• Korean Journal of Comparative Education
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• v.20 no.2
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• pp.95-128
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• 2010

This article presents a one and half-year process of Lesson Study conducted at a K-8 school in an urban district in the eastern U.S. Lesson Study, a Japanese form of professional development that centers on collaborative study of live classroom lessons, has spread rapidly in the U.S. since 1999 and has been argued as a promising alternative model for teacher-led school reform through professional development. The Lesson Study group described here was composed of five teachers, one administrator, and one instructional improvement coordinator belonging to the participant school and two instructional super-intendants from the school district. Data was collected from October 2007 to February 2009 and a qualitative case study method was employed for this study. Drawing a case of Lesson Study, this article intended to show how Lesson Study group members participated in planning, teaching, observing, discussing, and improving lessons collaboratively for student learning by enhancing teacher professional competence so that find directions for future implementation in Korea. This article investigates (1) process of Lesson Study, (2) issues Lesson Study group members mainly dealt with, and (3) changes have taken place in Lesson Study as it is conducted over time. (4) Finally, this article concludes with challenges to adopting Lesson Study successfully in Korea.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.697-702
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• 2023

Recently, with the introduction of drones, a core technology of the 4th industrial revolution, various convergence education using drones is being conducted in school education sites. In particular, drone theory and practice education is being conducted in connection with free semester classes and career exploration. The drone convergence education program has higher learner satisfaction than simple demonstration and practice education, and the learning effect is high due to direct practical experience. However, since practical education is being conducted for a large number of learners, it is impossible to restrict and control the flight of a large number of drones in a limited place. In this paper, we propose a monitoring system that allows the instructor to monitor multiple drones in real time and learners to recognize collisions between drones in advance when multiple drones are operated, focusing on education operated in schools. The communication module used in the experiment was equipped with GPS in Murata LoRa, and the server and client were configured to enable monitoring based on the location data received in real time. The performance of the proposed system was evaluated in an open space, and it was confirmed that the communication signal was good up to a distance of about 120m. In other words, it was confirmed that 25 educational drones can be controlled within a range of 240m and the instructor can monitor them.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.1-21
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• 2023

This study specifically reviewed the performance of the ranking schemes as an efficient feature selection method for text classification. Until now, feature ranking schemes are mostly based on document frequency, and relatively few cases have used the term frequency. Therefore, the performance of single ranking metrics using term frequency and document frequency individually was examined as a feature selection method for text classification, and then the performance of combination ranking schemes using both was reviewed. Specifically, a classification experiment was conducted in an environment using two data sets (Reuters-21578, 20NG) and five classifiers (SVM, NB, ROC, TRA, RNN), and to secure the reliability of the results, 5-Fold cross-validation and t-test were applied. As a result, as a single ranking scheme, the document frequency-based single ranking metric (chi) showed good performance overall. In addition, it was found that there was no significant difference between the highest-performance single ranking and the combination ranking schemes. Therefore, in an environment where sufficient learning documents can be secured in text classification, it is more efficient to use a single ranking metric (chi) based on document frequency as a feature selection method.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.104-108
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• 2023

Because of recent expansion of the electric car market. it is highly growing that should be supplemented its performance and safely issue. The EMI problem due to the interlocking of electrical components that causes various safety problems such as fire in electric vehicles is emerging every time. We strive to achieve optimal charging efficiency by combining various technologies and reduce radioactive noise among the EMI noise of a weirless charging control module, one of the important parts of an electric vehicle was designed and tested. In order to analyze the EMI problems occurring in the wireless charging control module, the optimized wireless charging control module by applying the optimization design technology by learning the accumulated test data for critical factors by utilizing the Python-based script function in the Ansys simulation tool. It showed an EMI noise improvement effect of 25 dBu V/m compared to the charge control module. These results not only contribute to the development of a more stable and reliable weirless charging function in electric vehicles, but also increase the usability and efficiency of electric vehicles. This allows electric vehicles to be more usable and efficient, making them an environmentally friendly alternative.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.221-232
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• 2009

