• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.263-273
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• 2017

Although this research puts the emphasis on the importance of the personality education, and lacks the understanding of the early childhood educator about the personality education, and essentially the content analysis of the direction of the operation of the personality education hasn't been performed. Therefore through the research study once again we collected the opinion of the early childhood educator about the personality education. As the object of the investigation, we questioned 208 teachers who work in the Daycare Center in the S city, and applied the SPSS 18.0 program. The result is as the following. First, there was a lot of concern in the understanding of the early childhood educator about the personality education, and that it was in need. The reason for emphasizing the personality education appears to be the "Individual Egoism", and the "Parental Value" as the factor of influence, and "Whole People Human Development and Health Promotion" as a factor of helping, and "Courage" as the inner information of the information of the personality education, and "Manner" as the outer information. Secondly, more than the majority was carrying out the personality education in the real state of the early childhood educator on the personality education and it happens to be that the instructional material is the "Material related to the personality education", "Conversation" as the teaching learning method, "Once per week" as number of times, "Within 30 minutes" as lead time, "Teacher in Charge" as the host, and "Uncooperative parents" as the difficulty. Lastly the accurate time of demanding the early childhood educator about the personality education happens to be from "Infancy", and the teaching method is "Teaching by making a connection with the family", and that "Leading by example of the teacher" is the factor of consideration.

• Journal of The Korean Association For Science Education
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• v.34 no.1
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• pp.10-20
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• 2014

This study compares the perceptions of elementary gifted child and science teacher in a science class for the gifted. In order to explore the research problem, students and teachers answered a written semi-structured questionnaire and participated in interviews regarding the gifted science class. The data was collected and analyzed. Science teachers recognized the characteristics of a good science class, especially in terms of educational content and teaching methodology. First, they suggested promoting inquiry skills, presenting a challenging task in atypical topic selection, student-centered curriculum, and controlling the pace of learning to recognize individual differences. Second, in terms of the science class skills and attitudes category, teachers recommended raising mutual satisfaction through vigorous interaction within a permissible atmosphere. Finally, science teachers need to strive for continued professional growth. Gifted children, meanwhile, want to investigate a wide range of topics without time constraints. Additionally, they may have to explore challenging topics further. They prefer to act like scientists in that they enjoy group activities, communication and cooperation. In particular, they want to be evaluated by others in a totally embedded assessment. Gifted children also expect teachers to understand the life circumstances and needs of the students. In addition, they asked for teachers to respect individual experiments and to show them how to safely use new equipment or research methods. As a result, gifted children and science teachers have to recognize the differences of opinion concerning a good science class for the gifted. This study can help formulate strategies to establish quality management of materials in gifted science classes.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.1-14
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• 2014

Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors' interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor's emotional state from responses to exhibited stimulus. Studies undertaken so far have attempted to estimate the human emotional state, most of them doing so by gauging either facial expressions or audio responses. However, the most recent research suggests that, a multimodal approach that uses people's multiple responses simultaneously may lead to better estimation. Given this context, we propose a new multimodal emotional state estimation model that uses various responses including facial expressions, gestures, and movements measured by the Microsoft Kinect Sensor. In order to effectively handle a large amount of sensory data, we propose to use stratified sampling-based MRA (multiple regression analysis) as our estimation method. To validate the usefulness of the proposed model, we collected 602,599 responses and emotional state data with 274 variables from 15 people. When we applied our model to the data set, we found that our model estimated the levels of valence and arousal in the 10~15% error range. Since our proposed model is simple and stable, we expect that it will be applied not only in intelligent exhibition services, but also in other areas such as e-learning and personalized advertising.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.197-202
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• 2019

In the era of the fourth revolution, interest in content production using proven engines in the broadcasting sector, such as Vizrt, is growing. The new visual effects required in the 5G era are critical to content production training. Vizrt has a good production time utility and affordability for broadcast and media content. In this paper, we are going to use this to present a practical case of the theorem and application of the basic training course in the production of virtual content, and to present the basic training direction. In the introduction, the graphic algorithm analyzed and studied the characteristics and environmental factors of the Vizrt engine. In this paper, the production process was studied separately, and the work carried out through engine implementation was presented. The VS Studio Foundation was provided as a practical production case at each stage. The Vizrt engine operator process is important in graphic approach and application, and through the results of the lecture, the method of understanding and implementing algorithms for virtual reality perspective suitable for basic learning was studied. Based on practice, the research method of main theory was to create Vizrt contents specialized in 5G contents work in each sector and to implement graphic production in new areas from contents image. Through this study, we came to the conclusion of the basic training method through virtual reality content work based on Vizrt by practicing content creation according to the subject. It also proposes the effect of creating Vizrt content and the direction of building Vizrt basic training courses.

• Journal of Technologic Dentistry
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• v.17 no.1
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• pp.41-57
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• 1995

