• Title/Summary/Keyword: Learning with Media

검색결과 907건 처리시간 0.029초

QR코드를 활용한 퀘스트 기반학습 개발 및 적용사례 연구 (Case Study and Development of Quest-Based Learning Using QR Code)

  • 박형성
    • 한국게임학회 논문지
    • /
    • 제11권5호
    • /
    • pp.79-88
    • /
    • 2011
  • 본 연구는 스마트폰으로 인식이 가능한 QR코드를 이용한 퀘스트 기반학습을 적용하여 교육 현장에서 학습방법으로서 가능성을 확인하는데 있다. 퀘스트 기반학습의 적용은 초등학교 3학년 32명을 대상으로 1개월간 총 8차시에 걸쳐 적용되었다. 학습활동 후 학습동기의 네 가지 하위요인에 대한 다변량분석을 하였다. 연구결과, 퀘스트 기반학습은 동기하위요인 중 주의집중과 자신감 요인의 동기를 촉진하는 긍정적인 결과를 보였다. 게임형태의 퀘스트 기반학습은 다양한 미디어를 활용한 학습방법으로 교육현장에서 학습자 참여를 촉진하고, 활동중심의 경험학습을 위한 학습방법으로 활용될 수 있을 것이다.

FakedBits- Detecting Fake Information on Social Platforms using Multi-Modal Features

  • Dilip Kumar, Sharma;Bhuvanesh, Singh;Saurabh, Agarwal;Hyunsung, Kim;Raj, Sharma
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제17권1호
    • /
    • pp.51-73
    • /
    • 2023
  • Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

기업가정신, 정보기술 수용성, 미디어 활용역량이 직장인의 업무몰입에 미치는 영향: 학습지향성 조절 효과를 반영하여 (Effects of Entrepreneurship, Information Technology Acceptance, and Media Utilization on Office Worker Commitment: with Moderating Effect of Learning Orientation)

  • 이상길;하규수
    • 벤처창업연구
    • /
    • 제12권3호
    • /
    • pp.37-51
    • /
    • 2017
  • 본 연구는 기업가정신, 정보기술 수용성, 미디어 활용역량이 직장인의 업무몰입에 미치는 영향에 관해 학습 지향성을 조절 효과로 반영하여 탐구하였다. 이는 스마트 정보화 시대에 개인과 조직에서의 핵심 역량 즉, 기업가정신, 정보기술 수용성, 미디어 활용역량이 업무몰입에 유의한 영향을 미치는지와 독립변수로 제시된 기업가정신, 정보기술 수용성, 미디어 활용역량과 종속변수인 업무몰입 간에 학습 지향성의 조절 효과를 분석하여, 업무몰입에 영향을 미치는 변수들을 규명하는 데 그 목적이 있다. 본 연구를 위해서 직장인을 대상으로 한 설문조사를 진행하였고, 최종적으로 340개의 유효한 설문지를 수집하였다. 수집된 자료는 인구통계학적 특성을 통제변인으로 하는 다중회귀분석을 진행하였고 학습지향성 조절효과는 조절회귀 분석을 실시하였다. 분석결과 기업가정신 중 성취 욕구와 진취성이 높을수록 업무몰입이 높아지는 것으로 나타났고 정보기술 수용성의 지각된 유용성과 미디어 활용역량의 커뮤니케이션 활용역량이 업무몰입에 정(+)의 영향을 미치는 것으로 나타났다. 학습 지향성의 조절 효과 분석 결과 기업가정신, 미디어 활용역량과 업무몰입 간에 학습 지향성의 조절 효과가 나타났다. 이러한 연구를 통해, 디지털 환경이 고도화된 스마트 정보사회에서 직장인의 업무몰입을 향상시키기 위해서는 진취성과 성취욕구, 정보기술에 대한 지각된 유용성, 온라인 커뮤니케이션 활용역량의 축적과 함께 학습지향성과의 시너지 효과를 적극적으로 모색해야 한다는 결론을 도출하였다.

  • PDF

커뮤니케이션매체 특성과 교수행위 특성이 협력적 상호작용과 프로젝트 성과에 미치는 영향 (The Impact of Characteristics of Communication Media and Instruction Behavior on Collaborative Interaction and Project Performance)

