• Title/Summary/Keyword: 대학기반

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Subject-Balanced Intelligent Text Summarization Scheme (주제 균형 지능형 텍스트 요약 기법)

  • Yun, Yeoil;Ko, Eunjung;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.25 no.2
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    • pp.141-166
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    • 2019
  • Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

A study on the classification of research topics based on COVID-19 academic research using Topic modeling (토픽모델링을 활용한 COVID-19 학술 연구 기반 연구 주제 분류에 관한 연구)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.155-174
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    • 2022
  • From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (

    ) were the topic modeling results for each research topic (
    ) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.

  • Review of the Korean Indigenous Species Investigation Project (2006-2020) by the National Institute of Biological Resources under the Ministry of Environment, Republic of Korea (한반도 자생생물 조사·발굴 연구사업 고찰(2006~2020))

    • Bae, Yeon Jae;Cho, Kijong;Min, Gi-Sik;Kim, Byung-Jik;Hyun, Jin-Oh;Lee, Jin Hwan;Lee, Hyang Burm;Yoon, Jung-Hoon;Hwang, Jeong Mi;Yum, Jin Hwa
      • Korean Journal of Environmental Biology
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      • v.39 no.1
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      • pp.119-135
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      • 2021
    • Korea has stepped up efforts to investigate and catalog its flora and fauna to conserve the biodiversity of the Korean Peninsula and secure biological resources since the ratification of the Convention on Biological Diversity (CBD) in 1992 and the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits (ABS) in 2010. Thus, after its establishment in 2007, the National Institute of Biological Resources (NIBR) of the Ministry of Environment of Korea initiated a project called the Korean Indigenous Species Investigation Project to investigate indigenous species on the Korean Peninsula. For 15 years since its beginning in 2006, this project has been carried out in five phases, Phase 1 from 2006-2008, Phase 2 from 2009-2011, Phase 3 from 2012-2014, Phase 4 from 2015-2017, and Phase 5 from 2018-2020. Before this project, in 2006, the number of indigenous species surveyed was 29,916. The figure was cumulatively aggregated at the end of each phase as 33,253 species for Phase 1 (2008), 38,011 species for Phase 2 (2011), 42,756 species for Phase 3 (2014), 49,027 species for Phase 4 (2017), and 54,428 species for Phase 5(2020). The number of indigenous species surveyed grew rapidly, showing an approximately 1.8-fold increase as the project progressed. These statistics showed an annual average of 2,320 newly recorded species during the project period. Among the recorded species, a total of 5,242 new species were reported in scientific publications, a great scientific achievement. During this project period, newly recorded species on the Korean Peninsula were identified using the recent taxonomic classifications as follows: 4,440 insect species (including 988 new species), 4,333 invertebrate species except for insects (including 1,492 new species), 98 vertebrate species (fish) (including nine new species), 309 plant species (including 176 vascular plant species, 133 bryophyte species, and 39 new species), 1,916 algae species (including 178 new species), 1,716 fungi and lichen species(including 309 new species), and 4,812 prokaryotic species (including 2,226 new species). The number of collected biological specimens in each phase was aggregated as follows: 247,226 for Phase 1 (2008), 207,827 for Phase 2 (2011), 287,133 for Phase 3 (2014), 244,920 for Phase 4(2017), and 144,333 for Phase 5(2020). A total of 1,131,439 specimens were obtained with an annual average of 75,429. More specifically, 281,054 insect specimens, 194,667 invertebrate specimens (except for insects), 40,100 fish specimens, 378,251 plant specimens, 140,490 algae specimens, 61,695 fungi specimens, and 35,182 prokaryotic specimens were collected. The cumulative number of researchers, which were nearly all professional taxonomists and graduate students majoring in taxonomy across the country, involved in this project was around 5,000, with an annual average of 395. The number of researchers/assistant researchers or mainly graduate students participating in Phase 1 was 597/268; 522/191 in Phase 2; 939/292 in Phase 3; 575/852 in Phase 4; and 601/1,097 in Phase 5. During this project period, 3,488 papers were published in major scientific journals. Of these, 2,320 papers were published in domestic journals and 1,168 papers were published in Science Citation Index(SCI) journals. During the project period, a total of 83.3 billion won (annual average of 5.5 billion won) or approximately US $75 million (annual average of US $5 million) was invested in investigating indigenous species and collecting specimens. This project was a large-scale research study led by the Korean government. It is considered to be a successful example of Korea's compressed development as it attracted almost all of the taxonomists in Korea and made remarkable achievements with a massive budget in a short time. The results from this project led to the National List of Species of Korea, where all species were organized by taxonomic classification. Information regarding the National List of Species of Korea is available to experts, students, and the general public (https://species.nibr.go.kr/index.do). The information, including descriptions, DNA sequences, habitats, distributions, ecological aspects, images, and multimedia, has been digitized, making contributions to scientific advancement in research fields such as phylogenetics and evolution. The species information also serves as a basis for projects aimed at species distribution and biological monitoring such as climate-sensitive biological indicator species. Moreover, the species information helps bio-industries search for useful biological resources. The most meaningful achievement of this project can be in providing support for nurturing young taxonomists like graduate students. This project has continued for the past 15 years and is still ongoing. Efforts to address issues, including species misidentification and invalid synonyms, still have to be made to enhance taxonomic research. Research needs to be conducted to investigate another 50,000 species out of the estimated 100,000 indigenous species on the Korean Peninsula.