This study was conducted to collect and analyze previous information in order to manage efficience, improve experience effect and promote employment rate. The questionnaire interview with 27 chief of dental Laboratory refered clinical experience in technology department about clinical experience in 14 Jumior colleges were also investigated. The results were summarried as follows : The portion of age of 35-39 among chief of dental Laboratory was 40.7% which was the highest, that of male was 96.3%, that of junior college graduate was 97.5%, that of 10years experience was 92.6% and that of ceramic technician was 85.2%, 63.0% dental laboratory for clinical experience was a bore space of 30pyong. Aspect of dental laboratory management, manufacturing all part of prosthetic restoration was 29.6%, othodontic appliance and ceramic restoration was 7.4%, 3.8%, each. The percentage of 40.7 was having connection with 30-3a dental clinics and referring case per day was 10-19 cases(40.7%), manufacturing time of referred prosthetic restoration was 3-4 days(77.8%), places preparing seminar room for education was 29.6%, above a place of 40pyong was 11.1% 30-34 pyong and 35-39 pyong was 7.4% each. During training of 2 years education course student, 18.5% was rack of thorough occupational career. While 44.4% will want the more salary among 3years education course student, 74.1% will expect the more dental techmicians would engaged in their field, 51.9% will hope improve of their theory and practice, 29.6% be expected better skill and 14.8% be expected better theory. Attitude of clinical experience places was distributed by 59.3% of offering only experience chance, 25.9% of wasting time and 29.0% of annoying. The big emphasis of climical experience was thorough occupational career(44.4%). The clinical experience places of our college were selected after direct visiting, so their condition of management was not that bad but most of dental laboratory were poor in management state and working environment. Therefore it is difficult to choose appropriate places and dental Laboratory are also limited manpower and time as suppliers. So that it recommended to induce flexible management of experience period by interval and rotation of experience places among college and to applicate intern-system for employment ant industry-college cooperation aspect.

• Journal of The Korean Association For Science Education
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• v.41 no.6
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• pp.471-481
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• 2021

The importance of science education for cultivating the competencies required by an intelligent information society is gradually being strengthened. The government's roles and responsibilities for science education are stipulated by laws and policies in Korea. In order to systematically support science education, continuous monitoring of related policies is essential. This study aims to develop indicators that can be used to systematically and continuously monitor the national policies on science education in Korea. To achieve this goal, we first derive the framework for the indicators that has two dimensions (learner and science education context) and three categories (input, process, and outcome) from literature reviews. In order to derive the components and subcomponents of the indicators, the contents of science education-related indicators developed in Korea or abroad were reviewed. In order to verify the suitability and validity of the framework and components of the initial indicators, a two-round Delphi method was conducted with 25 expert participants with five different professions in science education. Finally, three components of the 'input' category (student characteristics, teacher characteristics, and educational infrastructure), three components of the 'process' category (science curriculum implementation, science educational contents and programs implementation, and teacher professional development program implementation), and five components of the 'outcome' category (science competency, participation and action, affective achievement, cognitive achievement, and satisfaction) were derived. An instrument to collect data from students, teachers, and institutions was developed based on the components and subcomponents, and content validity and internal consistency of the instrument were analyzed. Korea's Science Education Indicators developed in this study can comprehensively measure the current status of science education and is expected to contribute to a more efficient and effective science education policy planning and implementation.

• Korean Journal of Child Education & Care
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• v.18 no.4
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• pp.247-265
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• 2018

Objective: The purpose of this study was to investigate the effect of teacher support program for integration of handicapped children on teaching efficacy of daycare center teachers. Methods: In the study, 12 day care teachers in 4 day care centers in Seoul and Gyeonggi area were selected as experimental groups and 12 teachers in 5 day care centers were selected as control group. Teacher education is carried out through group education, such as understanding of developmental area, curriculum modification, activity-based embedded intervention, cooperative learning, direct teaching, disability understanding education, behavior support, family support. Individual teacher education provided counseling on the reality of child care for children with disabilities that reflects the needs of teachers for integrated child care for handicapped children. Teacher's Efficacy in Inclusive Practices (TEIP) was used as a pre post test to measure teacher's efficacy change. In order to analyze the results of the study, two independent sample t tests were conducted on the difference between pre-post test of teacher efficacy between the two groups. Results: As a result, There was a significant difference in the pre-post change of teacher efficacy between the two groups. Conclusion/Implications: The results of this study are as follows, teacher support program provided immediate feedback in integrated child daycare center for the handicapped children, child care teachers improved their integrated handicapped children care expertise, provided responsive teacher support program to the actual needs of the site, teacher support program reflected various variables related to integration, and emphasized the cooperative relationship between researcher and child daycare center teacher. The results of this study can be used as actual data of field where lack of support for the integration of handicapped children is lacking.

• Journal of Nutrition and Health
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• v.44 no.2
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• pp.140-151
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• 2011

Middle-school students (158 boys and 199 girls) and their mothers were asked about nutritional attitudes, nutritional knowledge, dietary habits, and food intake using a questionnaire to examine whether nutritional knowledge and dietary behaviors of mothers affected their children's dietary habits. Nutritional attitude scores (total, 15 points) and nutritional knowledge scores (total, 20 points) of girls were 11.24 and 16.13 points, respectively, which were significantly higher than 10.47 and 15.43 points for boys. Generally, mothers received higher points than their children for all scores surveyed, but the results were not significantly different between boys' mothers and girls' mothers. The mean nutrient adequacy ratio (MAR) was calculated from dietary nutrient intakes to assess overall quality of meals. The results showed that girls had a higher MAR than that of boys (0.89 vs. 0.86, p < 0.01). Relationships among variables were examined by Pearson's correlation coefficient within children and between children and their mothers. Significant positive correlations were observed between nutritional attitudes and knowledge in both boys and girls. In girls, positive correlations between nutritional attitudes and dietary habits, nutritional knowledge and dietary habits, and dietary habits and MAR were also sig-nificant. In boys, only dietary habits and MAR were correlated with those of their mothers. Nutritional attitudes, dietary habits, and the MAR of girls' mothers were significantly correlated with nutritional attitude, dietary habits and the MAR of girls. The results indicate that the influence of mothers on dietary behaviors of children was greater in girls than that in boys, suggesting that a gender-specific nutrition education program is needed for middle school students.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.