• 대한공업교육학회지
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• v.44 no.1
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• pp.162-189
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• 2019

The purpose of this study is to develop and apply a Design Thinking-based Maker education program utilizing Arduino for middle school students. The study progress was made in four stages of preparation, development, implementation and evaluation according to the PDIE model. In this study, experts were verified for validity and pre-applied to students to improve the maker education program developed based on literature review. Then, it was applied to middle school club classes to check the effects through analysis of quantitative and qualitative data. In addition, the development of the program was completed by supplementing the improvements found in the course. The results of this study are as follows. First, the topics of the maker education program that can be used in middle schools were selected in consideration of the analysis of the 2015 revised curriculum, methods to using the Arduino, and social interest. Second, the program developed based on the selected topic consists of 4 classes of maker basic learning and 16 classes of design thinking-based maker activities. Third, the developed maker education program had a significant effect in improving STEAM literacy of middle school students, but did not have any significant effect in the interest in technology and orientation towards an engineering career. Fourth, learners were interested in the activities of designing and freely making by themselves, and they positively evaluated the experience of realizing the physical computing with Arduino. In addition, they practiced the spirit of a maker, such as autonomously collecting data and sharing them with colleagues, etc. while acting as a maker.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1386-1410
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• 2018

Entrepreneurial resilience is one of the core competencies that young entrepreneurs should own. However, compared to its importance, related studies about this topic are rare, especially in Korea. Therefore, this study, for empirical analysis, included resilience to the research model expanding existing research. The purpose of this study is to identify the direct effects of perceived norms of young entrepreneurs, entrepreneurial self-efficacy, and entrepreneurial resilience on entrepreneurial intentions, and to identify the mediated effects between perceived norm, entrepreneurial self-efficacy, and entrepreneurial intention. The data used in this research were collected through questionnaires from 443 potential young entrepreneurs. Our experimental result show that social norm and entrepreneurial self-efficacy were positively related to entrepreneurial resilience. Moreover, personal norm, entrepreneurial self-efficacy, and entrepreneurial resilience were statistically significant on intention of entrepreneurial. As a result of the indirect effect, entrepreneurial resilience mediates the relationship between social norms, entrepreneurial self-efficacy, and entrepreneurial intention. Finally, this research has significant meaning because it shows the importance of entrepreneurial resilience to entrepreneurial intention of young entrepreneurs. However, the limitation of this study relates to the restriction of sample in certain regions and universities.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.101-115
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• 2020

In this paper, big data analysis method was used to find out global trends in autonomous driving and to derive activate spatial information services. The applied big data was used in conjunction with news articles and patent document in order to analysis trend in news article and patents document data in spatial information. In this paper, big data was created and key words were extracted by using LDA (Latent Dirichlet Allocation) based on the topic model in major news on autonomous driving. In addition, Analysis of spatial information and connectivity, global technology trend analysis, and trend analysis and prediction in the spatial information field were conducted by using WordNet applied based on key words of patent information. This paper was proposed a big data analysis method for predicting a trend and future through the analysis of the connection between the autonomous driving field and spatial information. In future, as a global trend of spatial information in autonomous driving, platform alliances, business partnerships, mergers and acquisitions, joint venture establishment, standardization and technology development were derived through big data analysis.

• Journal of The Korean Association For Science Education
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• v.41 no.2
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• pp.155-169
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• 2021

This study aims at exploring the features of science teaching orientation (STO) and its relationships with other PCK (pedagogical content knowledge) components. To do this, based on the definition of STO by Friedrichsen, Driel, & Abell(2011) and PCK model by Magnusson, Krajcik, & Borko(1999), we observed one experienced elementary teacher's science lessons for 21 lesson hours (10 hours of 'Motion of Objects' and 11 hours of 'Light and Lens') and carried out qualitative analyses of the data obtained from lessons observation, teacher interviews, and CoRe (content representation) responses. We analyzed the teacher's three aspects of STO (i.e. beliefs about the goals and purpose of science teaching, beliefs about the nature of science, and beliefs about science teaching and learning) which can converge into an overall STO of 'inquiry'. And these aspects of STO appear to interact differently with four PCK components (i.e. curriculum knowledge, learner knowledge, instructional knowledge, and assessment knowledge) depending on the topic of the lesson. It is hoped that this in-depth understanding of the features of STO and its relationship with other PCK components would provide useful information on how to monitor and improve STO and PCK of elementary teachers.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.668-680
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• 2021

