• Title/Summary/Keyword: Collaborative Learning System

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A Design of Web-Based Learning System Using Self Directed Collaborative Learning Model (자기 주도적인 협동학습 모형을 통한 웹(Web) 기반 학습시스템 설계 -초등학교 ICT 활용교육을 중심으로-)

  • 김효준;조세홍
    • Proceedings of the Korea Multimedia Society Conference
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    • 2001.11a
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    • pp.741-745
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    • 2001
  • 본 논문은 구성주의적 관점에서의 학습환경을 구축하기 위하여 설계·구현된 웹 기반 협동학습 시스템을 기술한다. 웹 상에서 인터넷을 통해 상호작용적인 의사소통을 촉진하고 자기 주도적 협동학습을 가능케 하기 위해 관리자, 그룹관리자, 학습자의 3가지 모듈을 구성·설계하였고, 과제와 평가 역시 서로 연동시킴으로써 보다 내실있는 시스템을 설계하였다. 따라서 본 연구는 현재 강조되고 있는 ICT(Information & Communication Technology) 찬용 교육에 있어 의다 효율적인 협동학습 공간을 구축하는 데 많은 도움을 줄 수 있을 것이다.

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Personalized Size Recommender System for Online Apparel Shopping: A Collaborative Filtering Approach

  • Dongwon Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.8
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    • pp.39-48
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    • 2023
  • This study was conducted to provide a solution to the problem of sizing errors occurring in online purchases due to discrepancies and non-standardization in clothing sizes. This paper discusses an implementation approach for a machine learning-based recommender system capable of providing personalized sizes to online consumers. We trained multiple validated collaborative filtering algorithms including Non-Negative Matrix Factorization (NMF), Singular Value Decomposition (SVD), k-Nearest Neighbors (KNN), and Co-Clustering using purchasing data derived from online commerce and compared their performance. As a result of the study, we were able to confirm that the NMF algorithm showed superior performance compared to other algorithms. Despite the characteristic of purchase data that includes multiple buyers using the same account, the proposed model demonstrated sufficient accuracy. The findings of this study are expected to contribute to reducing the return rate due to sizing errors and improving the customer experience on e-commerce platforms.

Development of a Web Platform System for Worker Protection using EEG Emotion Classification (뇌파 기반 감정 분류를 활용한 작업자 보호를 위한 웹 플랫폼 시스템 개발)

  • Ssang-Hee Seo
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.37-44
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    • 2023
  • As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

A U-CoMM System for Cooperative Learning (협동학습을 위한 U-CoMM 시스템)

  • Lee Byong-Rok;Ji Hong-Il;Shin Dong-Hwa;Cho Yong-Hwan;Lee Jun-Hee
    • The Journal of the Korea Contents Association
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    • v.6 no.3
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    • pp.116-124
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    • 2006
  • Mentoring is defined as a sustained relationship between a mentor and a mentee. Through continued involvement, the mentor offers support, guidance, and assistance as the mentee faces new challenges, or works to correct earlier problems. A mentoring for cooperative learning has many merits including higher order thinking, collaborative competencies, socialization and development. In this paper, a U(Ubiquitous)-CoMM(Community of mentor & mentee) system was supposed to design an instructional learning strategy using cyber community of mentor & mentee in a ubiquitous environment. The proposed system provides participants with campus mentoring program in which they share their experience and expertise. By experimental result showed that the proposed system is effect in education about cooperative learning than existing system.

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E-Learning System for collaborative Learning on Blogsphere (블로그 환경에서의 협업 학습을 위한 E-Learning 시스템)

  • Ha In-ay;Jung Jason J.;Jo Geun-Sik
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.11b
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    • pp.724-726
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    • 2005
  • 인터넷이 생활의 일부로 자리 잡은 최근 개인의 개성을 표출할 수 있는 블로그가 각광받고 있다. 본 논문에서는 이러한 블로그 환경에 교육계 분야에서 최근 화두가 되는 E-Learning을 접목시켜 각 개인의 블로그를 조직화하여 협업 학습을 할 수 있는 E-Learning 시스템을 제안한다. 현재 E-Learning 시스템들이 다양한 시도에도 불구하고, 아직은 학교 교육에 대한 과외 대체 교육에 머물고 있고 학습자 개개인에게 개별적인 학습 피드백을 제공하기 위해 많은 시간이 소요되며, 전통적인 교실 수업에 존재하는 사회적 교류를 제공하지 못하고 있다. 따라서 이 논문에서는 블로그 환경에서 학습자끼리의 코멘트에 의한 상호작용을 통해 자발적인 협업 학습 서비스를 제공하고자 한다.

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Ranking by Inductive Inference in Collaborative Filtering Systems (협력적 여과 시스템에서 귀납 추리를 이용한 순위 결정)

  • Ko, Su-Jeong
    • Journal of KIISE:Software and Applications
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    • v.37 no.9
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    • pp.659-668
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    • 2010
  • Collaborative filtering systems grasp behaviors for a new user and need new information for the user in order to recommend interesting items to the user. For the purpose of acquiring the information the collaborative filtering systems learn behaviors for users based on the previous data and can obtain new information from the results. In this paper, we propose an inductive inference method to obtain new information for users and rank items by using the new information in the proposed method. The proposed method clusters users into groups by learning users through NMF among inductive machine learning methods and selects the group features from the groups by using chi-square. Then, the method classifies a new user into a group by using the bayesian probability model as one of inductive inference methods based on the rating values for the new user and the features of groups. Finally, the method decides the ranks of items by applying the Rocchio algorithm to items with the missing values.

