• Title/Summary/Keyword: Learning Media

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Comparative Study on the Educational Use of Home Robots for Children

  • Han, Jeong-Hye;Jo, Mi-Heon;Jones, Vicki;Jo, Jun-H.
    • Journal of Information Processing Systems
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    • v.4 no.4
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    • pp.159-168
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    • 2008
  • Human-Robot Interaction (HRI), based on already well-researched Human-Computer Interaction (HCI), has been under vigorous scrutiny since recent developments in robot technology. Robots may be more successful in establishing common ground in project-based education or foreign language learning for children than in traditional media. Backed by its strong IT environment and advances in robot technology, Korea has developed the world's first available e-Learning home robot. This has demonstrated the potential for robots to be used as a new educational media - robot-learning, referred to as 'r-Learning'. Robot technology is expected to become more interactive and user-friendly than computers. Also, robots can exhibit various forms of communication such as gestures, motions and facial expressions. This study compared the effects of non-computer based (NCB) media (using a book with audiotape) and Web-Based Instruction (WBI), with the effects of Home Robot-Assisted Learning (HRL) for children. The robot gestured and spoke in English, and children could touch its monitor if it did not recognize their voice command. Compared to other learning programs, the HRL was superior in promoting and improving children's concentration, interest, and academic achievement. In addition, the children felt that a home robot was friendlier than other types of instructional media. The HRL group had longer concentration spans than the other groups, and the p-value demonstrated a significant difference in concentration among the groups. In regard to the children's interest in learning, the HRL group showed the highest level of interest, the NCB group and the WBI group came next in order. Also, academic achievement was the highest in the HRL group, followed by the WBI group and the NCB group respectively. However, a significant difference was also found in the children's academic achievement among the groups. These results suggest that home robots are more effective as regards children's learning concentration, learning interest and academic achievement than other types of instructional media (such as: books with audiotape and WBI) for English as a foreign language.

Social Media Data Analysis Trends and Methods

  • Rokaya, Mahmoud;Al Azwari, Sanaa
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.358-368
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    • 2022
  • Social media is a window for everyone, individuals, communities, and companies to spread ideas and promote trends and products. With these opportunities, challenges and problems related to security, privacy and rights arose. Also, the data accumulated from social media has become a fertile source for many analytics, inference, and experimentation with new technologies in the field of data science. In this chapter, emphasis will be given to methods of trend analysis, especially ensemble learning methods. Ensemble learning methods embrace the concept of cooperation between different learning methods rather than competition between them. Therefore, in this chapter, we will discuss the most important trends in ensemble learning and their applications in analysing social media data and anticipating the most important future trends.

Research on the Participation Types and Strategies for Facilitating Learning based on the Analyses of Social Media Contents (소셜 미디어 콘텐츠 분석에 따른 참여유형 및 학습촉진방안 탐구)

  • Lim, Keol
    • The Journal of the Korea Contents Association
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    • v.11 no.6
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    • pp.495-509
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    • 2011
  • According to the rapid technological development such as ubiquitous environments, there has been growing interest in learning with social media as known as social learning. This study was conducted to analyze various participation types of social media contents aiming to explore strategies for facilitating learning. Specifically, the research model was established by two aspects in using social media contents. First was classified by writings and readings in contents, which consists of prosumers, producers, consumers, and non-participants. Second criterion was categorized by instruction-related and instruction-nonrelated, which is learning contents, learning management, emotional expression, and social activities. In order to acquire empirical data, a set of fourteen undergraduate students participated in this research for eight weeks using a microblog. Based on the analyses on the data through learning activities, three learning strategies were suggested to facilitate social media based learning: analysis on learners, role of the instructor, and instructional model design.

Design of Social Learning Platform for Collaborative Study (협력학습을 위한 소셜러닝 플랫폼의 설계)

  • Cho, Byung-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.5
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    • pp.189-194
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    • 2013
  • Social learning is a new study model of future knowledge information society. In different existing study, it lay stress on individual activity and collaborative study with others. It is useful to apply social media services to build social learning platform for collaborative study. In my paper, after existing social media services and social platforms are investigated and analyzed, an effective social learning platform applyng social media services is presented. Also differences and superiority compared to other social platforms is presented through new social learning platform architecture and screen design.

Effect of Flipped Learning Using Media Convergence in Practice Education on Academic Self-efficacy and Self-directed Learning of Nursing Students (미디어 융합 활용 플립러닝 기반 실습 수업이 간호대학생의 학업적 자기효능감과 자기주도학습에 미치는 효과)

  • Kim, Og Son
    • Journal of Convergence for Information Technology
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    • v.10 no.6
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    • pp.49-58
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    • 2020
  • This study was conducted to identify the changes in academic self-efficacy and self-directed learning ability after applying flipped learning using media convergence to the basic nursing practice courses. It is offering flipped learning to 22 students from the experimental group and 26 students from the control group. Data were collected from August 27 to December 3, 2019. The difference in academic self-efficacy before and after the flipped learning was no significant difference between the two groups. However, the difference in self-directed learning ability was 11.32 points in the experimental group and 0.23 points in the control group (t=2.32, p=.027). According to the results of this study, flipped learning using media convergence was found to be an effective teaching method to improve self-directed learning ability of students. Therefore, it is necessary to study the expanded application of flipped learning using media convergence to various nursing subjects.