  • 고윤정;정경수;고일상
    • Asia pacific journal of information systems
    • /
    • 제18권4호
    • /
    • pp.83-103
    • /
    • 2008
  • In the new web based learning environment which has recently emerged, a variety of new learning objectives and teaching methods suited to this learning environment have been adopted. Recently, web based project-based learning methods have received a great deal of attention from those wishing to improve learning performance. The objective of this study is to identify the impact of characteristics of communication media and instruction behavior on collaborative interaction and project performance through web based group projects. The characteristics of communication media were divided into richness, flexibility, and ease of use, and the characteristics of instruction behavior were divided into support and expression, which are independent variables. Collaborative interaction as a mediate variable, was divided into information sharing and negotiation. Project performance was the dependent variable. To verify the proposed research model empirically, an experiment was conducted in which learners participated in on-line and off-line courses with group projects. The group project was conducted virtual product development(VPD), and designed a web-site about the VPD. At the end of the project, a survey was conducted. Of the 270 students, 239 responded. The students were assigned to groups of 3 or 4 members, and represented different genders and levels of computer competence. The reliability, validity, and correlation of research variables were analyzed using SPSS 14.0, and the measurement model and the structural goodness-of-fit of the research model were verified through SEM analysis using Lisrel 8.54. We found important results as follows; First, richness and ease of use has positive impacts on each of sharing information and negotiation. This suggests that richness and ease of use are useful in sharing information which is related to the task and agreeing in opinions among group members. However, flexibility has not positive impacts on sharing information and negotiation. This implies that there is no great difference in performance of PC and information literacy of user. Second, support and expression of instructor have positive impacts on sharing information and negotiation. This indicates that instructors play an important role in encouraging learners to participate in the project and communicating with them, sharing information related to the project, making a resonable decision and finally leading them to improve a project performance. Third, collaborative interaction has a positive impact on project performance. This result shows that if the ability to share information and negotiate among students was improved then a project performance would be improved as well. Recently, in the state of revitalized web based learning, it is opportune that web-based group project is practically conducted, and the impact of characteristics of communication media and characteristics of instruction behavior on sharing information, negotiating among group members and improving a project performance is verified. On the basis of these results, we propose that forms of learning, such as web based project, could be one of solution which is to enforce interaction among learners, and ultimately improve learning performance. Moreover web-based group project is able to make up for a weakness which makes it difficult to make interpersonal relations or friendship among learners in computer mediated communication or web based learning.

청각장애인의 수어 교육을 위한 MediaPipe 활용 수어 학습 보조 시스템 개발 (Development of a Sign Language Learning Assistance System using Mediapipe for Sign Language Education of Deaf-Mutility)

  • 김진영;심현
    • 한국전자통신학회논문지
    • /
    • 제16권6호
    • /
    • pp.1355-1362
    • /
    • 2021
  • 최근 선천적 청각장애 뿐만 아니라 후천적 요인으로 인해 청각장애를 가지게 되는 사람들도 증가하고 있지만, 수어를 익힐 수 있는 환경은 열악한 상황이다. 이에 본 연구에서는 수어를 배우는 수어 학습자를 위한 수어학습 보조도구로써 수어(지숫자/지문자) 평가 시스템을 제시하고자 한다. 이에 본 논문에서는 OpenCV 라이브러와 MediaPipe를 이용하여 손과 손가락을 추적하여 수어 동작을 인식하고 CNN기법을 이용하여 수어의 의미를 텍스트 형태의 데이터로 변환하여 학습자에게 제공하는 시스템을 연구한다. 이를 통해 수어를 배우는 학습자가 스스로 올바른 수형인지를 판단할 수 있도록 자기주도학습을 가능하게 하여 수어를 익히는데 도움이 되는 수어학습보조 시스템을 개발하고, 청각장애인들의 의사소통의 주언어인 수어학습을 지원하기 위한 방안으로 수어학습보조 시스템을 제안하는 데 목적이 있다.

스마트미디어 기반의 '닭의 한살이' 융합인재교육(STEAM) 수업이 초등학생의 학업성취도, 과학 탐구 능력 및 정의적 영역에 미치는 영향 (The Effects of Smart Media Based STEAM Program of 'Chicken Life Cycle' on Academic Achievement, Scientific Process Skills and Affective Domain of Elementary School Students)

  • 최영미;양지혜;홍승호
    • 한국초등과학교육학회지:초등과학교육
    • /
    • 제35권2호
    • /
    • pp.166-180
    • /
    • 2016
  • This paper examines the effects on academic achievement, scientific process skills and affective domain for elementary students learning the 'Chicken life cycle' through traditional science class versus a smart media based STEAM approach. Students designed and built a hatching jar and created a smart media content for chickens using time-lapse technology. This STEAM program was developed to improve their scientific concepts of animals over nine periods of classes using integrated education methods. The experimental study took place in the third grade of public schools in a province, with the STEAM approach applied in 2 classes (44 students) and the traditional discipline approach implemented in 2 classes (46 students). The STEAM education significantly influenced the improvement of academic achievements, basic scientific process skills and affective domain. The results suggest that this STEAM approach for teaching scientific concepts of animal life cycles has the performance in terms of knowledge, skills and affect gain achievements in elementary school students' learning when compared to a traditional approach. Moreover, the smart media based STEAM program is helpful to lead students to engage in integrated problem-solving designs and learning science and technology.