    Color-related Query Processing for Intelligent E-Commerce Search (지능형 검색엔진을 위한 색상 질의 처리 방안)

    • Hong, Jung A;Koo, Kyo Jung;Cha, Ji Won;Seo, Ah Jeong;Yeo, Un Yeong;Kim, Jong Woo
      • Journal of Intelligence and Information Systems
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      • v.25 no.1
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      • pp.109-125
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      • 2019
    • As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

    A Comparative Study on the Effective Deep Learning for Fingerprint Recognition with Scar and Wrinkle (상처와 주름이 있는 지문 판별에 효율적인 심층 학습 비교연구)

    • Kim, JunSeob;Rim, BeanBonyka;Sung, Nak-Jun;Hong, Min
      • Journal of Internet Computing and Services
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      • v.21 no.4
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      • pp.17-23
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      • 2020
    • Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

    Using a Learning Progression to Characterize Korean Secondary Students' Knowledge and Submicroscopic Representations of the Particle Nature of Matter (Learning Progression을 적용한 중·고등학생의 '물질의 입자성'에 관한 지식과 미시적 표상에 대한 특성 분석)

    • Shin, Namsoo;Koh, Eun Jung;Choi, Chui Im;Jeong, Dae Hong
      • Journal of The Korean Association For Science Education
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      • v.34 no.5
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      • pp.437-447
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      • 2014
    • Learning progressions (LP), which describe how students may develop more sophisticated understanding over a defined period of time, can inform the design of instructional materials and assessment by providing a coherent, systematic measure of what can be regarded as "level appropriate." We developed LPs for the nature of matter for grades K-16. In order to empirically test Korean students, we revised one of the constructs and associated assessment items based on Korean National Science Standards. The assessment was administered to 124 Korean secondary students to measure their knowledge and submicroscopic representations, and to assign them to a level of learning progression for the particle nature of matter. We characterized the level of students' understanding and models of the particle nature of matter, and described how students interpret various representations of atoms and molecules to explain scientific phenomena. The results revealed that students have difficulties in understanding the relationship between the macroscopic and molecular levels of phenomena, even in high school science. Their difficulties may be attributed to a limited understanding of scientific modeling, a lack of understanding of the models used to represent the particle nature of matter, or limited understanding of the structure of matter. This work will inform assessment and curriculum materials development related to the fundamental relationship between macroscopic, observed phenomena and the behavior of atoms and molecules, and can be used to create individualized learning environments. In addition, the results contribute to scientific research literature on learning progressions on the nature of matter.

