• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2006년도 춘계 국제학술대회 논문집
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• pp.221-228
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• 2006

With the increasing use of the Internet improved Internet technologies as well as web-based applications, the effectiveness assessment of e-Learning has become one of the most practically and theoretically important issues in both Educational Engineering and Information Systems. This study suggests a research model, based on an e-Learning success model, the relationship of the e-learner's self-regulated learning strategy and the quality perception of the e-Learning environment. This research model focuses on the learning environment and on e-learning strategy. The former consists of learning management system, learning content quality and service quality that are provided by e-Loaming. The latter refers to the learners' self-regulated learning strategy. We will show the validity of the model empirically.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2004년도 춘계학술대회 21세기 IT산업의 발전 전망
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• pp.47-52
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• 2004

이 연구는 이미 편성되어 있는 초등학교 학급의 학생들을 연구 대상으로 학생들의 개인적 특성을 장 독립-장 의존 인지양식으로 분류하여 이에 따른 e-learning 시스템의 학습효과를 분석하기 위해 실험연구를 실시하였다. 연구결과 e-learning을 통한 학습은 인지양식에 따라 학습효과에 상이한 결과를 가져오기 때문에 e-learning 학습 컨텐츠 개발과정에서 보다 구체적으로 고려되어야 할 사항임을 시사하고 있다.

• 컴퓨터교육학회논문지
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• 제8권1호
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• pp.55-63
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• 2005

최근 공간적 시간적 제약을 초월하는 새로운 학습 환경으로 웹 기반 가상 학습 시스템이 각광을 받고 있다. 웹 기반 가상 학습 시스템 개발의 핵심은 어떻게 효과적으로 시스템을 사용하고 그 시스템을 사용한 학습자의 학습 성취도를 평가하도록 할 것인가를 결정하는 것이다. 전통적인 오프라인 학습 시스템에서는 학습자의 학습 성취도 평가를 위해 설계된 평가 문항을 학습자가 제한된 시간 내에 얼마나 많이 맞추었는지 헤아림으로써 학습자를 평가할 수 있다. 그러나 이 방법은 이들 시스템이 학습 성취도에서 차이를 보이는 모든 학습자에게 같은 학습 전략을 제공하기 때문에 가상 학습 시스템의 최대 강정이라고 할 수 있는 개별 학습을 불가능하게 한다, 따라서, 본 논문에서는 퍼지 함축 이론을 이용하여 주어진 테스트 문항에 대한 응답 간의 관계를 찾고 이 관계를 퍼지 공관계라고 부르기로 한다. 그리고 이 관계를 반영한 평가 결과를 생성한다. 일정한 학습이 경과된 후 학습자의 학습 성취도를 평가하기 위해 시험에 응시했을 때, 본 논문에서 제안하는 방법과 전통적인 평가 방법 간에 존재하는 차이점을 비교한다. 마지막으로, 이 연구 결과를 개별화 학습에 어떻게 활용할 것인지에 대해 논의한다.

• Journal of Information Technology Applications and Management
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• 제13권4호
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• pp.197-214
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• 2006

This study explores factors to facilitate web-based collaborative learning and the effect of learning, based on the PBL(Problem Based Learning) from the constructivist approach in e-learning. A research model, using the key variables such as situations, interactions, and systems, was developed. In order to test this proposed model, experimental design and post-survey was conducted to the learners who took on-line and off-line course with team project. In the research model, situation category was divided into instructor's support, unstructured problem, and self-directed learning. Interaction category was divided into three factors; 'interaction between learners', 'interaction between learner and instructor', and 'interaction between learner and technology'. System category was divided into.monitoring and incentives. As a result, it was found that collaborative learning can be improved by situations, interactions, and systems, and the effectiveness of learning can be improved by situations and interactions in PBL.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.138-141
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• 2003

Recently reinforcement learning has attracted attention of many researchers because of its simple and flexible learning ability for any environments. And so far many reinforcement learning methods have been proposed such as Q-learning, actor-critic, stochastic gradient ascent method and so on. The reinforcement learning system is able to adapt to changes of the environment because of the mutual action with it. However when the environment changes periodically, it is not able to adapt to its change well. In this paper we propose the reinforcement learning system that is able to adapt to periodical changes of the environment by introducing the time-varying parameters to be adjusted. It is shown that the proposed method works well through the simulation study of the maze problem with aisle that opens and closes periodically, although the conventional method with constant parameters to be adjusted does not works well in such environment.

• Asia pacific journal of information systems
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• 제6권2호
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• pp.77-105
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• 1996

The accuracy of knowledge is a major concern for expert system developers and users. Machine learning approaches have recently been found to be useful in knowledge acquisition for expert systems. However, the accuracy of concept acquired from machine learning could not be analyzed in most cases. In this paper we develop a comprehensive knowledge error analysis methodology for practical use of expert systems. Decision tree induction is an important type of machine learning method for business expert systems. Here we start to analyze with knowledge acquired from decision tree induction method, and extend the results to develop error analysis methodology for general machine learning methods. We give several examples and illustrations for these results. We also discuss the applicability of these results to multistrategy learning approaches.

• 동의생리병리학회지
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• 제30권6호
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• pp.412-418
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• 2016

The emergence of systems biology in the 21st century is changing the paradigm of biomedical research. Whereas the reductionist approaches focus on components rather than time or contexts, systems biology focus more on interrelationships, dynamics, and contexts. The key ideas of the systems biology shares much with the philosophy of Korean Medicine(KM) and therefore, the paradigm shift is shedding light on understanding the mechanism of action of KM at system level. In this article, I provide a guide to learning systems biology for KM researchers using online learning resources. Thanks to the recent development of MOOC(massive open online courses) and other online learning platforms, learners can access to plenty of high-quality resources from top-tier universities in the world. I expect this guide help researchers to employ systems biology methods into their KM researches, and will lead to the development of future curricula for training "bi-lingual" experts, KM and computational approaches.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1679-1686
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• 2007

In this paper, we introduce the sharable and reusable learning objects which are suitable for XML Web services in e-learning systems. These objects are extracted from the principles of pedagogical paradigms for reusable learning units. We call them LIO (Learning Item Object) objects. Existing models, such as Web-hosted and ASP-oriented service model, are difficult to cooperate and integrate among the different kinds of e-learning systems. So we developed the LIO objects that are suitable for XML Web services. The reusable units that are extracted from pedagogical paradigms are tutorial item, resource, case example, simulation, problems, test, discovery and discussion. And these units correspond to the LIO objects in our learning object model. As a result, the proposed model is that learner and instruction designer should increase the power of understanding about learning contents that are based on pedagogical paradigms. By using XML Web services, this guarantees the integration and interoperation of the different kinds of e-learning systems in distributed environments and so educational organizations can expect the cost reduction in constructing e-learning systems.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 1996년도 추계학술발표회 발표논문집
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• pp.217-227
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• 1996

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performin this specific task. In a previous work［6］, the authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification ad control. This paper develops improved indirect learning control algorithms, and studies the use of such controllers in decentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The basic result of the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample time in the digital learning controller is sufficiently short.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1996년도 추계 학술 발표회 발표논문집
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• pp.217-227
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• 1996

The new filed of learning control develops controllers that learn to improve their performance at executing a given task , based on experience performing this specific task. In a previous work[6], authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper develops improved indirect learning control algorithms, and studies the use of such controller indecentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an asssembly line. This paper starts with decentralized discrete time systems. and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The resultof the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample tie in the digital learning controller is sufficiently short.