• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.255-265
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• 2021

The purpose of this study was to examine the effects of Kahoot!(Game-based Student Response System) on nursing education. This study used an one group Pretest-posttest design. Participants were 179 nursing students from one D university located in Gwangju, Korea. The Kahoot!(Game-based Student Response System) was provided for 6 times. Data were collected between August 26 and October 25, 2019. The collected data was analyzed by descriptive statistics, paired t-test, pearson's correlation coefficient and stepwise multiple regression using IBM SPSS 21.0 program. The results showed that learning engagement(t=-6.257, p=.000) was significantly higher than levels before Kahoot!(Game-based Student Response System), critical thinking disposition(t=-2.163, p=.032) was significantly higher than levels before Kahoot!(Game-based Student Response System), problem solving ability(t=-3.032, p=.003) was significantly higher than levels before Kahoot!(Game-based Student Response System). Significant relationships were found among learning engagement(r=.375, p=.000), critical thinking disposition(r=.286, p=.000), problem solving ability(r=.291, p=.000) and learning satisfaction. The results of stepwise multiple regression indicates that learning engagement(β=.307, p=.000), problem solving ability(β=.158, p=.041) predicts 15.2% in learning satisfaction(F=16.905, p=.000). In conclusion, Kahoot!(Game-based Student Response System) is effective in improving learning engagement and problem solving ability to nursing education.

• Journal of The Korean Association of Information Education
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• v.5 no.3
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• pp.321-328
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• 2001

Generally, a Learning Games made based on Off-line. But Today, Web based learning has been used for many educational system by aid of the development of internet technique. If Off-line learning game serviced by On-line learning game, can provide learner with interesting and growing learner's study will. In this paper, I design the Mathematical of Elementary school Roll playing game for learning based on On-line. This is matched the point of On-line game with the point of Learning. A Learner's mathematical technic will be improve by The Mathematical On-line Roll playing game for Elementary school student. A student's ability of self directed learning and solving problem is expended too.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1004-1012
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• 2022

This paper contains the implementation of a game as a feature of a package tour management application with the Digital Game-based Learning approach that helps tourists learn about tourism spots. The game is written in Java language for an Android smartphone that is designed to be integrated with Content Management System (CMS) to manage the game's contents and assets. The game contains one tourism spots introductory level and five quiz game levels with each having a reward (points) and punishment (time penalty) system, then summed the results to obtain the total score from all levels. The total score will determine a tourist's performance and be listed on an online leaderboard to increase competitiveness among tourists. The conducted performance evaluation of the game shows satisfactory results of 0.9 seconds of response time from the database to the game. Implementing the game presented in this paper will potentially reduce the burden of the tour guide and increase the efficiency of managing the tour group.

• Journal of Korea Game Society
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• v.10 no.6
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• pp.37-45
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• 2010

The purpose of this paper is to analyze a positive educational effect of G learning(online game based learning). G learning has become an effective learning tool for constructivism based learning. Therefore, the paper developed G learning 'SKY math' and applied it to the elementary students. Through the analysis, the fact has been found that students' attitude and confidence for Math changed positively.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.603-611
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• 2016

Educational games offer an opportunity to engage and inspire students to take an interest in every subject material in school. The "fun" obtain when playing games become a trigger for the use of games in learning. However, there are doubts whether the players actually learn while they are having fun. Vidyanusa is an Online Mathematics Education Game being developed by Crayonpedia Education Ecosystem in Indonesia. The learning goal of Vidyanusa is to engage junior high school students in learning mathematics. In this paper, we design the Vidyanusa game material Functions and Relations by using Balanced Design Approach. This approach has three models in succession; the Content Model outlines the purpose of the game, the Task Model maps out the mission, and the Evidence Model outlines student measurement. This paper will then discusses the quality of games produced in term of Usability factor for effective results and objective. The measurement of the game was carried out based on International Standard ISO/IEC 9126-1 FDIS about Software Quality Product.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.155-160
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• 2012