    Relationship between Entrepreneurial Education and Entrepreneurial Opportunity Recognition: Focused on the Entrepreneurship Major College Students (앙트러프러너십 교육과 창업기회인식 역량과의 관계: 숙명여대 앙트러프러너십 전공 사례를 중심으로)

    • Lee, Woo Jin;Son, Jong Seo;Oh, Hyemi
      • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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      • v.13 no.3
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      • pp.71-83
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      • 2018
    • Recently, there are many efforts to define the field of entrepreneurship as an area of independent study. According to Shane & Venkataraman, the study of entrepreneurship is moving toward understanding the combination of entrepreneurial individual and valuable opportunity in becoming entrepreneurs. In Korea, entrepreneurship education is spreading widely on the basis of universities and in 2010 the entrepreneurship major was created in Sookmyung Women's University for the first time in Korea. The results of this study are as follows. First, there are many research about examining the relationship between entrepreneurship education and entrepreneurship intention. Nevertheless, there are lack of the study focusing on the opportunity recognition which many scholars have recognized as the independent study field of entrepreneurship domain. Therefore, the purpose of this study is to examine the effect of satisfaction of entrepreneurship major education on entrepreneurial opportunity recognition and to examine the mediating effect of entrepreneurial opportunity recognition according to educational commitment. The questionnaires were carried out for 3 weeks to entrepreneurship major students in Sookmyung Woment's University. A total of 84 surveys were collected and statistically analyzed by the R program. As a result of the analysis, it was found that the satisfaction of education positively influences the recognition of entrepreneurial opportunities. Commitment also has a full mediating effect on the recognition of entrepreneurial opportunities. The results of this analysis confirm that the ability to recognize entrepreneurial opportunity is developed by entrepreneurship education, and during the study students' commitment has an important role in the relationship between educational satisfaction and entrepreneurial opportunity recognition. The results were verified through empirical analysis. Satisfaction with entrepreneurship education and awareness of entrepreneurship opportunities through entrepreneurship can be anticipated as entrepreneurship activities in the future.

    A Study on the Real Condition and the Improvement Directions for the Protection of Industrial Technology (산업기술 보호 관리실태 및 발전방안에 관한 연구)

    • Chung, Tae-Hwang;Chang, Hang-Bae
      • Korean Security Journal
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      • no.24
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      • pp.147-170
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      • 2010
    • This study is to present a improvement directions for the protection of industrial key technology. For the purpose of the study, the survey was carried out on the administrative security activity of 68 enterprises including Large companies, small-midium companies and public corporations. survey result on the 10 items of security policy, 10 items of personal management and 7 items of the assets management are as follows; First, stable foundation for the efficient implement of security policy is needed. Carrying a security policy into practice and continuous upgrade should be fulfilled with drawing-up of the policy. Also for the vitalization of security activity, arrangement of security organization and security manager are needed with mutual assistance in the company. Periodic security inspection should be practiced for the improvement of security level and security understanding. Second, the increase of investment for security job is needed for security invigoration. Securing cooperation channel with professional security facility such as National Intelligence Service, Korea internet & security agency, Information security consulting company, security research institute is needed, also security outsourcing could be considered as the method of above investment. Especially small-midium company is very vulnerable compared with Large company and public corporation in security management, so increase of government's budget for security support system is necessary. Third, human resource management is important, because the main cause of leak of confidential information is person. Regular education rate for new employee and staff members is relatively high, but the vitalization of security oath for staff members and the third party who access to key technology is necessary. Also access right to key information should be changed whenever access right changes. Reinforcement of management of resigned person such as security oath, the elimination of access right to key information and the deletion of account. is needed. Forth, the control and management of important asset including patent and design should be tightened. Classification of importance of asset and periodic inspection are necessary with the effects evaluation of leak of asset.