To purpose of the study was to analyze faculty utility of Web-Based course support system in Universities. Data were collected from log file in server computer, 5,023 faculties and 12,733 courses offered at spring semester of 2009 in the Metropolitan area S, K, D universities were analyzed. Specifically, frequency and percentile of faculties and courses using course management system were analyzed. In addition, the frequencies and percentiles of courses using sub-functions of course management system were analyzed and X2 test used to examine the difference of frequencies of faculties and courses using course system at using announcement, providing instructional material, public bulletin board and free board. Results were as follows. The 62.28% of faculties and 50.3% of courses have used Web-Based course support system. The results of Subfunction utility analysis showed the highest use as 80.4%. in providing instructional material. However, the use of announcement functions and online discussion was more or less low. Results imply that most of faculties and course are using course management system as supplementary system of off-line instruction.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.33-39
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• 2022

This study aims to investigate the online class preference depending on students' gender and school level. To achieve this aim, the study conducted a survey on 4,803 elementary, middle, and high school students in 17 regions nationwide. The valid data of 4,524 were then analyzed using the Apriori algorithm to discern the associated patterns of the online class preference corresponding to their gender and school level. As a result, a total of 16 rules, including 7 from elementary school students, 4 from middle school students, and 5 from high school students were derived. To be specific, elementary school male students preferred software-based classes whereas elementary female students preferred maker-based classes. In the case of middle school, both male and female students preferred virtual experience-based classes. On the other hand, high school students had a higher preference for subject-specific lecture-based classes. The study findings can serve as empirical evidence for explaining the needs of online classes perceived by K-12 students. In addition, this study can be used as basic research to present and suggest areas of improvement for diversifying online classes. Future studies can further conduct in-depth analysis on the development of various online class activities and models, the design of online class platforms, and the female students' career motivation in the field of science and technology.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• Journal of Science Education
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• v.46 no.2
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• pp.178-194
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• 2022

This study analyzes the trend of domestic research related to science writing education. The subjects of analysis were 152 research papers related to science writing education in Korea from 2004 to 2021. The analysis criteria were set as the research problem, research subject, research method and research application etc. Result of the analysis shows a steady increase until 2014, but decreased afterwards. In the result of the research problems, it was found that most studies were about finding out the effects of scientific writing activities. The research subjects were mostly elementary, middle, and high school students. Qualitative research occupied a large proportion in the results of the research method analysis, and there were many mixed studies that combined quantitative and qualitative research. As for the research application method, the most applied research in regular classes. As a result of analyzing the effect of application, most of the studies were on science concepts, attitudes towards science, thinking skills, and creative problem-solving skills. Writing education such as experimental and observational writing in science classes has been steadily conducted since before the introduction of the 2007 revised curriculum. In particular, the importance of scientific writing as a text-based education is being emphasized from the 2007 revised curriculum to the 2022 revised curriculum overview. Writing is an important learning strategy in science education for students to generate, share, explain, and expand their ideas. Therefore, examining domestic research trends related to science writing education can provide important basic data for setting the future direction of science writing education.

• Journal of Technology Innovation
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• v.30 no.1
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• pp.57-104
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• 2022

The government has supported the innovation of private firms by intervening the market for various purposes, such as preventing market failure, alleviating information asymmetry, and allocating resources efficiently. Although the government's R&D budget increased rapidly in the 2000s, it is not clear whether the government intervention has made desirable impact on the market. To address this, the current study attempts to explore this issue by doing a systematic literature review on foreign and domestic papers in an integrated way. In total, 168 studies are analyzed using contents analysis approach and various lens, such as policy additionality, policy tools, firm size, unit of analysis, data and method, are adopted for analysis. Overlapping policy target, time lag between government intervention and policy effects, non-linearity of financial supports, interference between different polices, and out-dated R&D tax incentive system are reported as factors hampering the effect of the government intervention. Many policy prescriptions, such as program evaluation indices reflecting behavioral additionality, an introduction of policy mix and evidence-based policy using machine learning, are suggested to improve these hurdles.