Recently, measures for successful settlement and sustainability of social enterprises have become an important topic. Accordingly, researches related to social enterprises are increasing, but studies measuring sustainability are still insufficient. In this study, in order to seek the sustainability and development of social enterprises in the field of literature and arts, a theoretical model for the sustainability of social enterprises in the field of culture and arts was presented. To this end, interviews were conducted with social enterprises in the field of culture and arts, and the results were analyzed to derive the concept and categorization of sustainability of social enterprises in the field of culture and arts. In addition, the integration between the derived categories is illustrated. For a social enterprise in the field of culture and arts to be sustainable, differentiated culture and arts services are important, and each company must constantly strive for its mission and vision, and a differentiated branding strategy unique to companies is required. This research is expected to lay the foundation for empirical research on social enterprises in the culture and arts sector as data for entrepreneurs and prospective entrepreneurs who run social enterprises in the field of culture and arts.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.175-190
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• 2022

Abusive supervision occurs in a social context in which third-party observers react and interact with the abused victims and supervisors. Despite the importance of third-party observers' behavior in abusive supervision, research on abusive supervision has mainly focused on the dyadic relationship between direct victims and supervisors. Although in recent years research on third parties' reactions to peer abusive supervision has attracted growing attention, there are still insufficient studies examining the topic especially within domestic research in Korea. As such, this study comprehensively reviews empirical studies on third parties' reactions to peer abusive supervision and aims to broaden the scope of research in the field. Firstly, the results of previous studies show that the effects of observed peer abusive supervision are mediated by cognitive and affective processes. Secondly, previous studies are found to investigate the boundary conditions where the effects of observed peer abusive supervision can be amplified or mitigated with regard to various outcomes. Overall, compared to research on direct victims, research on third-party observers of abusive supervision is found to capture a wider spectrum of responses. In order to explain the mechanisms of this phenomena, this study thoroughly examines theoretical assumptions presented in previous studies and categorizes them into five theory types. Finally, this study identifies a couple of central methodological issues, including common method bias and inadequate model specification in the literature and suggests future research directions.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.133-140
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• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.135-155
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• 2022

This study analyzes patent trends by deriving sub-technical fields of Organic Light-Emitting Diodes (OLEDs) industry, and analyzing technology value, originality, and diversity for each sub-technical field. To collect patent data, a set of international patent classification(IPC) codes related to OLED technology was defined, and OLED-related patents applied from 2005 to 2017 were collected using a set of IPC codes. Then, a large number of collected patent documents were classified into 12 major technologies using the Latent Dirichlet Allocation(LDA) topic model and trends for each technology were investigated. Patents related to touch sensor, module, image processing, and circuit driving showed an increasing trend, but virtual reality and user interface recently decreased, and thin film transistor, fingerprint recognition, and optical film showed a continuous trend. To compare the technological value, the number of forward citations, originality, and diversity of patents included in each technology group were investigated. From the results, image processing, user interface(UI) and user experience(UX), module, and adhesive technology with high number of forward citations, originality and diversity showed relatively high technological value. The results provide useful information in the process of establishing a company's technology strategy.

• Journal of Korea Entertainment Industry Association
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• v.13 no.1
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• pp.47-57
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• 2019

The end of the 20th century, along with the popularity of new media technology and the rise of new media art, dance as a visual art, and body language art, has the features of more and more rich and changeful. In today's Internet booming new media environment, many different fields, such as film and theater, computer technology, digital art, etc.) with its commonness and characteristics of all kinds of interaction between the creation, produced a new interdisciplinary research with theoretical model. When cross-border interactions between various areas become a hot topic at the same time, the traditional form of dance performances are also seeking new breakthrough. Canada's famous social psychologist McLuhan believes that modern is retrieving lost over a long period of time "overall" feel, return to a feeling of equilibrium. The audience how to have the characteristics of focus on details of visual art back to the "overall" feel worthy of study. At the same time, the new media in today's digital dance teaching in colleges and universities dancing education remains to be perfect and popular, if continue to use the precept of the traditional teaching way blindly, so it is difficult to get from the development of the current domestic dance overall demand. In this paper, the main body is divided into two parts, the first chapter is the study of image device dance performance art, the second chapter is the research of digital dance teaching application system, thus further perspective of media technology to explore dance art crossover practice under the new media environment and mode of transmission.