• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.119-128
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• 2019

Minecraft game is a sandboxed game based on a high degree of users' freedom; the game encourages its users to recreate various play patterns to increase their immersion. Although recently there were many studies that use Minecraft game techniques to improve the teaching methods but still not well adapted due to being applications-based techniques. In this paper, we present a teaching model that utilizes the same concept of the Minecraft games in where learners customize the class concepts based on their needs. Moreover, Minecraft-based learning games attempt to be used for learner-led, creativity and programming instruction, to overcome these use-cases limitations, by our study we aim to include the Minecraft-based learning games in class teaching activities, theoretical and practical lessons. In this way, we intend to increase interest in programming lessons, and to increase immersion as another way of game learning. In the future, we attempt to measure various effects of the uses of Minecraft-game-based teaching in programming classes compare to the traditionally used methods.

• Journal of the Korea Society for Simulation
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• v.3 no.2
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• pp.69-76
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• 1994

Traditionally, simulation-based learning games which are known as flight-simulators have been constructed as a black-box game. Within a black-box game, game-players can view and modify only a part of model parameters. Game-players cannot change the structure of a simulation model. In a black-box game, game-players cannot understand and learn the system structure which is responsible for the system behavior. In this paper, the multi-tasking at the level of operating systems is exploited to enhance the transparency of simulation-based learning game. The white-box game or transparent-box game allows game-players ot view and modify the model structure. The multi-tasking solution for white-box learning game is implemented with Smalltalk language on MS-/windows operating system.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.259-264
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• 2019

In this paper, the prototyping process for developing syllable-initial consonant-based game 'Korean Guards' is described. Users may effectively learn Korean words using alphabetically sequential approaches, but the easiness of access bestowed on the smart environments and game algorithms could be fully utilized for the functional advantages for educational purposes. This functional game is developed on Android OS and the prototypical outcome is shown.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.35-38
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• 2006

The purpose of this study is to design and develop internet-based game content in elementary mass class. The design of Internet-based learning game content should be different from general game contents in terms of achieving learning goal, challenging learning steps, and learning motivation. This study presents the design and development strategies in the second grade multiply mass class. This study concludes that internet-based game content should consider the importances of the process of game, accumulations of game results to remind learners of what to achieve during the internet class not to enjoy the game itself.

• Journal of The Korean Association of Information Education
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• v.21 no.6
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• pp.607-618
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• 2017

Recently, there is a growing interest in learning to use games as a teaching method for digital native learners. In this study, we conducted a path analysis between bodily-kinesthetic intelligence, linguistic intelligence, flow, learning outcomes(academic achievement, persistence intention) in motion-capture game-based learning(the used game developed for elementary school history class). As a result, bodily-kinesthetic intelligence directly influenced flow and indirectly influenced learning outcomes. Linguistic intelligence did not have direct influence on flow and indirect effects on learning outcomes. Through this result, we expected that the motion-capture game-based learning facilitate learning motivation and performance of learners for higher bodily-kinesthetic intelligence.

• Journal of Digital Contents Society
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• v.10 no.4
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• pp.659-667
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• 2009

ADL SCORM(Sharable Content Object Reference Model) has been widely accepted as a global reference model for standardizing e-learning technology, and SCORM 2004 4th Edition, a stable version of SCORM, gives content developers the efficient way to build interoperable and reusable e-learning contents. Recently, a number of research efforts have been taken to build on-line SCORM contents based on some traditional training or learning styles. However, they have lacked for supporting more sophisticated learning style such as game based learning, and especially they do not consider employing the specific components of SCORM model for developing game based learning contents in practice. In this work, we elicit some SCORM data elements that is useful for representing game run-time data, and apply those elements to SCORM sequencing of game based learning SCOs(Sharable Content Objects). We thus present the whole procedure of developing SCORM game based learning contents with a sample contents.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.137-148
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• 2017

Researches on the Artificial Intelligence has been explosively activated in various fields since the advent of AlphaGo. Particularly, researchers on the application of multi-layer neural network such as deep learning, and various machine learning algorithms are being focused actively. In this paper, we described a development of an artificial intelligence Janggi game based on reinforcement learning algorithm and MCTS (Monte Carlo Tree Search) algorithm with accumulated game data. The previous artificial intelligence games are mostly developed based on mini-max algorithm, which depends only on the results of the tree search algorithms. They cannot use of the real data from the games experts, nor cannot enhance the performance by learning. In this paper, we suggest our approach to overcome those limitations as follows. First, we collects Janggi expert's game data, which can reflect abundant real game results. Second, we create a graph structure by using the game data, which can remove redundant movement. And third, we apply the reinforcement learning algorithm and MCTS algorithm to select the best next move. In addition, the learned graph is stored by object serialization method to provide continuity of the game. The experiment of this study is done with two different types as follows. First, our system is confronted with other AI based system that is currently being served on the internet. Second, our system confronted with some Janggi experts who have winning records of more than 50%. Experimental results show that the rate of our system is significantly higher.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.1
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• pp.59-74
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• 2024

In order to improve safety consciousness due to the increase in disasters and safety accidents, safety education is necessary to prepare for disasters with interest in safety. This study is a board game design for disaster safety education for elementary school students based on Keller's learning motivation theory. By considering the school safety curriculum and the safety education contents of the School Safety Mutual Aid Association and the Ministry of Public Administration and Security, the content and goals of learning were derived and the order of learning was determined. When designing game content, the fun elements of the game were applied to Keller's learning motivation inducing factors such as attention concentration (A), relevance (R), confidence (C), satisfaction (S), and educational game design elements to induce the achievement of learning goals at the game planning stage. It is expected that the existing safety education focusing on lecture-style and audiovisual will be supplemented and used in the educational field.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1657-1664
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• 2018

This paper proposes a decision making scheme for choosing the best move at each state of game in order to implement an artificial intelligence othello game player. The proposed decision making scheme predicts the various possible states of the game when the game has progressed from the current state, evaluates the degree of possibility of winning or losing the game at the states, and searches the best move based on the evaluation. In this paper, we generate learning data by decomposing the records of professional players' real game into states, matching and accumulating winning points to the states, and using the Artificial Neural Network that learned them, we evaluated the value of each predicted state and applied the Minimax search to determine the best move. We implemented an artificial intelligence player of the Othello game by applying the proposed scheme and evaluated the performance of the game player through games with three different artificial intelligence players.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.157-164
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• 2003

To enhance the effect of learning in vocabulary learning, it is important first of all for learner to take active learning and be interested in learning, not cramming education. Due to this background, the instructor sometimes takes advantage of the game concepts in producing the courseware for vocabulary learning. But because of overwhelming overload in making the game-based courseware, it have been not made practical application to vocabulary learning. In this research, we study on the strategy for making practical application of the game concept to producing the courseware for vocabulary learning. And, based on the strategy, we design and implement the authoring tool of courseware for vocabulary learning based on crossword puzzle game. This tool enables instructor to produce the courseware based on crossword puzzle game easily and quickly and to make efficiently the courseware for vocabulary learning with level.