This study is based on the political and economic standpoint of each country, Use advanced equipment to prevent new terrorism from causing widespread damage, In order to establish a countermeasures against terrorism in accordance with the reality of Korea, which is effective in responding to terrorist attacks, Korea conducted a SWOT analysis of the terrorist environment and terrorist environment through specialists. First, internal strengths of Korea 's terrorist environment include stable security situation, weakness of religious and ethnic conflicts, strong regulation and control of firearms, and counter terrorism capabilities and know - how accumulated during major international events. Second, the internal weaknesses of the terrorist environment in Korea include the insecurity of the people, the instability caused by the military confrontation with North Korea, the absence of anti-terrorism law system, the difficulty of terrorism control and management by the development of the Internet and IT technology. Third, the external opportunities for Korea 's terrorist environment are as follows: ease of supplementation and learning through cases of foreign terrorism failure, ease of increase of terrorist budget and support with higher terrorism issues, strengthening of counterterrorism through military cooperation with allied nationsRespectively. Fourth, the external threats to the terrorist environment in Korea are the increase of social dissatisfaction due to the continuous influx of defectors and foreign workers, the goal of terrorism from international terrorist organizations through alliance with the United States,Increased frequency of incidents, and increased IS coverage of terrorism around the world. In addition, the SWOT in - depth interviews on the terrorist environment of the expert group were conducted to diagnose and analyze the problems, terrorism awareness and legal system in the Korean terror environment. The results of the study are summarized as follows.First, the basic law on terrorism should be enacted.Second, the establishment of an integrated anti-terrorism organization.Third, securing and nurturing specialized personnel in response to terrorism.
Journal of Korean Home Economics Education Association
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v.19
no.2
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pp.131-152
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2007
The purpose in this study was to develope the concept maps of sub-units included in 'resource management and environment' area of Home Economics(HE) as an advance organizer after analyzing the overlapped and connected contents between HE textbooks and those of other subject matters(Ethics, Social Studies, Sciences, and Physical Education) taught in the middle schools. The results of this study were as follows. First, the unit of 'resource facilitation and environment' of HE is dealt in Ethics. Specifically the overlapped content in this unit between HE and Ethics is the content of the savings of resources, recycling, and environment conservation. The unit of 'work and time of youth' is dealt in Ethics and Science. The overlapped content of this unit is that of the concept of 'work'. While Ethics focuses on the general concept of work, Science focuses on the scientific concept of work. Home Economics doesn't focus on the concept of work but on how to manage the work. In the unit of the 'adolescents and their consumption', there are many overlapped contents among three subject matters, HE, Ethics and Social Studies. Second, the 7 concept maps were developed by following the steps: (1) confirming the learning objectives presented in the 'resource management and environment' area of HE; (2) identifying the overlapped and connected contents between HE and other subject matters(Eethics, Social Studies, Sciences, and Physical Education); (3) organizing the overlapped and connected contents between HE textbooks and those of other subject matters.
In this study, we look at the effect that the achievement goal of specialized high school students has on academic self-efficacy and the difference in academic self-efficacy depending on achievement goal orientation. The purpose of this research is to help students to efficiently increase their academic self-efficacy, develop research and study life guidance measures to improve negative factors, and select professors and learning methods. To achieve the purpose, survey was conducted with achievement goal orientation measurement tools(26 questions) and academic self-efficacy measurement tools(28 questions) for 745 students of 18 specialized technical high school students in 5 districts. The results of this study are as follows. First, preference to task difficulty and self-controlling efficacy have highly positive correlations with mastery goal orientation and confidence and mastery avoidance goal orientation have highly negative correlations each other. Second, achievement goal orientation form of specialized high school students were divided into 5 forms; 'execution avoidance(34.8%)', 'mastery orientation(20.8%)', 'approach(17%)', 'avoidance competition(14.9%)', and'mastery avoidance(12.5%)'. In preference to task difficulty, 'approach'group showed the highest average point and 'mastery avoidance'showed the lowest average point. The average point of 'approach' group was higher than other groups in confidence, but 'mastery orientation' group showed the highest average point. Through the results of this study, academic self-efficacy makes an effect by a certain direction in accordance with achievement goal orientation and it's necessary to access academic problems differently according to student's goal directivity. Therefore, it's necessary to provide educational method by student type based on explanation about academic self-efficacy of achievement goal orientation of specialized high school students and analysis on achievement goal orientation form.
Journal of The Korean Association For Science Education
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v.37
no.4
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pp.763-773
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2017
The purpose of this study is to investigate the impact of Argument-Based Inquiry (ABI) strategy on student's character competency. For this study, 51 grade 11 students (two classes) were selected to the role assignment (ABI-R group) and 46 students (two classes) were assigned to the non-role assignment group (ABI group). In the result, the role assignment group (ABI-R group) showed a statistically higher change in character competency than the group without role assignment (ABI group). Particularly, the ABI-R group has significantly higher grade than ABI group in empathy, responsibility, and respect among the sub-factors of character competency. However, in the case of the cooperation factor of character competency, the ABI group showed statistically significant higher grade than ABI-R group. The results of this study showed that Argument-Based Inquiry (ABI) as teaching and learning strategies in science can contribute to the enhancement of human character competency. In addition, we suggest that students should be actively involved in the class through role assignment, but it is necessary to present the class situation so that they can be actively engaged according to the problem situation rather than being fixed in a given role.
