• 지식경영연구
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• 제15권2호
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• pp.129-145
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• 2014

As a community of practice (CoP) is known to facilitate team learning, it is increasingly important to understand the mechanisms of CoP, thereby enabling organizations to fully utilize it and optimize its benefits. To explain how CoP improves organizational performance, we focus on its effects on social capital and knowledge management activities, and propose a research model suggesting that shared goals and trust in CoP improve its performance through knowledge integration. Our analysis uses structural equation modeling, with field data collected from 372 members of 46 CoPs in three companies; the analysis validates our research model. Our findings also suggest that CoP diversity can strengthen the link between knowledge integration and CoP performance.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.204-214
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• 2017

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

• Educational Technology International
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• 제11권2호
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• pp.25-41
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• 2010

Challenges brought by applications of advanced technologies in education call for new approaches that can best ensure the provision of quality e-learning experiences. This paper presents an ecological approach as one of such approaches to quality assurance in e-learning that can monitor, assess and improve the effectiveness and the links between the various elements of e-learning. The ecological model for QA in e-learning emphasizes interrelation transactions between elements (e.g. providers, learners, cultures and policies) and systemic integration of those elements, and stresses that all these elements within a QA system play an equal role in maintaining balance of the whole. The model focuses attention both on individual and societal/cultural environmental factors as cornerstones for QA efforts in e-learning. It addresses the importance of QA efforts directed at changing QA transactions from provider-centered to 'all stakeholder-oriented', from one-size-fits-all model to 'globally oriented, locally adaptive model' and from control framework to 'culture creation framework'.

• 한국과학교육학회지
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• 제21권2호
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• pp.357-384
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• 2001

본 논문에서는 통합과학교육에 관한 이론적 방향과 실제적 교수 학습방안을 연계성 있게 제시하여 과학교사들의 통합과학교육에 관한 이해를 도움과 동시에 통합과학 수업 보조자료를 개발하여 실제수업에 활용할 수 있도록 하였다. 이를 위해 공통과학 교과내용 중 통합 과학적 성격이 특히 강한 에너지 단원을 대상으로 통합과학 교수 학습 방안을 모색하였는데, 이것은 이전 논문에서 구성한 '통합과학교육의 방향별 에너지 교수 학습 전략' 을 바탕으로 하고 여기에 각 방향별 특징에 적합한 수업 모형을 적용한 것이다. 즉, 지식내용중심의 통합은 물리, 화학, 생물, 지구과학의 지식을 통합하기 위해서 '에너지의 여행' 을 주제로 선정하고 ' 개방된 발견학습' 수업모형을 적용하여 개념과 탐구관련 중심으로 모색하였다. 사회문제중심의 통합은 과학관련 사회문제를 해결하기 위하여 '에너지의 미래'를 주제로 선정하고 '발생학습' 수업모형을 적용하여 학습자의 인지과정을 중심으로 모색하였다. 개인흥미중심의 통합은 과학과 개인흥미의 통합을 위하여 '에너지의 변신' 을 주제로 선정하고 '프로젝트' 수업모형을 적용하여 학습자의 흥미나 관심분야를 중심으로 모색하였다. 이상과 같은 방향에 따른 통합과학 교수 학습 방안은 다음과 같은 순서에 의해 모색되었다. 먼저, 각 주제별로 다루어야할 통합과학적 교수 학습 내용을 구성하고, 이를 바탕으로 각각의 주제를 통합적으로 수업하기 위한 통합과학적 수업 절차를 설계하였다. 그리고 작성한 수업 절차에 따라 실제 통합과학 수업에서 적용할 수 있는 통합과학적 수업 지도안을 작성하였다. 이상의 연구는 21세기를 대비한 통합과학교육의 방향정립과 교재, 교사, 학생을 고려한 종합적인 통합과학교육 프로그램 개발에 활용될 수 있을 것으로 생각된다.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제19권3호
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• pp.177-193
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• 2015

Mathematical creativity, an important goal in mathematics education, can be promoted through an integrated learning environment where students explore mathematics with other subject areas such as science, technology, engineering and art. Establishing such learning environments is not a trivial task. Therefore, this creates a need for the development of instructional resources promoting meaningful integration. This paper focuses on integration of the fields of mathematics and music. Beginning with some of the historical discoveries and views of the connections between mathematics and music, this paper attends to several musical concepts correlating to middle school mathematical content and then provides ideas for teaching.

• 한국시스템다이내믹스연구
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• 제15권4호
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• pp.61-84
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• 2014

This study aims to explore the development and application of a simulated skills package designed to improve nursing students' knowledge integration and their system thinking(ST) skills about congestive heart failure(CHF) and to identify the change in students' ST levels using a ST-based learning approach. A simulated learning support package was developed by nurse educators and ST experts. The developed program was implemented with 35 third-year nursing students from S university in Seoul. The subjects improved their ST skills regarding CHF after intervention. Mean test scores for students completing the program were significantly higher than pre-intervention scores, including measures of direction of causality, polarity of causal relationship, feedback loop, polarity of feedback loop (reinforcing, balancing) and time delay (t=2.26~6.53, p=.030~p<.001). It is suggested that more educational programs be developed on various topics in order for nursing students to improve their ST skills as well as knowledge integration in clinical nursing practicum packages.

• Asia pacific journal of information systems
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• 제10권1호
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• pp.19-35
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• 2000

Data Envelopment Analysis(DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

• 한국수학교육학회지시리즈A:수학교육
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• 제53권3호
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• pp.435-447
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• 2014

Recently, the interdisciplinary integration and story-telling are often mentioned in mathematics education. It is probably because they might be helpful to students for positive attitude for mathematics. In this research, through brief discussion mathematics related with wallpaper patterns, we try to integrate mathematics and design, and eventually develop the teaching/learning materials for experience activities and story-telling.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2006년도 춘계 국제학술대회 논문집
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• pp.77-88
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• 2006

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

• 한국멀티미디어학회논문지
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• 제19권9호
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• pp.1659-1668
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• 2016

Understanding 3D structure of scenes is of a great interest in various vision-related tasks. In this paper, we present a unified approach for estimating depth from a single monocular image. The key idea of our approach is to take advantages both of parametric learning and non-parametric sampling method. Using a parametric convolutional network, our approach learns the relation of various monocular cues, which make a coarse global prediction. We also leverage the local prediction to refine the global prediction. It is practically estimated in a non-parametric framework. The integration of local and global predictions is accomplished by concatenating the feature maps of the global prediction with those from local ones. Experimental results demonstrate that the proposed method outperforms state-of-the-art methods both qualitatively and quantitatively.