• Journal of the Korea Convergence Society
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• v.6 no.1
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• pp.23-28
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• 2015

Teaching programming skills is not only required for computer related departments but through the area of engineering and natural science. Moreover recently teaching programming skill is emphasized in software education for primary schools and secondary schools. Since programming ability is considered an essencial element of national competitiveness, we need programming learning system which alleviates the difficulty. We implemented Blockly webc Programming Convergent Learning System which is based on the graphic tools called Blockly by Google. Inside system problem sets for the programming beginners are embedded in the system. These problem sets are gone under more than 20 years verification and these problem sets may be used to help beginning programmers escape novice coder in short time. Blockly webc Programming Convergent Learning System together with already developed Simple Visual Language2 Programming Learning System is expected to play an important role as a programming learning system for the beginners.

• Journal of The Korean Association of Information Education
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• v.14 no.1
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• pp.123-130
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• 2010

In this paper, we introduce a new programming learning system for young students. The programming learning system consists of a LED display kit and a web-based flowchart system. The LED display kit acts as an output device by way of displaying lights while following a set of instructions given through a flowchart programming. In the flowchart system, the students use symbolic variables for the calculation and can get various displays or animations after creating a flowchart by drag-and-drop. Then we describe the survey results of various programming classes using our system between fall 2005 and spring 2009. The programming teaching was conducted with diverse groups such as elementary school students, gifted students, college students, and teachers etc. The responses from our in class surveys were generally positive.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.51-58
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• 2010

Programming education needs learning which is adjusted individual learners' level of their learning abilities. Recommendation system is one way of implementing personalized service. In this research, we propose recommendation method which learning items are recommended for individual learners' learning in web-based programming education environment by. Our proposed system for leveled programming education provides appropriate programming problems for a certain learner in his learning level and learning scope employing collaborative filtering method using learners' profile of their level and correlation profile between learning topics. As a result, it resolves a problem that providing appropriate programming problems in learner's level, and we get a result that improving leaner's programming ability. Furthermore, when we compared our proposed method and original collaborative filtering method, our proposed method provides the ways to solve the scalability which is one of the limitations in recommendation systems by improving recommendation performance and reducing analysis time.

• The Journal of Korean Association of Computer Education
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• v.10 no.6
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• pp.1-10
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• 2007

Programming is emphasized in information(computer science) education course domestically and in foreign countries, and novices are given ample opportunities to experience programming. Programming error is a critical factor which makes it difficult to learn programming for novices. However, if they are given appropriate feedback, it can have positive influence on programming learning. In this paper, we design programming learning supporting system for novice through error feedback and provide some implementations for EPL 'Dolittle'. This system has four features as highlighting, guiding messages, object tree, and step-execution.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.11-17
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• 2010

In this paper, we propose a recommendation system for supporting self-directed programming language education. The system is a recommendation system using collaborative filtering based on learners' level and stage. In this study, we design a recommendation system which uses collaborative filtering based on learners' profile of their level and correlation profile between learning topics in order to increase self-directed learning effects when students plan their learning process in e-learning environment. This system provides a way for solving a difficult problem, that is providing programming problems based on problem solving ability, in the programming language education system. As a result, it will contribute to improve the quality of education by providing appropriate programming problems in learner"s level and e-learning environment based on teaching and learning method to encourage self-directed learning.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.382-389
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• 2009

Recently, knowledge management has been required in companies as a tool of competitiveness. Companies have constructed Enterprise Resource Planning(ERP) system in order to manage huge knowledge. But, it is not easy to formalize knowledge in organization. We focused on data mining system by genetic programming(GP). Data mining system by genetic programming can be useful tools to derive and extract the necessary information and knowledge from the huge accumulated data. However when we don't have enough amounts of data to perform the learning process of genetic programming, we have to reduce input parameter(s) or increase number of learning or training data. In this study, an enhanced data mining method combining Genetic Programming with Self organizing map, that reduces the number of input parameters, is suggested. Experiment results through a prototype implementation are also discussed.

• The Journal of Korean Association of Computer Education
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• v.12 no.4
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• pp.1-11
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• 2009

There are several studies in order to learn about programming language. This paper develops a peer agent system based on teaching and learning strategies in order to improve problem-solving ability. Problem-solving ability involves three components - content understanding, domain-dependent problem-solving strategies, and self-regulation. This paper shows the teaching and learning strategies about components of problem-solving for learning to program and the peer agent system uses the teaching and learning strategies. This study intents to analyze the educational effects of the peer agent system. The results show that the system has superior effects on problem-solving ability compared to traditional programming courses or pair programming courses. It means that the peer agent system is the effective educational system in improving student's problem-solving ability.

• Journal of The Korean Association of Information Education
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• v.9 no.2
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• pp.349-358
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• 2005

It is not sufficient to give a lecture in programming language without programming practice since lectures on programming must be given at lecture room with H/W and S/W for programming. In this paper, learning for Visual Basic programming has been designed and embodied with the leveled learning system in order to give an effective and positive result to both teacher and learner under the constructivism theory of education (Problem Based learning, Self-Directed learning) for the theoretical basis of the seventh education curriculum. We implemented a web courseware for Visual Basic programming using ActiveX and Tutor System. As the result of education using this courseware, it is verified as a leveled education method to adapt the learning ability of individual students, and it can raise the achievement, enthusiasm of learning and provide various opportunity of education with this various education methods. Also it enhances the problem solving ability and the logical thinking power by providing students with error correction learning.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.354-359
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• 2006

The analysis of large-scale water resources systems is often complicated by the presence of multiple reservoirs and diversions, the uncertainty of unregulated inflows and demands, and conflicting objectives. Reinforcement learning is presented herein as a new approach to solving the challenging problem of stochastic optimization of multi-reservoir systems. The Q-Learning method, one of the reinforcement learning algorithms, is used for generating integrated monthly operation rules for the Keum River basin in Korea. The Q-Learning model is evaluated by comparing with implicit stochastic dynamic programming and sampling stochastic dynamic programming approaches. Evaluation of the stochastic basin-wide operational models considered several options relating to the choice of hydrologic state and discount factors as well as various stochastic dynamic programming models. The performance of Q-Learning model outperforms the other models in handling of uncertainty of inflows.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.292-297
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• 1999

Evolving in artificial agent is an extremely difficult problem, but on the other hand, a challenging task. At present the studies mainly centered on single agent learning problem. In our case, we use simulated soccer to investigate multi-agent cooperative learning. Consider the fundamental differences in learning mechanism, existing reinforcement learning algorithms can be roughly classified into two types-that based on evaluation functions and that of searching policy space directly. Genetic Programming developed from Genetic Algorithms is one of the most well known approaches belonging to the latter. In this paper, we give detailed algorithm description as well as data construction that are necessary for learning single agent strategies at first. In following step moreover, we will extend developed methods into multiple robot domains. game. We investigate and contrast two different methods-simple team learning and sub-group loaming and conclude the paper with some experimental results.