Probiotics and their products, such as yogurt and cheese have been widely consumed in many countries with proven health benefits including anti-microbial activity and anti-diarrheal activity. LHFM (Lactobacillus helveticus - fermented milk) is a processed skim milk powder, fermented by a probiotics, L. helveticus IDCC3801. In the present study, we aimed to investigate the neuroprotective effects and the cognitive improvements of LHFM. LHFM itself did not show any cytotoxicity to the human neuroblastoma cell line, SH-SY5Y; however, it dose-dependently protected against glutamate-induced neuronal cell death. LHFM also attenuated scopolamine-induced memory deficit in Y-maze and Morris-water maze. In the analysis of hippocampus after a behavior test, LHFM significantly increased the acetylcholine level and also inhibited acetylcholine esterase activity. Therefore, the raised acetylcholine release partially contributes to the improvement of learning and memory by a treatment with LHFM. These results suggest that LHFM is an effective material for prevention or improvement of cognitive impairments caused by neuronal cell damage and central cholinergic dysfunction.
Journal of Korean Home Economics Education Association
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v.20
no.1
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pp.137-152
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2008
This study examined the organization and operation of home economics curriculum of specialized middle school in the form of regular school among alternative schools and analyzed the perceptions of teachers and students about home economics class. Interviews were conducted with teachers of 6 specialized schools in order to determine the operations and teachers' perceptions of home economics education. Students' perceptions for home economics class were gathered through surveys with students from the 3 (of the original 6) schools that authorized the questionnaire survey. The final analysis utilized 205 student responses. Survey data were analyzed using the SPSS program. The results of the research were as follows: First, home economics education within specialized middle schools was mostly conducted according to the form of the technology-home economics curriculum, which is the national common basic curriculum. Compared to the 7th national curriculum, the class of technology-home economics curriculum in 4 schools occurred 1 hour less each week. Each school incorporated various specialized curricula related to home economics. Second, as for the operation of home economics education in specialized schools, most home economics classes were conducted by teachers who had majored (or minored) in home economics. Moreover, all but 1 school, which used self-made materials, used the national textbook and dealt with the entire content of the textbook. For teaching-learning methods and instructional media, various means were utilized. For evaluation methods, most schools based grades on paper-and-pencil tests(50-60%) and performance tests(40-50%). Third, among teachers' perceptions of home economics education, the meaning of home economics education was focused on practical help and the pursuit of home happiness; the purpose was to realize the happiness of students and their homes by applying these to actual living, and increase students' ability to see the world. In regards to difficulties in educational operations, most pointed out poor conditions of practice rooms. As for differences from general schools, most teachers mentioned the active communication with students. Fourth, through the home economics class, it was found that students perceived the goal of technology-home economics curricula as lower than average. Among students' perceptions about home economics class, most were negative. Perceptions about goal of technology-home economics curricula and home economics class also showed meaningful differences according to each school. Students of the school, which had more home economics class hours and specialized curricula related to home economics, perceived more positively. Also, students who were more satisfied with school and learned from a teacher who majored in home economics tended to perceive home economics class more positively.
In the era of the fourth industrial revolution, maker education is drawing attention as a method of student-led education. At a time when interest in maker education is also growing in technology education, figuring out what stage of concern(SoC) a middle school technology teacher is critical to effective implementation. This study analyzed SoC in maker education by layer sampling among 400 middle school technology teachers using Concerns-based adoption model. SoC was then obtained by measuring the origin using the SoCQ and then presenting it as a SOCQ profile. Gender, training experience with two lower variables were analyzed using t verification, working cities, teaching experience with more than three lower variables were analyzed using one-way ANOVA. Studies showed that SoC in maker education of middle school technology teachers showed the most similar characteristics to that of non-users. The difference in concern depending on gender was that male teachers were more concerned in maker education than female teachers. The difference in concern depending on the working city was that teachers working in the township were more concerned in the maker education than teachers working in the large city, and the difference in concern depending on the teaching career was higher among teachers with middle experience than those with low and high experience. There was also a higher stage of concern in maker education than in teachers without training experience. Therefore, it is necessary to provide middle school technology teachers with an introduction to the maker education and various information, teaching, learning and evaluation data to enhance overall concern and to support the use and evaluation of the maker education in the classroom by providing various teacher training and consulting on the maker education in the future. Further, through further study, we should conduct study that analyzes both Stage of Concern, Level of Use and Innovation Configuration, to put in the effort for effective settlement of maker education.
The purpose of this study was to analyze recognition characteristics of science gifted students on the earth system based on their thinking style. The subjects were 24 science gifted students at the Science Institute for Gifted Students of a university located in metropolitan city in Korea. The students' thinking styles were firstly examined on the basis of the Sternberg's theory of mental self-government. And then, the students were divided into two groups: Type I group(legislative, judicial, global, liberal) and Type II group(executive, local, conservative) based on Sternberg's theory. Data was collected from three different type of questionnaires(A, B, C types), interview, word association method, drawing analyses, concept map, hidden dimension inventory, and in-depth interviews. The findings of analysis indicated that their thinking styles were characterized by 'Legislative', 'Executive', 'Anarchic', 'Global', 'External', 'Liberal' styles. Their preference were conducting new projects and using creative problem solving processes. The results of students' recognition characteristics on earth system were as follows: First, though the two groups' quantitative value on 'System Understanding' was very similar, there were considerable distinctions in details. Second, 'Understanding the Relationship in the System' was closely connected to thinking styles. Type I group was more advantageous with multiple, dynamic, and recursive approach. Third, in the relation to 'System Generalization' both of the groups had similar simple interpretational ability of the system, but Type I group was better on generalization when 'hidden dimension inventory' factor was added. On the system prediction factor, however, students' ability was weak regardless of the type. Consequently, more specific development strategies on various objects are needed for the development and application of the system learning program. Furthermore, it is expected that this study could be practically and effectively used on various fields related to system recognition.
With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.
Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.
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