Does Social Media Use Increase or Decrease Learning Performance? A Meta-Analysis Based on International English Journal Studies

  • Park, Ki-ho;Ren, Gaufei
    • The Journal of Information Systems
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    • v.28 no.4
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    • pp.293-311
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    • 2019
  • Purpose This paper is to make a meta-analysis of the relationship between the social media use and learning performance as well as its potential moderating variables to clarify the differences in research conclusions in existing literatures, and refine the situational and method factors that affect the relationship between them. Methodology Meta-analysis used in this study can combine the quantitative data from different empirical studies, focus on the same research problem, and finally reach a research conclusion. Findings The results show that social media use and learning performance have a moderating positive correlation. The moderating effect test of usage scenarios shows that social media types, usage groups, application platforms and discipline fields have moderating effects on the relationship between social media use and learning performance. The moderating effect test of the research method found that measurement models, data attributes and learning performance indicators also had moderating effects on the relationship between social media use and learning performance.

Instructor Factors and Media Richness Affecting Distance Learning Student's Intention to Use and Performance (교수자 요인과 매체풍부성이 원격교육 학습자의 이용의도와 학습성과에 미치는 영향)

  • Ryu In;Shin Seon-Jin
    • The Journal of Information Systems
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    • v.15 no.3
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    • pp.35-53
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    • 2006
  • Distance teaming systems have become popular tools for teaching and learning. The purpose of this study is to analyze influence of instructor factors and media richness on student's intention th use and performance in distance teaming. We used TAM as a theoretical foundation to explain student's behavior. The model was tested using LISREL analysis on the sample of 246 users rho have experience with the distance teaming systems. The results show that instructor factors such as luぉ style and attitude have partial effects on perceived usefulness, ease of use and media richness. In addition, results also show that both TAM variables and media richness strongly predict intention In use of the distance loaming system Finally, the usage intention has a positive effect on teaming performance. Implications of these findings are discussed for researchers and practitioners.

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A Survey on Deep Convolutional Neural Networks for Image Steganography and Steganalysis

  • Hussain, Israr;Zeng, Jishen;Qin, Xinhong;Tan, Shunquan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.3
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    • pp.1228-1248
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    • 2020
  • Steganalysis & steganography have witnessed immense progress over the past few years by the advancement of deep convolutional neural networks (DCNN). In this paper, we analyzed current research states from the latest image steganography and steganalysis frameworks based on deep learning. Our objective is to provide for future researchers the work being done on deep learning-based image steganography & steganalysis and highlights the strengths and weakness of existing up-to-date techniques. The result of this study opens new approaches for upcoming research and may serve as source of hypothesis for further significant research on deep learning-based image steganography and steganalysis. Finally, technical challenges of current methods and several promising directions on deep learning steganography and steganalysis are suggested to illustrate how these challenges can be transferred into prolific future research avenues.

A Study of the Influence of Medium Richness and Learner's Experience with Various Mediums on the Usefulness of Mediums and Learning Commitment in Integrated Media Korean Classical Education (매체통합 고전문학수업에서 매체풍부성과 매체경험이 매체유용성과 학습몰입에 미치는 영향 연구)

  • Hyun, Young-Ran;Chung, So-Yeon
    • Journal of Korean Library and Information Science Society
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    • v.46 no.4
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    • pp.471-491
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    • 2015
  • The purpose of this paper is to examine the structural relationship between the use of a web medium and learning commitment to develop creative talent for higher media integrated Korean classical literature education. For this we used DBs of The 'Encyclopedia of Korean Local Culture(a local culture DB)' built by the Academy of Korean Studies, and a survey was conducted on 418 high school students, attending a classical literature class which used a local culture DB. The result of this study demonstrates media usefulness of local culture DBs' positive effect on learning commitment. Specifically, media richness and media experience affects the learning commitment through the medium usefulness. These results indicate that in order to encourage learner's medium experience and increase medium richness it is necessary to increase the utilization of mediums, such as local culture DBs.

Semi-supervised Cross-media Feature Learning via Efficient L2,q Norm

  • Zong, Zhikai;Han, Aili;Gong, Qing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1403-1417
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    • 2019
  • With the rapid growth of multimedia data, research on cross-media feature learning has significance in many applications, such as multimedia search and recommendation. Existing methods are sensitive to noise and edge information in multimedia data. In this paper, we propose a semi-supervised method for cross-media feature learning by means of $L_{2,q}$ norm to improve the performance of cross-media retrieval, which is more robust and efficient than the previous ones. In our method, noise and edge information have less effect on the results of cross-media retrieval and the dynamic patch information of multimedia data is employed to increase the accuracy of cross-media retrieval. Our method can reduce the interference of noise and edge information and achieve fast convergence. Extensive experiments on the XMedia dataset illustrate that our method has better performance than the state-of-the-art methods.