모바일 분노조절훈련 애플리케이션의 사용성 평가 연구 (Study on the Usability Evaluation of Mobile Anger Control Training Applications)

  • 유경한;강지안;최지은;조재희
    • 한국멀티미디어학회논문지
    • /
    • 제25권11호
    • /
    • pp.1621-1633
    • /
    • 2022
  • The present study aims to design an application for anger control training of individuals and test its practical usability with the goal of encouraging preventive training in daily life. This study also investigates, through usability evaluation, whether users can use the application to carry out the actual anger management training program, whether it is useful and convenient, and whether it produces adequate learning effects. In order to conduct usability evaluation, a usability evaluation scale comprised of six factors-utility, reuse intention, learning, error, and reflectivity-was derived, and survey items tailored to each factor were produced. The association between usability evaluation elements, user demographic parameters, mobile usage behavior, and state anger was also examined. The result demonstrated that additional menus and features are necessary to increase the usability of the application for anger management. The result also revealed that it is vital to build an intuitive application interface that users unfamiliar with mobile app functionality can easily navigate, as well as to add entertaining components in the content, as users may be somewhat bored. On the basis of the findings, ideas of modifying and creating anger management training programs were discussed.

Digital Forensic Investigation on Social Media Platforms: A Survey on Emerging Machine Learning Approaches

  • Abdullahi Aminu Kazaure;Aman Jantan;Mohd Najwadi Yusoff
    • Journal of Information Science Theory and Practice
    • /
    • 제12권1호
    • /
    • pp.39-59
    • /
    • 2024
  • An online social network is a platform that is continuously expanding, which enables groups of people to share their views and communicate with one another using the Internet. The social relations among members of the public are significantly improved because of this gesture. Despite these advantages and opportunities, criminals are continuing to broaden their attempts to exploit people by making use of techniques and approaches designed to undermine and exploit their victims for criminal activities. The field of digital forensics, on the other hand, has made significant progress in reducing the impact of this risk. Even though most of these digital forensic investigation techniques are carried out manually, most of these methods are not usually appropriate for use with online social networks due to their complexity, growth in data volumes, and technical issues that are present in these environments. In both civil and criminal cases, including sexual harassment, intellectual property theft, cyberstalking, online terrorism, and cyberbullying, forensic investigations on social media platforms have become more crucial. This study explores the use of machine learning techniques for addressing criminal incidents on social media platforms, particularly during forensic investigations. In addition, it outlines some of the difficulties encountered by forensic investigators while investigating crimes on social networking sites.

Link Stability aware Reinforcement Learning based Network Path Planning

  • Quach, Hong-Nam;Jo, Hyeonjun;Yeom, Sungwoong;Kim, Kyungbaek
    • 스마트미디어저널
    • /
    • 제11권5호
    • /
    • pp.82-90
    • /
    • 2022
  • Along with the growing popularity of 5G technology, providing flexible and personalized network services suitable for requirements of customers has also become a lucrative venture and business key for network service providers. Therefore, dynamic network provisioning is needed to help network service providers. Moreover, increasing user demand for network services meets specific requirements of users, including location, usage duration, and QoS. In this paper, a routing algorithm, which makes routing decisions using Reinforcement Learning (RL) based on the information about link stability, is proposed and called Link Stability aware Reinforcement Learning (LSRL) routing. To evaluate this algorithm, several mininet-based experiments with various network settings were conducted. As a result, it was observed that the proposed method accepts more requests through the evaluation than the past link annotated shorted path algorithm and it was demonstrated that the proposed approach is an appealing solution for dynamic network provisioning routing.

Deep reinforcement learning for base station switching scheme with federated LSTM-based traffic predictions

  • Hyebin Park;Seung Hyun Yoon
    • ETRI Journal
    • /
    • 제46권3호
    • /
    • pp.379-391
    • /
    • 2024
  • To meet increasing traffic requirements in mobile networks, small base stations (SBSs) are densely deployed, overlapping existing network architecture and increasing system capacity. However, densely deployed SBSs increase energy consumption and interference. Although these problems already exist because of densely deployed SBSs, even more SBSs are needed to meet increasing traffic demands. Hence, base station (BS) switching operations have been used to minimize energy consumption while guaranteeing quality-of-service (QoS) for users. In this study, to optimize energy efficiency, we propose the use of deep reinforcement learning (DRL) to create a BS switching operation strategy with a traffic prediction model. First, a federated long short-term memory (LSTM) model is introduced to predict user traffic demands from user trajectory information. Next, the DRL-based BS switching operation scheme determines the switching operations for the SBSs using the predicted traffic demand. Experimental results confirm that the proposed scheme outperforms existing approaches in terms of energy efficiency, signal-to-interference noise ratio, handover metrics, and prediction performance.