• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.209-210
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• 2013

본 연구의 목적은 공학에 대한 흥미, 태도, 성취가 낮은 여학생에게 공학 경험을 제공함으로써 공학 분야의 여성 인재를 양성할 수 있는 계기를 마련하기 위한 공학 중심 STEAM 프로그램의 틀을 설계하는 데 있다. 이를 위하여 여학생의 특성을 분석하고 여학생 친화적인 환경을 구축하였으며 여학생 친화적 환경에 부합하는 e-textile이라는 도구를 활용하여 STEAM 교육 프로그램을 설계하였다. 교육 프로그램은 학습자가 직접 참여할 수 있도록 Learning by Doing, Learning by Design의 전략을 사용하도록 하였으며 교육 프로그램 전 과정을 학습자 스스로 창의적인 사고를 바탕으로 문제를 해결해나가도록 하고 교사는 조력자, 안내자 역할을 할 수 있도록 하였다.

• Architectural research
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• v.15 no.3
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• pp.123-132
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• 2013

Design studio is a unique type of course in architecture and interior design education, in which learning is based on student-instructor interaction and learning by doing; yet little research has been conducted on student perceptions of the ideal design studio instructor. The purpose of this paper was to identify characteristics of the ideal studio instructor from student perspectives. Three award-winning design studio instructors' studio activities were observed, and the three instructors and their 40 students were interviewed. As a result, characteristics in four categories were identified. The author argues that providing customized feedback and allowing student autonomy are the two distinct characteristics that students value in design studio as compared to students in other fields or type of courses. The findings provide valuable insights to design educators who would like to strengthen their teaching studios by listening to student voices.

• The Journal of Fisheries Business Administration
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• v.35 no.2
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• pp.53-69
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• 2004

While the life in the fishing villages in old days was characterized by accepting the sea as destiny by birth, it became an industrial one nowadays with industry - scale fisheries as the mainstream. It is expected, however, that nature - friendly life will be prevailing in the fishing villages in the future In these days, the status of fishing village is on a very terrible situation due to the decrease in population, low income, environment destruction, and so on. However, the fishing village should be revitalized because of its public benefits at least. Recently, a kind of affirmative appearance in fishing village is that people who are willing to visit fishing village are increasing. The fishermen are supposed to use this opportunity for its economic and social interests. This paper suggests a kind of way, enjoyable fishery after catching and farming fishery, to use it. Enjoyable fishery consists of watching (learning by observation) fishery and doing (experience) fishery. The example of watching fishery is inspecting the fixed net fishery, doing fishery is experience of small dragnet fishery. The activation devices of the enjoyable fishery are suggested as follows; 1) fixing the identification of regional tourism 2) the development of regional enjoyable 3) opening of one day's fisherman school. 4) networking with fishing village amenity improvement 5) driving sisterhood system with urban area.

• Korean Journal of Childcare and Education
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• v.15 no.6
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• pp.139-167
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• 2019

Objective: This study aims to investigate the effects of a learning cycle model-based early childhood education program using physical motion on young children's scientific inquiry ability, scientific attitude, object manipulation ability and spatial ability. Methods: The subjects of this study were 60 five-year-old children who were attending K-G City Childcare Center. The SPSS Window 21.0 program and content analysis method were used, and post-validation Tukey was conducted to examine the differences between the one-way ANOVA and the group. Results: Activities using body movement were practiced systematically based on the circle learning. Children could revise their pre-concept and concept of error by interacting with other children, teachers and the environment. Furthermore, children were attaining new knowledge while they were doing body movement activities, assessing and applying them to actual activities. Conclusion/Implications: This study is investigated a cyclic learning-based early childhood science education program using physical motion, which has significance in systematic and practical early childhood centered education for young children.

• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.20-27
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• 2023

Background: As the number of nuclear facilities nearing their pre-determined design life increases, demand is increasing for technology and infrastructure related to the decommissioning and decontamination (D&D) process. It is necessary to consider the nature of the dismantling environment constantly changing and the worker doing new tasks. A method was studied that can calculate the effect of learning and the change in work time on the work process, according to the learning-forgetting curve model (LFCM). Materials and Methods: The LFCM was analyzed, and input values and scenarios were analyzed for substitution into the D&D process of a nuclear facility. Results and Discussion: The effectiveness and efficiency of the training were analyzed. It was calculated that skilled workers can receive a 16.9% less collective radiation dose than workers with only basic training. Conclusion: Using these research methods and models, it was possible to calculate the change in the efficiency of workers performing new tasks in the D&D process and the corresponding reduction in the work time and collective dose.

