• Journal of The Korean Association For Science Education
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• v.35 no.6
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• pp.1063-1074
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• 2015

In this study, we developed an analogy-generating strategy and applied this to a 7th grade science-gifted class. The types of analogies they generated, verbal interactions and analogy-generating patterns, and perceptions of five groups on the analogy-generating strategy were examined. The analyses of the results revealed that there was a higher proportion of the elaborated analogies in terms of quality generated by science-gifted students individually in the analogy-generating strategy than in general analogy-generating activity. After having small group activities, most small groups generated the elaborated analogies. The frequencies and percentages of verbal interactions of each sub-stage were found to be slightly different. Analogy-generating patterns in small groups were categorized into three types; selecting in-depth source, selecting inclusive source, and selecting surficial source. The elaborating patterns of mapping between a target concept and analogies were different among the types. Science-gifted students positively perceived in terms of its values and attitudes toward the analogy-generating strategy, and they responded that the analogy-generating strategy was helpful in generating more elaborated analogies and fostering creative thinking. Therefore the analogy-generating strategy is expected to generate positive impact on the creativity of science-gifted students.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of The Korean Association For Science Education
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• v.32 no.5
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• pp.903-927
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• 2012

The study aimed to analyze middle school students construction of physics inquiry problems for open inquiry from the viewpoint of variable isolation and clarification, and investigate students' difficulties during the processes of variable isolation and clarification to get implications for teaching and learning strategies for small group open inquiry activities which have been included in the 2007 national curriculum. The participants were 4 students who had attended an outreach program for the science gifted run by a university institution located in Seoul area. They performed an open inquiry on egg drop for 13 lessons for 30 hours. Level descriptions for variable isolation and clarification have been developed and applied to analyze students' inquiry problems and variables included by the problems. Students iterated inquiry processed 5 times and the inquiry problem showed progress gradually. Dependent variables have been isolated ahead and the levels of variable isolation and clarification showed higher than the independent variables. Many kinds of independent variables isolated extensively and the independent variables and control variables have been mingled. One of the reasons why students had some difficulties in isolation of independent variables could be the absence of theoretical models. The realities of school lab could restrict the variable isolation and clarification as well as topic selections. Some sensory or extensive variables such as broken eggs and drop height seem to be salient to be focused on as core variables. Lack of background knowledges could be one of the reasons for students' difficulties in variable clarification, such as theoretical definitions and operational definitions. As a result of lacking background knowledges, students could not construct theoretical models even though they could isolate and clarify variables as scientific lexical definitions. Some perceptions of inquiry as trial and error or reckless establishment of causal relations between variables could be accounted as one reason.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.1-9
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• 2015

Internet ethics is one of liberal arts courses in a college. We also have taught this subject for a number of years. In order to effectively communicate to students the internet ethics course, we gave some demonstration practice lectures by taking advantage of internet ethics related videos. Since the latest video presentation and its discussion were performed, it was helpful for students to recognize the internet ethical issues and concerns. However, simply video watching is short in the view of students' learning outcome improvement, since each student just watches the content passively in a class. Thus, we assign small student group consisting of 3 people make a video on internet ethics topic. This team project based class methodology is effective to each student who actively participates in the class and understands the concept which they directly make a video. We confirmed that classroom students' understanding for internet ethics has been increased by a survey of the class attendees.

• Journal of the Korean School Mathematics Society
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• v.12 no.4
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• pp.389-409
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• 2009

This article was to investigate the previous research as a research synthesis in the area of Mathematics Education for students with diversity including multi-cultural education, language minority, and social economic status. The following summaries were made: Recognizing equity in students with diversity; Restoring teachers' perspectives toward poststandardization; Introducing creative curricular based on students' characteristics; Application of the direct instruction; Foci on interests, challenges and mastery learning; Application of Anchored Instruction; Application of CRA; Tasks, tools, & classroom norms; Enhancement of connection and communication using small-group activity; Development of programs enriched by bilingual education; and Producing curriculum for students from North Korea.

