• 한국문헌정보학회지
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• 제48권3호
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• pp.193-215
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• 2014

본 연구는 간호학과 학생들의 그룹과제 시 협동적 정보행태에서 나타나는 만족도 및 정서적 경험 등을 설문조사하여 이들의 관계에 대해 종합적으로 분석해 보고자 하였다. 이를 위해 본 연구는 이용자들의 협동적 정보검색에서 나타나는 긍정적 또는 부정적 정서에 대한 평가는 동일 설문지에서 PANAS 척도를 이용하여 정서적 경험을 측정하였다. 학생들의 협동적 정보검색에 대한 경험은 정서적 측면과 상관관계를 살펴보고, 일반적 특성, 협동적 정보검색에 대한 경험, 정서적 측면과의 통계적 우의성은 t-test로 분석하였다. 연구결과, 간호학과 학생들의 협동적 정보검색과 정서적 경험은 상관관계가 있었으며, 또한 학생들의 일반적 특성, 협동적 정보검색과 정서적 경험은 통계적으로 유의미한 관계가 있는 것으로 나타났다. 특히 학생들의 성별과 '전반적 협동에 대한 만족도', 학생들의 성별과 긍정적 정서에서 유의미한 상관관계를 나타내었다. 본 연구를 통해서 협동적 정보행태에서 정서적 경험에 대한 후속 연구에 가능성을 발견하였다.

• 한국멀티미디어학회논문지
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• 제23권6호
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• pp.756-764
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• 2020

A typical algorithm used for image analysis is the Convolutional Neural Network(CNN). R-CNN, Fast R-CNN, Faster R-CNN, etc. have been studied to improve the performance of the CNN, but they essentially require large amounts of data and high algorithmic complexity., making them inappropriate for small and medium-sized services. Therefore, in this paper, the image label prediction algorithm based on CNN with collaborative layer with low complexity, high accuracy, and small amount of data was proposed. The proposed algorithm was designed to replace the part of the neural network that is performed to predict the final label in the existing deep learning algorithm by implementing collaborative filtering as a layer. It is expected that the proposed algorithm can contribute greatly to small and medium-sized content services that is unsuitable to apply the existing deep learning algorithm with high complexity and high server cost.

• 전자통신동향분석
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• 제37권6호
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• pp.32-42
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• 2022

Recently, decentralized approaches to artificial intelligence (AI) development, such as federated learning are drawing attention as AI development's cost and time inefficiency increase due to explosive data growth and rapid environmental changes. Collaborative AI technology that dynamically organizes collaborative groups between different agents to share data, knowledge, and experience and uses distributed resources to derive enhanced knowledge and analysis models through collaborative learning to solve given problems is an alternative to centralized AI. This article investigates and analyzes recent technologies and applications applicable to the research of multi-agent collaboration of AI bots, which can provide collaborative AI functionality autonomously.

• Asia pacific journal of information systems
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• 제18권4호
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• pp.83-103
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• 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.

• Educational Technology International
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• 제11권2호
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• pp.149-172
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• 2010

Knowledge can be more meaningful when it is shaped and personalized through interaction with others. Implementation of open learning environments such as open courseware or shared knowledge communities has gradually become more common. A case study which investigated instructors' experiences and perceptions of publishing and using open courseware in the classroom was conducted at a university in Korea. Responses from participating students and an evaluation group regarding how they perceived open learning environments were also examined. Based on the inductive analysis of the data, this study discusses advantages and challenges of publishing open courseware and collaborative learning environments. Also, practical guidelines for developing reusable learning materials are suggested.

• 정보기술응용연구
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• 제1권
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• 정보교육학회논문지
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• 제11권3호
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• pp.359-369
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• 2007

학습자가 학습을 시작하기 전 혹은 학습을 진행하는 동안 전문가의 정신모형을 제시하는 모형 중심 교수는 비전문 학습자의 문제해결 과정에 도움을 줄뿐만 아니라 학습의 과정을 용이하게 할 수 있다. 또한 협동학습 전략은 모형 중심 교수 이론을 적용하는 인지 도제 학습 모형의 여섯 단계 동안 비전문 학습자의 정신 모형을 정교하게 하고 반추하도록 하는데 큰 역할을 할 수 있다. 본 연구는 '컴퓨터교육'교과를 수강하는 교육대학교의 예비교사들의 교수설계 과정을 학습하는데 있어서 모형 중심 교수와 협동학습의 효과를 탐구하여 그 결과를 제시하였다.

• 대한안전경영과학회지
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• 제23권4호
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• 컴퓨터교육학회논문지
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• 제5권3호
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• pp.89-106
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• 2002

본 연구의 목적은 네트웍 기반 협력학습(CSCL)에서 학습자의 성찰을 지원하는 인지적 도구를 설계하는 주요전략과 도구의 구성요소를 탐색해 보는데 있다. CSCL에서는 실세계에서 직면하는 복잡한 문제를 해결하기 위한 방안으로 학습자가 다양한 관점에서 의견을 교환하고 협력하는 활동을 강조한다. 학습경험을 유의미한 의미생성과 지식구성으로 확장하기 위해서는 학습자의 성찰이 필수적이며, 따라서 학습자가 자신 또는 그룹의 학습과정과 결과를 지속적으로 모니터링할 수 있는 기제가 제공될 필요가 있다. 이에 본 연구에서는 학습자 성찰의 중요성을 이론적으로 탐색하고 네트웍 기반 성찰지원 도구에 대한 선행연구들을 분석하여 시사점을 도출하였다. 나아가 사회문화적 인지 이론을 토대로, 협력학습과정을 지원하고 그룹인지를 확장시킬 수 있도록 협력적 성찰지원 도구를 설계하였다. 구체적으로는 (1)학습자의 협력적 인식, (2)사고의 시각화, (3)대화(협상) 촉진, (4)메타타인지적 단서로 세분화하였으며, 성찰지원 도구의 구성요소로서 추석달기, 협력노트 및 메타인지 프롬프트 등의 적용을 제안하였다.

• 한국수학교육학회지시리즈A:수학교육
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• 제57권2호
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• pp.137-155
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• 2018

From the assumption that an individual's working memory capacity is limited, the cognitive load theory is concerned with providing adequate instructional design so as to avoid overloading the learner's working memory. Based on the cognitive load theory, this study aimed to provide implications for effective problem-based collaborative teaching and learning design by analyzing the level of middle school students' cognitive load which is perceived according to the problem types(short answer type, narrative type, project) in the process of collaborative problem solving in middle school function part. To do this, this study analyzed whether there is a relevant difference in the level of cognitive load for the problem type according to the math achievement level and gender in the process of cooperative problem solving. As a result, there was a relevant difference in the task burden and task difficulty perceived according to the types of problems in both first and second graders in middle schools students. and there was no significant difference in the cognitive effort. In addition, the efficacy of task performance differed between first and second graders. The significance of this study is as follows: in the process of collaborative problem solving learning, which is most frequently used in school classrooms, it examined students' cognitive load according to problem types in various aspects of grade, achievement level, and gender.