• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.99-109
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• 2011

Ubiquitous computing technology makes an impact on the appearance of u-learning and presents an advanced direction of futuristic school education. In ubiquitous learning environments, various embedded computational devices will be pervasive and interoperable across the network for supporting the learning, so users may utilize these devices anytime anywhere. An important next step for ubiquitous learning is the introduction of context-aware learning service that employing knowledge and reasoning to understand the local context and share this information in support of intelligent learning services. However, the existing studies on design and application of ontology context model to support context-aware service in actual school environments are incomplete state. This paper, therefore, suggests a scheme of constructing ubiquitous learning space for existing school network by introducing USN to support context-aware ubiquitous learning services. This paper, also, designs an ontology based context model for ubiquitous school environments which describes context information through OWL. To determine the suitability of proposed ubiquitous learning space and ontology context model, we implement some of context-aware learning services in the ubiquitous learning environments.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1303-1311
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• 1999

In order to learn in dynamic environments, reinforcement learning algorithms like Q-learning, TD(0)-learning, TD(λ)-learning have been proposed. however, most of them have a drawback of very slow learning because the reinforcement value is given when they reach their goal state. In this thesis, we have proposed a reinforcement learning method that can approximate fast to the goal state in maze environments. The proposed reinforcement learning method is separated into global learning and local learning, and then it executes learning. Global learning is a learning that uses the replacing eligibility trace method to search the goal state. In local learning, it propagates the goal state value that has been searched through global learning to neighboring sates, and then searches goal state in neighboring states. we can show through experiments that the reinforcement learning method proposed in this thesis can find out an optimal solution faster than other reinforcement learning methods like Q-learning, TD(o)learning and TD(λ)-learning.

• Korean Journal of Child Studies
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• v.30 no.5
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• pp.73-85
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• 2009

The purpose of this research was to compare mathematically gifted students with non-gifted students in perception of learning environments, learning ability beliefs, and preference for problem-solving and task. Thirty-seven mathematically gifted students and 75 general students in middle school completed questionnaires about perceptions about mathematics. Data were analyzed by ${\chi}^2$ test and t-test. Compared with general students, mathematically gifted students estimated their talents for mathematics higher, studied mathematics more, expended more time and effort to solving difficult problems, put learning mathematics itself as their primary purpose for studying mathematics and regarded inappropriate environments as the major obstacle to mathematics study. Mathematically gifted students perceived their parents' support higher, solved problem creatively, and had higher preference for challenging tasks.

• Journal of Korean Elementary Science Education
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• v.25 no.3
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• pp.307-317
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• 2006

Those students with ability and interest in science should be supported to develop their potential and to reach high levels of achievement in science and technology. In order to ensure that gifted pupils are able to enhance their creativity as well as research abilities, appropriate learning programs and environments are essential. One of the various teaching and learning models for the gifted in science is the discovery learning model based on inductive science activities. There is a clear line of continuity between knowledge discovery at the forefront of research and student's learning activities. If students receive excellent training in organizing scientific concepts for themselves, they will be able to skillfully apply appropriate scientific concepts and solve problems when facing unfamiliar situations. It is very important to offer an appropriate learning environment to maximize the learning effect whilst, at the same time, understanding individual student's characteristics. In this study, the authors took great pains to research effective learning environments for gifted science students. Firstly, appropriate classroom learning environments thought by the teacher to offer the most potential were investigated. 3 different classes in which a revised teaching and learning environment was applied in sequence were examined. Inquiries were conducted into students' activities and achievement through observation, interviews, and examination of students' worksheets. A Science Education expert and 5 elementary school teachers specializing in gifted education also observed the class to examine the specific character of gifted science students. A number of suggestions in discovery learning classes for elementary students gifted in science are possible; 1) Readiness is essential in attitudes related to the inquiry. 2) The interaction between students should be developed. A permissive atmosphere is needed in small group activities. 3) Students require training in listening to others. In a whole class discussion, a permissive atmosphere needs to be restricted somewhat in order to promote full and inclusive discussion. 4) Students should have a chance to practice induction and abduction methods in solving problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.279-284
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• 2009

