• Journal of Gifted/Talented Education
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• v.20 no.2
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• pp.571-594
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• 2010

Learning styles affect how students access and handle their task, so it is very important to understand how they study, when planning teaching-learning process, to enhance their potential to the maximum. In addition, in order to improve the quality of gifted education, there is a need to examine the curriculum and teaching-learning process which reflect learner characteristics. In this study, gifted student's preferred learning styles are investigated using questionnaires and learning style inventory. Also by analyzing the characteristics of the learners, it is hoped to get parents and teachers to understand the gifted who have various talents, and to support teaching programs for the gifted in order to develop their potential. This study shows that there are differences in the studying style between the gifted child and the average child. Namely, learner's physical and psychological environment can affect learning styles. Also there is a difference between the studying style which the gifted students prefer and the teaching style which teachers use most frequently. Programs for the gifted should be planned through better understanding of the characteristics of the learners.

• The Journal of Korean Philosophical History
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• no.56
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• pp.209-238
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• 2018

The purpose of this research is to analyze characteristics of the method of education or learning reflected in the teacher-student relationship in On Haeng Lok By Toe-gye and explore their relevance to modern education. By writing various works and conversing with his students, Toe-gye devoted himself in the education of the traditional Confucian principles. Specially, he taught his students based on two Confucian educative principles, namely Shim Deuk(心得) and Goong Haeng(躬行). Judging from this, Toe-gye can be seen as someone who tries to fulfill the role of teacher as dictated in the educative principles of the Confucianism. In Confucianism, teacher is responsible for forming a well-rounded view on life in student, rather than simply transmitting knowledge. As such, the teacher was supposed to find a harmonious way to create something new based on what was inherited from the past generation and try to do his best in learning new things himself and teaching his students. These Toe-gye managed to do successfully, earning his students' trust and respect. Being moved and inspired by their teacher, the students continued their intellectual pursuit. This relationship between Toe-gye and his students can be analyzed from the perspective of education method and discussed in terms of cognitive learning and adult learning. In terms of cognitive learning, the education method reflected in the relationship is similar to potential learning, insight learning, and imitation learning. In terms of adult learning, it is similar to self-directed learning and communicative learning.!

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1673-1681
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• 2007

The u-Learning just begins to emerge as the next-generation knowledge-based business. Since it has a great potential to become a high value-added industry, there is much attention paid in this field. In this work, we first summarized the concept of the u-Learning where the architecture of various u-learning areas has been identified. Then we investigated the current status and problems of the u-Learning industry. Through the SWOT analysis, we have extracted the political strategies that will be essential for the rapid industrialization of u-Learning which will, in turn, contribute much to enhance the competitiveness of national economy.

• Educational Technology International
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• v.8 no.2
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• pp.21-52
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• 2007

Research related to Web-based learning (WBL) has grown exponentially in the last decade. Scholars have explored a variety of areas related to WBL, including techniques, strategies and best practices. One area of particular interest to scholars is the potential of WBL to support and facilitative collaborative learning. Despite the continued exploration, there continues to be a concern related to the theoretical foundations of WBL. The purpose of this article is to explore how different theories may be used to guide research and inform practice in online collaborative learning. We integrate the major points drawn from current research and theory from a variety of perspectives so as to gain a better understanding of how learning is enabled by asynchronous modes of online collaborative learning. We then use this understanding to identify opportunities and challenges for theory development and research in WBL.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.127-135
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• 2024

Recent studies have shown that inverse design using deep learning has the potential to rapidly generate the optimal design that satisfies the target performance without the need for iterative optimization processes. Unlike traditional methods, deep learning allows the network to rapidly generate a large number of solution candidates for the same objective after a single training, and enables the generation of diverse designs tailored to the objectives of inverse design. These inverse design techniques are expected to significantly enhance the efficiency and innovation of design processes in various fields such as aerospace, biology, medical, and engineering. We analyzes inverse design models that are mainly utilized in the nano and chemical fields, and proposes inverse design models based on supervised and unsupervised learning that can be applied to the engineering system. It is expected to present the possibility of effectively applying inverse design methodologies to the design optimization problem in the field of engineering according to each specific objective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3867-3886
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• 2015

This article investigates the problem of opportunistic spectrum access in dynamic environment, in which the signal-to-noise ratio (SNR) is time-varying. Different from existing work on continuous feedback, we consider more practical scenarios in which the transmitter receives an Acknowledgment (ACK) if the received SNR is larger than the required threshold, and otherwise a Non-Acknowledgment (NACK). That is, the feedback is discrete. Several applications with different threshold values are also considered in this work. The channel selection problem is formulated as a non-cooperative game, and subsequently it is proved to be a potential game, which has at least one pure strategy Nash equilibrium. Following this, a multi-agent Q-learning algorithm is proposed to converge to Nash equilibria of the game. Furthermore, opportunistic spectrum access with multiple discrete feedbacks is also investigated. Finally, the simulation results verify that the proposed multi-agent Q-learning algorithm is applicable to both situations with binary feedback and multiple discrete feedbacks.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.222-232
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• 2021

The power output of solar panels highly depends on environmental situations like weather and air pollution. Due to bad weather or air pollution, it is difficult for solar panels to operate at their full potential. Knowing the power output of solar panels in advance helps set up the solar panels correctly and work their possible potential. This paper presents an approach to predict the power output of solar panels based on weather and air pollution features using machine learning methods. We create machine learning models with three kinds set of features, such as weather, air pollution, and weather and air pollution. Our datasets are collected from the area of Seoul, South Korea, between 2017 and 2019. The experimental results show that the weather and air pollution features can be efficient factors to predict the power output of solar panels.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.2
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• pp.146-165
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• 2012

The purpose of this study is development of learning coaching program that is grafted onto advantage of Self-directed learning and coaching intended for Youth-After-School-Academy children and analysis the effect on self-efficacy and Self-directed learning ability from this program. The program of this study is developed on the base of Seels & Richey's 'ADDIE Model'. In order to verify the effect of this study, two times tests were carried out on 14 persons of the experimental group and the control group respectively, before and after the program was performed. The MANCOVA & ANCOVA was done on the difference between the post-test results of the experimental group and the control group. Findings of this study might be summarized as follows: First, the post-test result in the experimental group on self-efficacy was meaningfully higher than in the control group. Second, on Self-directed learning ability the result in the experimental group was also higher than in the control group. Therefore, learning coaching program impacted on self-efficacy and Self-directed learning ability of Youth-After-School-Academy children. This program that aim to discover the potential on learning, expect to be effective for children education of today when pursue Self-directed learning ability and creativity.

• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• The Journal of Korean Association of Computer Education
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• v.16 no.4
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• pp.47-54
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• 2013

Currently, the robot is widely utilized in various educational settings such as after-school classes, and special classes for gifted students. The robot is widely recognized as a useful tool for helping students solve problems. The core activities of programming learning with robot need to provide various problem contexts to the students and guide students' problem solving process. Students gain cognitive and affective benefits when they solve problems with robots. This paper describes the impact of programming learning using robot based on schoolwide enrichment model on elementary school students' creative potential. As a result, the students of experimental group than the students of the control group improved creative personality and ideational behavior, and the gifted students of experimental group than the gifted students of control group improved ideational behavior.