This paper designed a smartphone application with sequence problems which users can improve their learning ability and this application is implemented as serious game which is designed for the special purposes of education with entertainment and game-like fun at anytime and anywhere during the spare time. Also to prove learning effects through sequence of number application under ubiquitous environment which is popular these days, the proposed serious game which has various types of sequence questions is implemented based on the iphone and android environments. User characteristics and learning effects which are based on game record of proposed application are analyzed according to socio-demographic characteristics.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.267-277
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• 2024

This paper explores the use of machine learning in game production to create goal-oriented, realistic animations for skeleton monsters. The purpose of this research is to enhance realism by implementing intelligent movements in monsters within game development. To achieve this, we designed and implemented a learning model for skeleton monsters using reinforcement learning algorithms. During the machine learning process, various reward conditions were established, including the monster's speed, direction, leg movements, and goal contact. The use of configurable joints introduced physical constraints. The experimental method validated performance through seven statistical graphs generated using machine learning methods. The results demonstrated that the developed model allows skeleton monsters to move to their target points efficiently and with natural animation. This paper has implemented a method for creating game monster animations using machine learning, which can be applied in various gaming environments in the future. The year 2024 is expected to bring expanded innovation in the gaming industry. Currently, advancements in technology such as virtual reality, AI, and cloud computing are redefining the sector, providing new experiences and various opportunities. Innovative content optimized for this period is needed to offer new gaming experiences. A high level of interaction and realism, along with the immersion and fun it induces, must be established as the foundation for the environment in which these can be implemented. Recent advancements in AI technology are significantly impacting the gaming industry. By applying many elements necessary for game development, AI can efficiently optimize the game production environment. Through this research, We demonstrate that the application of machine learning to Unity and game engines in game development can contribute to creating more dynamic and realistic game environments. To ensure that VR gaming does not end as a mere craze, we propose new methods in this study to enhance realism and immersion, thereby increasing enjoyment for continuous user engagement.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1677-1684
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• 2017

In this paper, we tried to combine the findings obtained from pedagogical analysis of serious game, which is a study of Soo-Cheol Ha [2, 3], and learning theories such as behaviorism, cognitivism, constructivism, situated learning, and other theories. Based on the previous research, we propose pedagogical elements of serious games based on theories and researches from models and other studies using learning theory. The suggested elements were applied on GSS(Global Startup Simulation), which is a serious game, and the results were confirmed through questionnaire evaluation of learners who are learning through it.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.157-162
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• 2019

The video game Tetris is one of most popular game and it is well known that its game rule can be modelled as MDP (Markov Decision Process). This paper presents a DQN (Deep Q-Network) based game agent for Tetris game. To this end, the state is defined as the captured image of the Tetris game board and the reward is designed as a function of cleared lines by the game agent. The action is defined as left, right, rotate, drop, and their finite number of combinations. In addition to this, PER (Prioritized Experience Replay) is employed in order to enhance learning performance. To train the network more than 500000 episodes are used. The game agent employs the trained network to make a decision. The performance of the developed algorithm is validated via not only simulation but also real Tetris robot agent which is made of a camera, two Arduinos, 4 servo motors, and artificial fingers by 3D printing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3771-3788
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• 2015

This paper studies the distributed energy efficient resource management in the Internet of Things (IoT). Wireless communication networks support the IoT without limitation of distance and location, which significantly impels its development. We study the communication channel and energy management in the wireless communication network supported IoT to improve the ability of connection, communication, share and collaboration, by using the game theory and distributed learning algorithm. First, we formulate an energy efficient neighbor collaborative game model and prove that the proposed game is an exact potential game. Second, we design a distributed energy efficient channel selection learning algorithm to obtain the global optimum in a distributed manner. We prove that the proposed algorithm will asymptotically converge to the global optimum with geometric speed. Finally, we make the simulations to verify the theoretic analysis and the performance of proposed algorithm.