A Research about Cooperative Work System Using a Blog (블로그를 활용한 협력작업 시스템에 대한 연구)

  • Yun, Gyeong-Nam;Han, Seon-Gwan
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2007.05a
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    • pp.189-196
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    • 2007
  • 본 논문에서는 다인수 학급에서 한계를 나타내고 있는 교육현장에서의 협력작업을 학급 및 학생 개인별 블로그 운영을 통해 해결하는 방안을 제시한다. 이를 위해 우선 학급 홈페이지 등 기존 협력작업 웹사이트의 문제점을 분석하고, 도출된 문제점을 해결하기 위 한 블로 그의 기능과 특징 등 을 도입하여 보다 효율 적인 협력 작업 시스템을 설 계 및 구현하고자 한 다.

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Collaborative Reading Comprehension of Science Textbook via Students' Knowledge Sharing in an Online Annotation System (온라인 주석시스템에서 학생들의 지식공유를 통한 과학교과서의 협력적 독해 양상 분석)

  • Lee, Jiwon
    • Journal of The Korean Association For Science Education
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    • v.38 no.5
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    • pp.667-680
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    • 2018
  • The purpose of this study is to investigate 1) the types of knowledge students ask for in their reading comprehension of science textbooks using an online annotation system, 2) the accuracy of the knowledge provided by the students to their peers, 3) the frequency of knowledge sharing behaviors, 4) the evaluation of the effect of collaborative reading, and 5) the trust among peers as knowledge sharers. Questions made by 241 students in the second grade of middle school using an online annotation system in two chapters of the science textbook were analyzed using Bloom's revised taxonomy and their answers were grouped according to five accuracy categories. Also, questionnaires for the evaluation of the effectiveness of collaborative reading comprehension and of trust among the students were used. The students asked their peers 'understanding questions' which comprised almost 80% of the total questions they made and were similar with individual metacognitive strategies for reading comprehension. Of the total threads, 71% has scientifically correct threads shared by the students. The frequency of the knowledge sharing behaviors was high but this was affected by the rewards (point system). Students evaluated that collaborative reading comprehension conducted through an online annotation system were helpful in their learning. In addition, the ratio of students trusting their peers who did the knowledge sharing is over 80%. This study shows that when students use an online annotation system, they can fill one another's cognitive gaps in the reading process by sharing knowledge. Also, collaborative reading using an online annotation system has proved that cognitive individualization is possible through sharing knowledge interactively and dynamically, unlike reading hard copies of textbooks which are a one way information transfer.

Non-Curriculum Recommendation Techniques Using Collaborative Filtering for C University (협업 필터링을 활용한 비교과 프로그램 추천 기법: C대학 적용사례)

  • yujung Janu;Kyungeun Yang;Wan-Sup Cho
    • The Journal of Bigdata
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    • v.7 no.1
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    • pp.187-192
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    • 2022
  • Many schools are trying to improve students' competencies through many subjects and non-curricular activities, each students has different goals and different activities to prepare for employment. Accordingly, it is difficult to determine whether the programs offered in a comprehensive and comprehensive manner in the existing subject and non-curricular subjects systems are actually suitable for students, so it is necessary to introduce a personalized system. In this study, a method was proposed to classify non-departmental subjects that are uniformly provided to all students of Chungbuk National University by grade level and department. In addition, three types of collaborative filtering models are implemented using the evaluation score of students who participated in the non-curricular program, and personalized recommendations are proposed with the most accurate model by comparing performance.

A Delphi Study on Competencies of Mechanical Engineer and Education in the era of the Fourth Industrial Revolution (4차 산업혁명 시대 기계공학 분야 엔지니어에게 필요한 역량과 교육에 관한 델파이 연구)

  • Kang, So Yeon;Cho, Hyung Hee
    • Journal of Engineering Education Research
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    • v.23 no.3
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    • pp.49-58
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    • 2020
  • In the era of the fourth industrial revolution, the world is undergoing rapid social change. The purpose of this study is to predict the expected changes and necessary competencies and desired curriculum and teaching methods in the field of mechanical engineering in the near future. The research method was a Delphi study. It was conducted three times with 20 mechanical engineering experts. The results of the study are as follows: In the field of mechanical engineering, it will be increased the situational awareness by the use of measurement sensors, development of computer applications, flexibility and optimization by user's needs and mechanical equipment, and demand for robots equipped with AI. The mechanical engineer's career perspectives will be positive, but if it is stable, it will be a crisis. Therefore active response is needed. The competencies required in the field of mechanical engineering include collaborative skills, complex problem solving skills, self-directed learning skills, problem finding skills, creativity, communication skills, convergent thinking skills, and system engineering skills. The undergraduate curriculum to achieve above competencies includes four major dynamics, basic science, programming coding education, convergence education, data processing education, and cyber physical system education. Preferred mechanical engineering teaching methods include project-based learning, hands-on education, problem-based learning, team-based collaborative learning, experiment-based education, and software-assisted education. The mechanical engineering community and the government should be concerned about the education for mechanical engineers with the necessary competencies in the era of the 4th Industrial Revolution, which will make global competitiveness in the mechanical engineering fields.