• 컴퓨터교육학회논문지
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• 제7권3호
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• pp.111-121
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• 2004

협동학습 모델 중에서 매우 간단하고 적용이 쉬운 구조중심 협동학습은 다양한 구조의 유기적 연결과 학습내용의 결합을 통해 교수학습이 이루어진다. 본 연구에서는 이러한 구조중심의 협동학습을 위한 교수-학습 모델을 제안하고, 이를 지원하는 웹기반 구조중심 협동학습 시스템을 설계 및 구현하였다. 본 연구에서 제안하는 구조중심 협동학습 모델에서는 교과학습에 적용할 수 있는 구체적인 틀을 제시하여 협동학습을 효과적으로 지원할 수 있도록 하였다. 또한 학습 내용과 형태에 따라 다른 구조를 적용할 수 있도록 지식 습득형, 탐구형, 기능 숙달형 구조로 분류하고 이에 따른 적용 모형들을 제시하고 있다. 이러한 모형들을 기반으로 실제 협동학습을 수행할 수 있도록 시스템을 구현하여, 수업에 적용한 후 그 효과를 분석해 보았다.

• 한국정보통신학회논문지
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• 제19권1호
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• pp.35-40
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• 2015

본 논문은 유전 알고리즘 기반 귀납적 학습 환경 하에서 메타 학습법을 이용한 다중 분류기 시스템의 구축에 관한 것이다. 메타 학습법을 이용한 다중 분류기 시스템의 구축에서 분류기는 일반 분류기와 메타 분류기로 구성된다. 메타 분류기는 사례에 대한 일반 분류기의 분류 결과에 학습 알고리즘을 적용하여 얻어진다. 분류시스템의 의사 결정과정에서 메타 분류기의 역할은 일반 분류기의 분류 결과를 평가하여 최종 의사 결정 과정에의 참여 여부를 결정하는 것이다. 분류 시스템은 분류기의 분류 결과가 옳은 것으로 평가된 결과들만 취합하여 이를 바탕으로 최종 분류 결과를 도출해 낸다. 메타 학습법이 다중 분류기 시스템의 성능에 미치는 영향을 다수의 사례 집합을 이용하여 평가하였다.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.583-587
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• 2015

Scenario-based learning (SBL) has been used in a variety of training situations across different disciplines. Despite its seemly widespread use in construction management discipline, very few attempts have been made to explore its effectiveness and the respective students' learning experience. Using a survey research design, this study aims to investigate students' perceptions on SBL approach in construction management courses. The specific objectives are: (i) to identify the characteristics of a favourable SBL environment, and (ii) to explore the students' learning experience and effectiveness of the SBL approach. The results show that the four characteristics of a favourable SBL environment are: effective team formulation, constant engagement with lecturer, working in a group, and incorporation of motivational incentive for participation. The students really appreciated the opportunities to apply concepts learnt in the lectures in their SBL group work. Also, they perceived that the SBL approach is effective in developing their reflective and critical thinking skills, analytic and problem-solving skills and their ability to work as a team. These findings should facilitate more critical approaches to similar form of teaching methods.

• 지식경영연구
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• 제1권1호
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• pp.65-80
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• 2000

The main purpose of this study is to answer a question that how a company can be a learning organization producing useful knowledge by applying neuro-cybernetics approach. This approach borrows its working principles from the human body systems. The current study urges that the principles can be applied to build a learning organization. System 1 to 5, the core parts of neuro-cybernetics, are explained. And it is explored that how these systems can be designed for a company to be a learning organization. Limitations of the current study are discussed at the end of the paper.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.333-336
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• 1997

In this paper, we present a nonlinear dynamic controller for position tracking of brushless dc motors. In constructing the controller, a backstepping-type approach is used under the condition of full state information, while an adaptive controller is adopted for parameter uncertainty throughout the entire electromechanical system. The nonlinear dynamic controller using the adaptive learning technique approach is shown to drive the state variables of system to the desired ones asymptotically and whose effectiveness is also sown via computer simulation.

• Journal of the Korean Data and Information Science Society
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• 제12권2호
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• pp.83-93
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• 2001

We investigate a kernel approach to discriminant analysis for binary classification as a machine learning point of view. Our view of the kernel approach follows support vector method which is one of the most promising techniques in the area of machine learning. As usual discriminant analysis, the kernel method can discriminate an object most likely belongs to. Moreover, it has some advantage over discriminant analysis such as data compression and computing time.

• 정보기술과데이타베이스저널
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• 제4권1호
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• pp.65-77
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• 1997

This paper describes and effective teaching approach to an undergraduate database course. This research draws on practical experience based on the hands-on practice approach which leads students to develop a database application utilizing various tools. Students not only learn concepts, methodologies and tools of database technology in class and through online multimedia learning aids, but also practice how to integrate them through collaborative team projects. The course employs collaborative learning approach and multimedia and internet technologies. Students are encouraged to work collaboratively on assignments and projects and to learn independently through online multimedia learning aids.

• Asian Journal of Business Environment
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• 제7권4호
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• pp.17-25
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• 2017

Purpose - The purpose of this study is to present a framework for determining the most appropriate business model for e-learning. Research design, data, and methodology - The Electronics Branch of Azad University has been elected as a case study in this research. This study conducted using a descriptive method. The information was obtained using interviews with experts including managers, faculty and students at the Electronics Branch of Azad University. Results - Three service-product system (product oriented system, use an oriented and result oriented system) approaches determined a framework for the formation of a portfolio. This portfolio is including three types of e-learning business models. Examining the relevant characteristics, correspondence of behaviorism learning theory with a product-oriented approach, correspondence of cognitivism theory with a user-oriented approach and in finally match correspondence of constructivist learning theory with a results-oriented approach which is evident. Conclusions - After reviewing the literature on the fields of e-learning, business model and product - service systems, we have achieved three types of e-learning business models. Then the variables in any of the business models were defined by using business model canvas tool and thus a portfolio consisting of three types of e-learning business model canvas was obtained.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.214-222
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• 2021

Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

• 한국BIM학회 논문집
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• 제6권4호
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• pp.35-41
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• 2016

Learning effect is an observation that the more times a task is performed, the less time is required to produce the same amount of outcomes. The construction industry heavily relies on repeated tasks where the learning effect is an important measure to be used. However, most construction durations are calculated and applied in real projects without considering the learning effects in each of the repeated activities. This paper applied the learning effect to the repeated activities in a small sized apartment construction project. The result showed that there was about 10 percent of difference in duration (one approach of the total duration with learning effects in 41 days while the other without learning effect in 36.5 days). To make the comparison between the two approaches, a large number of BIM based computer simulations were generated and useful patterns were recognized using machine learning algorithm named Decision Tree (See5). Machine learning is a data-driven approach for pattern recognition based on observational evidence.