• Knowledge Management Research
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• v.20 no.3
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• pp.155-171
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• 2019

In the entertainment industry which has great uncertainty, it is essential to predict public preference first. Thanks to various mass media channels such as cable TV and internet-based streaming services, the reality audition program has been getting big attention every day and it is being used as a new window to new entertainers' debut. This phenomenon means that it is changing from a closed selection process to an open selection process, which delegates selection rights to the public. This is characterized by the popularity of the public being reflected in the selection process. Therefore, this study aims to implement a machine learning model which predicts the winner of , which has recently been popular in South Korea. By doing so, this study is to extend the research method in the cultural industry and to suggest practical implications. We collected the data of winners from the 1st, 2nd, and 3rd seasons of the Produce 101 and implemented the predictive model through the machine learning method with the accumulated data. We tried to develop the best predictive model that can predict winners of by using four machine learning methods such as Random Forest, Decision Tree, Support Vector Machine (SVM), and Neural Network. This study found that the audience voting and the amount of internet news articles on each participant were the main variables for predicting the winner and extended the discussion by analyzing the precision of prediction.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.149-158
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• 2015

The purpose of this paper is to investigate the determinants of new product diffusion. We seek to document and explain systematic features of product diffusion. In this essay, we examine the well-documented empirical regularity that the speed of diffusion has accelerated during the twentieth century. The empirical results show that the main source of acceleration are faster declines in prices. Faster price declines make the product affordable to more consumers within a given period of time. Based on theories of intertemporal price discrimination and learning-by-doing, the association between the speed of adoption and the speed of price decline was explained. Faster price declines are attributed to several product characteristics as well as changes in income distribution. Above all, the introduction of consumer electronic products in more recent years can be regarded as the most important factor in accelerating price declines. Consumer electronic products are technologically different from non-electronic goods, in that semiconductors are important components. As the price of semiconductors has dropped rapidly, the falling production costs can be rapidly incorporated to the price of consumer electronic goods. Furthermore, most of the recently introduced consumer electronic products have network externalities, and many products with network externalities require complementary products. A complementary product becomes more readily or cheaply available as more people have the main product. One major difference between previous studies and this study is that the former focuses only on the factors that operate directly on the speed of adoption, while this study incorporated factors that work through price changes as well as the factors that work directly on the speed of adoption.

• Journal of Computing Science and Engineering
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• v.10 no.4
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• pp.103-110
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• 2016

Emotion recognition is an important component of affective computing, and is significant in the implementation of natural and friendly human-computer interaction. An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem. However, in emotion recognition, the texts involved are usually very short, leaving a very large, sparse feature space, which decreases the performance of emotion classification. This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster features, offering a novel word clustering algorithm, and using a new feature weighting scheme. Emotion classification experiments were performed with different features and weighting schemes on a publicly available dataset. The experimental results suggest that the word cluster features and the proposed weighting scheme can partly resolve problems with feature sparseness and emotion recognition performance.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2016-2019
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• 2003

In this paper, we take some features for face recognition out of face image, using a simple type of templates. We use the extracted features to do Adaboost learning for face recognition. Using a carefully-chosen feature among these features, we can make a weak face classifier for face recognition. And doing Adaboost learning on and on with those chosen several weak classifiers, we can get a strong face classifier. By using Adaboost Loaming, we can choose particular features which is not easily subject to changes in illumination and facial expression about several images of one person, and construct face recognition system. Therefore, the face classifier bulit like the above way has robustness in both facial expression and illumination variation, and it finally gives capability of recognizing face fast due to the simple feature.

• Korean Journal of Child Studies
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• v.16 no.2
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• pp.65-80
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• 1995

This study explored principles of child education in such traditional Korean child education books as "So Hak", "Dong Mong Sun Seup", "Kyuk Mong Yo Kyul", and "Sa So Goel". Principles of child education presented in those traditional Korean child education books can be identified as (1) modeling and identification, (2) integration of knowledge and behavior, (3) spontaneity of learning, (4) learning by doing, (5) early education with consideration of critical periods, and (6) individualization. From those findings, we can conclude that traditional Korean child education (1) emphasizes learner characteristics and principles of child development, (2) gives good guidance to significant adults around children, and (3) suggests implications to modern child education practices which are mainly concerned with knowledge and function.