• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.561-571
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• 2019

Programming education generally includes problem analysis process, automation through algorithms and programming, and generalization process. It is a good software education method for students in improving computing thinking. However, it was found that beginners had difficulties in understanding instruction usage, writing algorithms, and implementing programming. In this study, we developed a game programming education model and curriculum for programming education of pre-service teachers. The 4E model consisted of empathy, exploration, engagement and evaluation. In addition, it is configured to learn game core elements and core command blocks by each stage. To help the pre-service teachers understand the use of various programming blocks, a three-step teaching and learning method was presented, consisting of example learning, self-game creation, and team-based projects. As a result of applying and verifying the curriculum for 15 weeks, it showed significant results in the 4E model and pre-service teachers' perception of block programming competence and the level of computational thinking on the submitted game project results was also high.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.17-24
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• 2019

In this paper, we propose a new model for predicting effective Win/Loss in professional baseball game in Korea using machine learning technique. we used basic baseball data and Sabermetrics data, which are highly correlated with score to predict and we used the deep learning technique to learn based on supervised learning. The Drop-Out algorithm and the ReLu activation function In the trained neural network, the expected odds was calculated using the predictions of the team's expected scores and expected loss. The team with the higher expected rate of victory was predicted as the winning team. In order to verify the effectiveness of the proposed model, we compared the actual percentage of win, pythagorean expectation, and win percentage of the proposed model.

• Journal of the Korea Institute of Building Construction
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• v.22 no.2
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• pp.219-228
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• 2022

In this study, to improve educational motivation and learning outcomes, a mobile app using game elements was developed, and the effect of its application in rebar work education was analyzed. Using the 4F(Figure out-Focus-Fun design-Finalize) process, which is a game development model, a mobile learning app for rebar work was developed that considers the characteristics of college students familiar with smartphone use, and the app was developed in a manner that utilizes game mechanics such as learning missions and points to stimulate a learner's interest and improve educational motivation. The results show that the proposed app for rebar work is positively evaluated in terms of interface style, perceived usefulness, perceived ease of use, perceived enjoyment, attitude toward using, and intention to use. Therefore, it can be concluded that using the learning game app for rebar work in classes can contribute to improving a learner's performance in various aspects.

• Human Ecology Research
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• v.54 no.3
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• pp.333-349
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• 2016

This study develops and evaluates a game-based lesson plan applied to the 'Food Culture' unit of a high school Home Economics class. We developed, implemented, and evaluated lesson plans for seven periods that contained 'the Korean food table setting card,' 'the world's food culture card,' and the procedure for cards games according to the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model. 'The Korean food table setting card' consisted of 'the Korean food table setting order card' to easily understand 10 types of Korean traditional daily meals based on pictures and 'the Korean food table setting food card' to easily understand Korean traditional food based on 104 kinds of food picture and quick response (QR) code. 'The world's food culture card' consisted of 'the world's food culture quiz card' to help learners easily understand influential food culture formation factors, features of food culture, typical foods from 16 countries, and 'the world's traditional food card' to help learners easily understand typical foods from 16 countries through 63 kinds of pictures. Respective 'game guides' were also developed. High school students who studied the game-based Home Economics classes and who participated in the 'Food Culture' unit, could easily and enjoyably learn the food culture of Korea (and other countries), actively participate in learning activities, and understood the content of food culture. In addition, they evaluated that the game-based instruction was easy to remember with minimal memorizing.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.709-714
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• 2003

It is important that the interaction between learners and contents in Educational Contents. But, there is just simple interaction in traditional WBI or CAI. As it is necessary to study for interaction with learners. There is applied more multimedia elements for the fun of learners. But, it is also necessary to study for Network Educational Game Contents which can give virtual environment to learn easily and funny. In this study, Competition Learning Model is designed for network learning environment. We can look at the new view point of Educational Contents by implementation of Network Educational Game Contents and Competition Learning Model.

• Smart Media Journal
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• v.11 no.2
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• pp.9-17
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• 2022

The purpose of this study is to implement a predictive model to support decision-making to replace a starting pitcher before a crisis situation in a baseball game. To this end, using the Major League Statcast data provided by Baseball Savant, we implement a predictive model that preemptively replaces starting pitchers before a crisis situation. To this end, first, the crisis situation that the starting pitcher faces in the game was derived through data exploration. Second, if the starting pitcher was replaced before the end of the inning, learning was carried out by composing a label with a replacement in the previous inning. As a result of comparing the trained models, the model based on the ensemble method showed the highest predictive performance with an F1-Score of 65%. The practical significance of this study is that the proposed model can contribute to increasing the team's winning probability by replacing the starting pitcher before a crisis situation, and the coach will be able to receive data-based strategic decision-making support during the game.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5820-5834
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• 2017

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

• Journal of Korea Game Society
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• v.22 no.1
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• pp.33-42
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• 2022

In online games, interactions with other players may threaten player satisfaction. Therefore, matching players of similar skill levels is important for players' experience. However, with the current evaluation method which is only based on the final result of the game, newbies and returning players are difficult to be matched properly. In this study, we propose a method to improve matchmaking quality. We build machine learning models to predict the MMR of players and derive the basis of the prediction. The error of the best model was 40.4% of the average MMR range, confirming that the proposed method can immediately place players in a league close to their current skill level. In addition, the basis of predictions may help players to accept the result.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.23-32
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• 2023

E-sports, a burgeoning facet of modern sports culture, has achieved global prominence. Particularly, Aeon of Strife (AOS) games, emblematic of E-sports, blend individual player prowess with team dynamics to significantly influence outcomes. This study aggregates and analyzes real user gameplay data using statistical techniques. Furthermore, it develops and tests win-loss prediction models through machine learning, leveraging a substantial dataset of 1,149,950 individual data points and 230,234 team data points. These models, employing five machine learning algorithms, demonstrate an average accuracy of 80% for individual and 95% for team predictions. The findings not only provide insights beneficial to game developers for enhancing game operations but also offer strategic guidance to general users. Notably, the team-based model outperformed the individual-based model, suggesting its superior predictive capability.

• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.283-292
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• 2016

Based on revised 2015 curriculum, diversified SW education methods for elementary school students are researched, developed and applied. However, as most of SW education is based on English text, its coding process may be difficult for low graders of elementary school who are not familiar with English and Math. Under this situation, Kodu game lab based 'icon card board' by which coding could be learnt with ease through game and icon was developed and story activity, coding activity and collaboration activity (SCC) strategy based 17th session SW curriculum was applied and verified. As a result of research, in terms of satisfaction of students for SW class, students more than 86% recognized such class positively and a significant effect was obtained from students' interest level and learning model for coding.