• Journal of radiological science and technology
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• v.38 no.3
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• pp.295-304
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• 2015

This study intended to examine the correlation of career self-regulation (plan and check-up, positive thinking, career feedback, environment formation for career) and career identity (career decision, indecisiveness, career indecision) caused by parental career support (informative, emotional, financial, and empirical) among freshmen, sophomores, and juniors in the radiotechnology department. For assessment, a survey was conducted and according to the results, there existed correlation as follows. Regarding parental career support, emotional support is plan and check-up (r=.25, p<.001), Career feedback (r=.54, p<.001), and positive thinking (r=.46, p<.001) showed high positive correlation while informative support showed correlation in all factors showing high correlation with environment formation for career (r=.22, p<.001), plan and check-up (r=.20, p<.001), career feedback (r=.24, p<.001), and positive thinking (r=.26, p<.001). Financial support career feedback (r=.33, p<.001) and positive thinking (r=.34, p<.001) showed somewhat higher correlation. All factors of environment formation for career (r=.18, p<.001), plan and check-up (r=.25, p<.001), career feedback (r=.37, p<.001), and positive thinking (r=.30, p<.001) showed high correlation. Informative support showed high correlation only with career decision (r=.27, p<.001) and financial support also showed high correlation only with career decision (r=.18, p<.001). Also, empirical support was somewhat highly correlated only with career decision (r=.23, p<.001). Regarding school-year difference depending on parental career support, there was significant difference between emotional support (F=8.52, p<.001), financial support (F=8.97, p<.001), and empirical support (F=5.36, p<.05) while informative support was dismissed. Regarding school-year difference depending on career self-regulation, there was significant difference between career feedback (F=8.48, p<.001) and positive thinking (F=16.29, p<.001) while environment formation for career and plan and check-up were dismissed. Regarding school-year difference depending on career identity, there was significant difference between career indecision (F=4.01, p<.05) and career decision (F=11.72, p<.001) while indecisiveness was dismissed. According to the analysis results, parents' active support to their child like respecting and listening to their opinion on career, provision of career related experience or information, and provision of necessary financial aid for their study or academic preparation made the students plan and exploring their career, examine accomplishment progress, have positive idea to realize their objectives. In addition, the students were able to establish the objective of their career by forming the environment that helped them realize their objectives by seeking advices and encouragement from surroundings. Meanwhile, the parents' attitude to respect and listen to their child's career related opinion affected their career decision and indecision. Although informative support helped the students' career decision, financial and empirical support caused effect only to career decision.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Journal of The Korean Association For Science Education
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• v.31 no.8
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• pp.1092-1109
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• 2011

The purpose of this study was to analyze of the effects of instructional supervision emphasizing reflective thinking on science teaching of elementary teachers. The participants in this study were two teachers. This study was divided in former, middle, and later periods, and consisted of monitoring their own teaching, interviewing, journal writing, discussion with peer teachers and teacher training. Data included descriptions of nine science classes, nine interviews, seven journals and the journals of the researcher. Data analysis tools were the frameworks of the questions, feedback, teaching methods, elements of teaching behavior, and reflection levels. This study employed qualitative research, analysis of the frequency of data, and quoting of descriptions related to the result. The results of this study were as follows: First, teachers showed mainly technical reflection, but changed to show more practical reflection, and critical reflection in the later period of instructional supervision. Second, instructional supervision emphasizing reflective thinking on science teaching for elementary teachers meaningfully changed the question, feedback, teaching methods and teaching elements of teachers. From the results of this study, instructional supervision emphasizing reflective thinking on science teaching for elementary teachers can be considered an effective method in improving teaching elementary science, and instructional supervision used in this study made possible the higher level of reflection and appropriate teaching behavior.

• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.177-189
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• 2020

In this study, we implemented an education program to improve the responsive teaching ability of pre-service science teachers, and analyzed the responsive teaching practices revealed during the program process. Through this, we derived the types and characteristics of responsive teaching practice, identified factors that made it difficult for pre-service teachers to practice, and obtained empirical data on under what conditions the responsive teaching capacity of pre-service teachers was developed. For this purpose, a practice-based teacher education program was designed and carried out for 14 pre-service teachers who had no experience in responsive teaching. The program consists of four steps; observation of class, practice through rehearsal, application in practicum, and post-reflection on educational practice. In particular, qualitative analysis was conducted on the types of responsive teaching and their detrimental factors revealed during application in practicum. As a result of the analysis, four types were derived; discriminator type, communicator type, guide type, and facilitator type. Each type was identified as having a common responsive teaching step element. The education program implemented in this study was effective for pre-service teachers to recognize the importance of student-participation class and the educational effect of responsive teaching. However, three barriers that prevented pre-service teachers from responsive teaching practice were also analyzed. First was the pressure to achieve specific learning goals within a given class time. Second was the rigid belief of the fixed curriculum. Third was the obsession that the teacher should lead the class. Based on these results, it was suggested that in order to improve the responsive teaching ability of pre-service teachers, it is necessary to support the recognition of breaking out of the thinking the time constraint, the flexibility of the curriculum, and the role of teacher as a class supporter.

• 대한공업교육학회지
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• v.43 no.1
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• pp.134-157
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• 2018

This study surveyed and analyzed satisfaction and issues about an intellectual property education system, and educational needs for intellectual property NCS (intellectual property management, intellectual property information survey analysis, intellectual property assessment trade), in order to introduce and operate NCS-based education system that trains practical manpower in the field. The results of this study are as follows. First, satisfaction for intellectual property education system showed education contents (M=3.86), followed by lecture (M=3.79), teaching method and environment (M=3.66) and education assessment (M=3.50). The issues to be improved are low application in the current occupation due to no reflection of demands of industrial fields, as well as insufficient education contents system, lectures who fall short of education capability and interactions with students tend to stress theoretical knowledge more than practical ability, teaching method lacks application of educational medium, insufficient interest and motivation, assessment methods that fall short of theoretical knowledge and practical ability achievement, and that is theory-centered. Second, educational needs for intellectual property NCS showed intellectual property assessment trade (4.33), followed by intellectual property management (3.68), and intellectual property information survey analysis (2.99), which should be reviewed to reform or newly develop NCS-based education course. Conclusively, intellectual property education showed satisfaction above the average, but a job-centered education is demanded to elevate application in the industrial field, which puts emphasis more on practical ability than theory. For this, it is necessary to introduce intellectual property NCS reflecting demands of industrial field, and to reform or newly develop into NCS-based education course. In addition, intellectual property education needs to be operated by changed education paradigm, such as user-centered teaching method, not provided-centered, and performance and course-centered assessment method, not theoretical knowledge-centered.