밝혀내었다. 셋째, 업사이클링에 대한 잠재적인 주제를 도출하기 위해 토픽모델링 분석을 실시한 결과, 2020년 은 4개의 주제, 2021년은 3개의 주제로 구분되었다. 본 연구는 업사이클링에 대한 현재적 관심과 인식을 파악함으 로써 관련 산업에 대한 통찰력을 제공하였다는 점에서 의의가 있다. The objective of this study is to investigate consumers’ perception on upcycling and related trends through big data analysis. The data containing the key word, ‘upcycling’ were collected from January 1, 2020 to December 31, 2021. Trends of the collected big data were analyzed by period and by channel. Additional analyses based on frequency, centrality and topic modeling were performed. The results are as follows. First, the search volume increased in 2021, compared to 2020. Also, among channels, the number of searches in blogs was higher than that of the others. Second, this study identified the top 50 words in frequency and found major 5 key words. The key words were ‘upcycling’, ‘utilization’, ‘recycling’, ‘ecofreindly’, and ‘product’ in the order of frequency of use. Comparing centrality with frequency revealed that the major key words in frequency differs from those in centrality. Third, as a result of topic modeling analysis to derive potential topics for upcycling, key words were divided into 4 topics in 2020 and 3 topics in 2021. This study is meaningful in that it identified consumers’ current interests and perceptions on upcycling to provide insights into the fashion industry.

토픽모델링을 활용한 물리학 독서감상문 텍스트의 교육과정 연계성 분석

임정훈 한국도서관·정보학회 2022 한국도서관정보학회지 Vol.53 No.2

This study analyzed the relevance of the curriculum by applying topic modeling to book reports written as content area reading activities in the ‘physics’ class. In order to carry out the research, 332 physics book reports were collected to analyze the relevance among keywords and topics were extracted using STM. The result of the analysis showed that the main keywords of the physics book reports were ‘thought’, ‘content’, ‘explain’, ‘theory’, ‘person’, ‘understanding’. To examine the influence and connection relationship of the derived keywords, the study presented degree centrality, between centrality, and eigenvetor centrality. As a result of the topic modeling analysis, eleven topics related to the physics curriculum were extracted, and the curriculum linkage could be drawn in three subjects (Physics I, Physics II, Science History), and six areas (force and motion, modern physics, wave, heat and energy, Western science history, and What is science). The analyzed results can be used as evidence for a more systematic implementation of content area reading activities which reflect the subject characteristics in the future. 본 연구는 ‘물리학’ 수업에서 교과독서 활동으로 작성된 독후감상문의 교육과정 연계성을 분석하는데 목적이 있다. 연구를 수행하기 위해 교과독서 활동으로 작성한 332편의 물리학 독서감상문을 수집하여 키워드와 키워드들의 연결 관계를 분석하고, STM(Structural Topic Modeling)을 적용하여 토픽을 추출하였다. 분석 결과, 물리학 독서감상문의 주요 키워드는 ‘생각’, ‘내용’, ‘설명’, ‘이론’, ‘사람’, ‘이해’ 등으로 나타났으며, 도출된 키워드의 영향력과 연결 관계를 살펴보기 위해 연결중심성, 매개중심성, 위세중심성을 제시하였다. 토픽모델링 분석 결과, 물리학 교육과정과 관련된 11개 토픽이 추출되었으며, 3과목(물리학Ⅰ, 물리학Ⅱ, 과학사), 6개 영역(힘과 운동, 현대물리, 파동, 열과 에너지, 서양과학사, 과학이란 무엇인가)에서 교육과정 연계성을 확인할 수 있었다. 본 연구의 결과는 추후 교과 특성을 반영한 교과독서를 보다 체계적으로 시행할 수 있는 근거자료로 활용할 수 있을 것이다.

「통일교육 지원법」상 대학에서의 통일교육 활성화를 위한 대학생 통일 인식 연구

김대홍(Kim, Dae Hong),김성태(Kim, Sung-Tae) 숭실대학교 법학연구소 2023 法學論叢 Vol.56 No.-

본 연구에서는 「통일교육 지원법」상 대학에서의 통일교육 활성화를 위한 대학생 통일 인식 연구를 위해 숭실대학교 학보인 숭대시보에서 통일, 북한, 분단, 남북으로 검색되는 기사를 대상으로 하여 텍스트 네트워크 분석을 시도하였다. 기사의 시기는 박근혜 정부 시기와 문재인 정부 시기로 구분하였다. 구체적으로는 토픽 모델링과 연결 중심성, 에코 네트워크 분석 기법을 활용하였고 분석 프로그램으로는 NetMiner를 사용하였다. 토픽 모델링은 분석 대상인 해당 텍스트 집단을 가장 잘 드러내는 토픽으로 범주화하는 것이고, 연결 중심성 분석은 전체 텍스트 내에서 영향력을 갖는 단어들을 추출, 분석하는 것이다. 에고 네트워크 분석은 주어진 텍스트에서 주요 단어들 간의 개별적인 연결 관계를 분석하는 것이다. 분석 결과를 보면, 토픽 모델링과 연결 중심성, 에코 네트워크 분석 결과 모두 박근혜 정부 시기와 문재인 정부 시기 유의미한 차이를 보이지 않았다. 연결 중심성에서는 숭실, 통일, 대학, 북한 등의 단어들이 강한 연결 중심성을 갖는 노드들로 동일하게 나타나기도 하였다. 학보를 통해 나타난 대학생 통일 인식은 정부 성향이나 시사적 이슈보다는 학교의 통일 관련교육이나 과목, 연구, 연수 등에 영향을 받는 것으로 나타났다. 이러한 점들은 장기적 관점에서 대학에서의 통일교육 활성화를 위해 고려되어야 점이라고 할 수 있다. In this study, I attempted to conduct a text network analysis of college students perceptions of reunification in order to promote reunification education at universities, in accordance with the Unification Education Support Act using articles from the student newspaper at Soongsil University, which were searched for the keywords unification, North Korea, division, and North and South. The articles were divided into the Park government period and the Moon government period. Specifically, I utilized Topic Modeling, Degree Centrality, and Ego Network analysis, using NetMiner as the analysis program. Topic Modeling categorizes the target text group into the most revealing topics. Degree Centrality analysis extracts and analyzes words that have influence throughout the entire text, while Ego Network analysis analyzes individual connections between key words in the given text. The analysis results showed no significant differences in the results of Topic modeling, Degree Centrality, and Ego Network analysis between the Park and the Moon government periods. In Degree Centrality, words such as Soongsil, Unification, University, and North Korea appeared the same as nodes with strong connection centrality. The perception of reunification among college students, as expressed through the student newspaper, was shown to be influenced by the universitys reunification-related education, courses, research, and training, rather than the governments orientation or current issues. These points should be considered for the long-term promotion of reunification education at universities.