• Title/Summary/Keyword: 게임기반학습

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A Study on Evaluation of the Reading Culture Promotion Project and Develpment Direction of Smart Era at the National Library for Children and Young Adults (국립어린이청소년도서관의 독서문화진흥사업 평가와 스마트 시대 발전방향에 대한 연구)

  • Kang, Ji Hei;Cha, Sung-Jong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.31 no.2
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    • pp.203-221
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    • 2020
  • This study closely analyzed changes in the educational environment and changes in the needs of children's and young people's reading culture programs, which are directly beneficiaries of the promotion of reading culture as they enter the fourth industrial revolution. It also comprehensively evaluated the reading culture promotion project for children and adolescents promoted by the National Children and Youth Library and proposed a reading culture promotion project that meets the needs of the smart era. This study investigated the cases of various domestic and foreign reading culture promotion projects to divulge trends. The authors invited experts from public libraries and school libraries with experience of the reading culture promotion projects and performed Focus Group Interviews (FGI). The authors evaluated individual reading culture program based on the PDCA method (Plan, Do, Check, Act). Based on the data obtained through case studies and expert evaluations, the development plan of reading culture promotion project and the strategy of promoting new projects to be pursued in the National Children and Youth Library were presented. By gathering the results of the research, 'Interactive e-book making platform production / distribution business', 'Game-type reading program production / distribution business', 'Habruta reading culture dissemination project using backward learning method', 'Youth coding branding "Teen-Start -Up"' were proposed as new services.

Inductive Inverse Kinematics Algorithm for the Natural Posture Control (자연스러운 자세 제어를 위한 귀납적 역운동학 알고리즘)

  • Lee, Bum-Ro;Chung, Chin-Hyun
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.4
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    • pp.367-375
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    • 2002
  • Inverse kinematics is a very useful method for control]ing the posture of an articulated body. In most inverse kinematics processes, the major matter of concern is not the posture of an articulated body itself but the position and direction of the end effector. In some applications such as 3D character animations, however, it is more important to generate an overall natural posture for the character rather than place the end effector in the exact position. Indeed, when an animator wants to modify the posture of a human-like 3D character with many physical constraints, he has to undergo considerable trial-and-error to generate a realistic posture for the character. In this paper, the Inductive Inverse Kinematics(IIK) algorithm using a Uniform Posture Map(UPM) is proposed to control the posture of a human-like 3D character. The proposed algorithm quantizes human behaviors without distortion to generate a UPM, and then generates a natural posture by searching the UPM. If necessary, the resulting posture could be compensated with a traditional Cyclic Coordinate Descent (CCD). The proposed method could be applied to produce 3D-character animations based on the key frame method, 3D games and virtual reality.

The effect of Virtual Reality sports experience on sports satisfaction, sports immersion, and sports attitude

  • Myung-Soo, Kim;Byung-Nam, Min;Seung-Hwan, Lee;Sung-Hee, Kim;Jae-Hoon, Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.129-136
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    • 2023
  • In this paper, we propose the positive effects of Virtual Reality(VR) sports classes and the foundation for VR sports to become the basis of lifelong sports education through the application of physical education classes in sports virtual reality programs are to be provided. For this purpose, the effect of VR sports experience on sports satisfaction, sports immersion, and sports attitude factors was investigated for 281 elementary school students in Busan. Results It was found that VR sports experience had a significant effect on sports satisfaction, sports satisfaction had a significant effect on sports immersion and sports attitude, and sports immersion had a significant effect on sports attitude. The great advantage of sports virtual reality is that sports activities for items that are difficult to deal with in physical education classes and unpopular items will be easily performed. In addition, by using a program that links physical education classes with English and mathematics, physical education will be recognized as a convergence subject by elementary school students, and at the same time, it will become an integrated subject that can acquire fun elements and learning elements at the same time through play or games.

An analysis of students' engagement in elementary mathematics lessons using open-ended tasks (개방형 과제를 활용하는 초등 수학 수업에서 학생의 참여 분석)

  • Nam, Inhye;Shin, Bomi
    • The Mathematical Education
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    • v.62 no.1
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    • pp.57-78
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    • 2023
  • Students' engagement in lessons not only determines the direction and result of the lessons, but also affects academic achievement and continuity of follow-up learning. In order to provide implications related to teaching strategies for encouraging students' engagement in elementary mathematics lessons, this study implemented lessons for middle-low achieving fifth graders using open-ended tasks and analyzed characteristics of students' engagement in the light of the framework descripors developed based on previous research. As a result of the analysis, the students showed behavioral engagement in voluntarily answering teacher's questions or enduring difficulties and performing tasks until the end, emotional engagement in actively expressing their pleasure by clapping, standing up and the feelings with regard to the topics of lessons and the tasks, cognitive engagement in using real-life examples or their prior knowledge to solve the tasks, and social engagement in helping friends, telling their ideas to others and asking for friends' opinions to create collaborative ideas. This result suggested that lessons using open-ended tasks could encourage elementary students' engagement. In addition, this research presented the potential significance of teacher's support and positive feedback to students' responses, teaching methods of group activities and discussions, strategies of presenting tasks such as the board game while implementing the lessons using open-ended tasks.

Study on Development of Digital Ocean Information Contents for Climate Change and Environmental Education : Focusing on the 3D Simulator Experiencing Sea Level Rise (기후변화 환경교육을 위한 디지털 해양정보 콘텐츠 개발 방안 연구 - 해수면 상승 체험 3D 시뮬레이터를 중심으로 -)

  • Jin-Hwa Doo;Hong-Joo Yoon;Cheol-Young Lee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.5
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    • pp.953-964
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    • 2023
  • Climate change is undeniably the most urgent challenge that humanity faces today. Despite this, the level of public awareness and understanding of climate change remains insufficient, indicating a need for more proactive education and the development of supportive content. In particular, it is crucial to intensify climate change education during elementary and secondary schooling when values and ethical consciousness begin to form. However, there is a significant lack of age-appropriate, experiential educational content. To address this, our study has developed an innovative 3D simulator, enabling learners to indirectly experience the effects of climate change, specifically sea-level rise. This simulator considers not only sea-level rise caused by climate change but also storm surges, which is a design based on the analysis of long-term wave observation big data. To make the simulator accessible and engaging for students, we utilized the 'Unity' game engine. We further propose using this simulator as a part of a comprehensive educational program on climate change.

Incorporating Social Relationship discovered from User's Behavior into Collaborative Filtering (사용자 행동 기반의 사회적 관계를 결합한 사용자 협업적 여과 방법)

  • Thay, Setha;Ha, Inay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.1-20
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    • 2013
  • Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.