• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.133-143
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• 2019

When writing historical dramas, there was an argument that restoring the language of the times was the responsibility of the playwright, but no full-scale research was done. There was no collaborative study between playwrights and Korean Language scholars. So far, many playwrights have considered it the responsibility of Korean Language scholars to discover and restore language. However, it is a medium that can easily meet the public like a play or movie, and it should have a great responsibility for creation. Language changes with time, so restoring the language of the time in plays and scenarios can lead to difficulties in communicating with modern audiences. However, the change of language according to the times means that it captures the social image and fashion of the time Therefore, language restoration in historical dream means that scenes and backgrounds can be described more realistically. Restore of language is not just necessary to improve the creative environment; it should be understood as the responsibility of the artist to meet the ability of the audience to understand the language of the times already learned. The playwright who writes the historical drama should not only learn the grammar of the background era, but also find out the lost pronunciation and the changed vocabulary so that he can use various dialogues.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.276-279
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• 2022

The 4th industrial revolution refers to the transition to a knowledge society in which the production speed of knowledge is fast and the proportion of the knowledge industry is greatly increased. The reorganization of the industrial structure and the change of occupations and jobs due to new technologies are bringing about changes in education, and the development of digital technology has made education that is borderless, individual and dynamic, becoming the new standard of education. With these changes, interest in nano-degrees on new technologies or micro-degrees focused on core courses rather than regular course degrees is increasing. As a representative example, Udacity in the United States has opened and operated online nanodegree courses related to jobs, and collaborates with major companies to develop and educate core training courses necessary for companies, thereby efficiently supporting companies in securing talent. With the revitalization of online vocational and job training, an environment has been prepared in which individuals can set goals for vocational competency development and continue their portfolio-based sustainable learning. However, for effective vocational education, automated and personalized educational content design should be preceded. To this end, in this paper, we propose a personalized career and course map recommendation system in the era of online learning

• Korean Journal of Poultry Science
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• v.16 no.2
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• pp.105-127
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• 1989

Although poultry industry in Japan has been much developed in recent years, it still needs to be developed , compared with developed countries. Since the poultry market in Korea is expected to be opened in the near future it is necessary to maximize the Productivity to reduce the production costs and to develop the scientific, technologies and management organization systems for the improvement of the quality in poultry production. Followings ale the summary of poultry industry in Japan. 1. Poultry industry in Japan is almost specized and commercialized and its management system is ： integrated, cooperative and developed to industrialized intensive style. Therefore, they have competitive power in the international poultry markets. 2. Average egg weight is 48-50g per day (Max. 54g) and feed requirement is 2. 1-2. 3. 3. The management organization system is specialized and farmers in small scale form complex and farmers in large scale are integrated.

• Journal of Korean Home Economics Education Association
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• v.31 no.3
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• pp.91-116
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• 2019

The purpose of this study is to examine the meaning of Changemaker education and to investigate the significance of Changemaker education in home economics education through a study of growth of learners applying the TEMPS program. To this end, first, the concept of Changemaker education was defined. Changemaker education is an education that changes society in a positive direction through a process of thinking about, learning about, making, and participating(playing) in various problems that we face in real life and drawing out solutions and share he solutions with others. Second, in this reasearch, the direction of Changemaker education is to make them interested in social problems and solve it and to make both the family and the career life happy and healthy by collaborating with other people. The scope of the contents is defined as "the selection of the content elements of the five domains of the child family, diet nutrition, clothing, housing and consumer life". As a way of teaching, we suggested that the TEMPS phase is followed so that the session purpose is achieved. Third, the Changemaker program consists of five steps of TEMPS among the five key ideas of Changemaker education. T(Thinking) is the step of understanding the problem and thinking about how to solve it, and E(Education) is getting the background for the next step. M(Making) is a step to create a target for problem solving, and P(Participation) and P(Play) are steps to Participation and enjoy. S(Share) is a step of changing the society through the result display, SNS sharing, and class presentation. In this study, 12 programs for middle school and 15 programs for high school were developed on the basis of TEMPS level. Each of the programs consists of 2 to 12 unit hours, which add up to 68 hours in the middle school program and 68 in high school. The learners who participated in the Changemaker program for one year (March 2, 2018~December 31, 2018) will experience improvement in many aspects including the linkage of life and education, practical ability, self-directed learning, self-esteem, sense of achievement and self-reflection, sensory observation, and so on.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.179-194
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• 2024

The aim of this study was to explore how a novice science teacher's epistemological framing, characterized from her modeling instruction, evolved over time. We observed that the teachers' framing changed over time, as she collaborated with researchers to plan, facilitate, and reflect on a series of lessons to support students' small-group scientific modeling. We tried to understand how such experiences contributed to the changes in her framing. One 8th grade science teacher with two years of teaching experience participated in the study. The teacher collaborated with researchers for four months to co-plan and facilitate 18 lessons that included small-group scientific modeling. She also engaged in cogenerative reflection on the lessons for 13 times. All of her lessons and reflections were video-recorded, transcribed, and qualitatively analyzed for the purpose of the study. Our findings showed that the teacher's epistemological framing, characterized from her interactions with students during modeling lessons, evolved during the study period: transitioning from an emphasis on students merely "filling in blanks" to prioritizing "constructing personal reasoning" and ultimately to focusing on the "social construction of scientific reasoning." The teacher's perception about what students are capable of changed, as she observed students during the modeling lessons, and this led to the shifts in her framing. Furthermore, through her engagement in planning, implementing, and reflecting on modeling lessons with researchers, she came to recognize the value of student collaboration in knowledge-building processes. These results can offer implications for supporting and studying teachers' epistemological framing and modeling-based teaching by partnering with them.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.