• KDI Journal of Economic Policy
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• v.35 no.4
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• pp.1-29
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• 2013

This paper examines the effect of trade liberalization or globalization, more broadly, on plants' growth as well as on "bi-polarization". To do so, we reviewed the possible theoretical mechanisms put forward by recent heterogeneous firm trade theories, and provided available micro-evidence from existing empirical studies on Korean manufacturing sector. Above all, the empirical evidence provided in this paper strongly suggests that globalization promoted growth of Korean manufacturing plants. Specifically, evidence suggests that exporting not only increases within-plant productivity but also promotes introduction of new products and dropping of old products. However, the empirical evidence also suggest that globalization has some downsides: widening productivity differences across plants and rising wage inequality between skilled and unskilled workers. Specifically, trade liberalization widens the initial productivity differences among plants through learning from export market participation as well as through interactions between exporting and R&D, both of which increase plants' productivity. We also show that there is only a small group of large and productive "superstar" plants engaged in both R&D and exporting activity, which can fully utilize the potential benefits from globalization. Finally, we also show evidence that trade liberalization interacts with innovation to increase the skilled-unskilled wage inequality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.137-143
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• 2009

Through the development of techniques, robots are becomes smaller, and many of robots needed for application are greater and greater. Method of coordinating large number of autonomous robots through local interactions has becoming an important research issue in robot community. Swarm Robot System is a system that independent autonomous robots in the restricted environment infer their status from preassigned conditions and operate their jobs through the coorperation with each other. Within the SRS,a robot contains sensor part to percept the situation around them, communication part to exchange information, and actuator part to do a work. Specially, in order to cooperate with other robots, communicating with other robot is one of the essential elements. In such as Bluetooth has many adventages such as low power consumption, small size module package, and various standard procotols, it is rated as one of the efficent communcating system for autonomous robot is developed in this paper. and How to construct and what kind of procedure to develop the communicatry system for group behavior of the SRS under intelligent space is discussed in this paper.

• Journal of the Korean earth science society
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• v.25 no.3
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• pp.194-204
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• 2004

The purpose of this literature review is to investigate what kinds of research have been done about scientific inquiry in terms of scientific argumentation in the classroom context from the upper elementary to the high school levels. First, science educators argued that there had not been differentiation between authentic scientific inquiry by scientists and school scientific inquiry by students in the classroom. This uncertainty of goals or definition of scientific inquiry has led to the problem or limitation of implementing scientific inquiry in the classroom. It was also pointed out that students' learning science as inquiry has been done without opportunities of argumentation to understand how scientific knowledge is constructed. Second, what is scientific argumentation, then? Researchers stated that scientific inquiry in the classroom cannot be guaranteed only through hands-on experimentation. Students can understand how scientific knowledge is constructed through their reasoning skills using opportunities of argumentation based on their procedural skills using opportunities of experimentation. Third, many researchers emphasized the social practices of small or whole group work for enhancing students' scientific reasoning skills through argumentations. Different role of leadership in groups and existence of teachers' roles are found to have potential in enhancing students' scientific reasoning skills to understand science as inquiry. Fourth, what is scientific reasoning? Scientific reasoning is defined as an ability to differentiate evidence or data from theory and coordinate them to construct their scientific knowledge based on their collection of data (Kuhn, 1989, 1992; Dunbar & Klahr, 1988, 1989; Reif & Larkin, 1991). Those researchers found that students skills in scientific reasoning are different from scientists. Fifth, for the purpose of enhancing students' scientific reasoning skills to understand how scientific knowledge is constructed, other researchers suggested that teachers' roles in scaffolding could help students develop those skills. Based on this literature review, it is important to find what kinds of generalizable teaching strategies teachers use for students scientific reasoning skills through scientific argumentation and investigate teachers' knowledge of scientific argumentation in the context of scientific inquiry. The relationship between teachers' knowledge and their teaching strategies and between teachers teaching strategies and students scientific reasoning skills can be found out if there is any.

• New Physics: Sae Mulli
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• v.68 no.12
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• pp.1356-1363
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• 2018

The purpose of this study was to investigate science high-school students' creativity and scientific attitude when an integrated science, technology, engineering and mathematics (STEM) project themed 'lighting of quantum dot solution' was applied to them. The subjects were a one team composed of 3 students in the 11th grade desiring to participate in the Korea Science Exhibition. They began with a scientific inquiry related to the physical properties of the QD solution and then gradually showed the process of expansion of their ideas into the integration of engineering, technology, and mathematics. Also, during the process, they showed problem solving ability and scientific attitudes, such as cooperation, endurance, and satisfaction of accomplishment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.181-187
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• 2021

Recently, various air pollution factors have been measured and analyzed to reduce damages caused by it. In this process, many missing values occur due to various causes. To compensate for this, basically a vast amount of training data is required. This paper proposes a statistical techniques that effectively compensates for missing values generated in the process of measuring ozone, carbon dioxide, and ultra-fine dust using a small amount of learning data. The proposed algorithm first extracts a group of meteorological data that is expected to have positive effects on the correction of missing values through statistical information analysis such as the correlation between meteorological data and air pollution level factors, p-value, etc. It is a technique that efficiently and effectively compensates for missing values by analyzing them. In order to confirm the performance of the proposed algorithm, we analyze its characteristics through various experiments and compare the performance of the well-known representative algorithms with ours.