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    The development direction of vocational education teachers' fostering of china based on vocational teachers specialization and vocational disciplines (직업교사 전문화 및 직업과학 학과발전에 기반한 중국 직업교육 교사양성 전망 -UNESCO '국제 직업교사 석사 교육과정 구성표준'을 중심으로-)

    • Yin, Zi-Long;Zhao, Zhi-Qun;Nam, Seung-Kwon;Choi, Won-Sik
      • 대한공업교육학회지
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      • v.35 no.2
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      • pp.70-81
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      • 2010
    • The purpose of this study is to introduce formation 'International framework curriculum for a Master Degree for TVET teachers and lectures' to present implications about fostering Chinese vocational teachers and to analyze the contents related to it. In 2004, UNFSCO composed formation International framework curriculum for a Master Degree for TVET teachers and lectures ("framework curriculum") to improve the ability of professionals in the vocational education and training fields including teachers and training leaders as well as to promote international academic exchange. Universities which introduce the framework curriculum should form specialized committee and carry out education considering the specific situation including other universities' situation, students' ability, educational certification system, etc. The framework curriculum should include the latest trends of the development of international vocational education science and carry out united educational learning between several internal or external high schools. UNFSCO tries to promote the development of educational learning and study of basic departments of vocational education such as vocational educational learning theory, vocational science, etc through the framework curriculum and to improve knowledge of vocational educational teachers and realize specialization of them. The number of universities that established the master's degree of vocational education in China is approx. 20 and the number of students that they collect every year. As for the plans of the master's degree of vocational teachers in each university, the courses about the practical problems like educational courses and educational learning are insufficient. But the framework curriculum thinks that educational learning of application theory is more important and emphasizes practice about the specific area and educational learning much more. Utilization of preceding experiences of advanced countries has the important meaning in search of models that foster Chinese vocational teachers and departmental system. The framework curriculum implies several useful points in installment of majors and educational process of the process that fosters Chinese vocational teachers.

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    A Study on the Transition Process of Vocational Education as National Human Resource Development in Korea (산업인력양성 체제로서 국내 직업교육의 변천 과정 고찰)

    • Kim, Chung Hwan;Moon, Inyoung;Park, Shinhee;Kim, Ji Hyeon
      • 대한공업교육학회지
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      • v.45 no.2
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      • pp.21-45
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      • 2020
    • The purpose of this study was to verify how the vocational education for training industrial workforce as a national human resource development (NHRD) system has undergone a transition process in relation to the national economic, industrial, and socio-cultural contexts. First, how vocational education as an industrial workforce training system has changed in accordance with Korea's economic environment, industrial development, and social changes; second, what are the main factors that influenced the role and importance of vocational education; and third, vocational education as a system for training industrial workforce and training workforce in science and engineering were analyzed differently from the perspective of the NHRD model. To this end, domestic and international academic journal papers, research reports, and thesis were investigated and classified by period, and major changes in vocational education were analyzed in relation to economic, industrial, and social issues and policies by period. As a result of the research, first, as the industry advanced, the level of vocational education increased and the scope expanded. Second, vocational education tended to shrink gradually after the manufacturing industry base, and especially secondary vocational education tended to decline after the national industry focused on light industry. Third, since the 1970s, the diversification of the NHRD and jobs has resulted in wage gaps depending on the level of education, which has increased the preference for university education and avoided secondary vocational education. In addition, a NHRD model focusing on training science and engineering workforce was proposed to compare the existing NHRD model focusing on overall vocational education, and it was revealed that the NHRD needs to be subdivided into various fields or levels to derive a model and examine changes. From the results of the study, vocational education in Korea, especially in secondary vocational education, has declined due to large impacts on socio-cultural perception due to economic growth, enthusiasm for education, and external shocks such as the financial crisis, and the long-term effort to change this perception is suggested to overcome the crisis of vocational education.


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