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method using many SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of Cascade SVM is adopted in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.66-69
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• 2003

This paper considers a reinforcement learning(RL) which deals with real environments. Most reinforcement learning studies have been made by simulations because real-environment learning requires large computational cost and much time. Furthermore, it is more difficult to acquire many rewards efficiently in real environments than in virtual ones. The most important requirement to make real-environment learning successful is the appropriate construction of the state space. In this paper, to begin with, I show the basic overview of the reinforcement learning under real environments. Next, 1 introduce a state-space construction method under real environmental which is State Partition Method. Finally I apply this method to a robot navigation problem and compare it with conventional methods.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.475-483
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• 2009

With the development of information communication and network technologies, ubiquitous era that supports various services regardless of places and time has been advancing. The development of such technologies have a great influence on educational environments. As a result, e-learning concepts that learners use learning contents in anywhere and anytime have been proposed. The various learning contents authoring systems that consider the e-learning environments have also been developed. However, since most of the existing authoring systems support only PC environments, they is not suitable for various ubiquitous mobile devices. In this paper, we design and implement a contents authoring system based on learning activities for u-learning environments. Our authoring system significantly improves the efficiency for authoring contents and supports various ubiquitous devices as well as PCs.

• Knowledge Management Research
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• v.25 no.1
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• pp.155-172
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• 2024

This study investigates the effectiveness of foreign language learning through diverse treatments in virtual settings, particularly by differentiating virtual environments with three textual enhancement techniques. A 2 × 3 mixed-factorial design was used, treating virtual environments as within-subject factors and textual enhancement techniques as between-subject factors. Participants experienced two videos, each in different virtual learning environments with one of the random textual enhancement techniques. The results showed that the interaction between different virtual environments and textual enhancement techniques had a statistically significant impact on presence among groups. In examining main effects of virtual environments, significant differences were observed in flow and attitude toward pre-post learning. Also, main effects of textual enhancements notably influenced flow, intention to use, learning satisfaction, and learning confidence. This study highlights the potential of Metaverse in foreign language learning, suggesting that learner experiences and effects vary with different virtual environments.

• The Journal of Korea Robotics Society
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• v.10 no.2
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• pp.79-89
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• 2015

The purpose of this study was to examine the concept of r-learning based on existing studies of r-learning. It also aimed to analyze r-learning environments in an effort to determine prerequisites for the successful entrenchment of r-learning in material(technology and infrastructure), human(young children and teacher) and institutional(law and policy) aspects. This study intended to suggest some of the right directions for the revitalization of r-learning. In conclusion, the position of r-learning and its interrelationship with related systems in the ecosystem of early childhood education should accurately be grasped to accelerate the integration of r-learning into kindergarten education to maximize the effects of the convergence of the two. Intensive efforts should be made from diverse angles to expedite the spread and enrichment of r-learning.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.95-102
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• 2008

The interactive virtual reality technology has used in scientific inquiry learning since it can overcome the restriction of real world and it draws user's interest and foster active participation. However, prior works are mostly designed for a specific inquiry learning lesson and it is quite difficult to use them for constructing other inquiry learning environments. Hence, we developed the integrated virtual reality system, SASILE (System for Augmenting Scientific Inquiry Learning Environments), that helps ease the development of the scientific inquiry learning environment. In this paper, we first describe the related works on supporting VR scientific inquiry learning systems, followed by the SASILE system architecture and implementation. Then, we illustrate the use of this system to develop a Virtual Moyangsung application for teaching a scientific structure of Korean traditional house by exploring and observing the convection currents as well as a Mars Rover application for estimating the asteroid impacts on Mars by measuring rock properties. Finally, we will discuss the future research directions for this system.