• 제목/요약/키워드: Learning capability

검색결과 685건 처리시간 0.025초

DEVELOPMENT AND APPLICATION OF FAILURE-BASED LEARNING MODEL FOR CONSTRUCTION TECHNOLOGY EDUCATION

  • Do-Yeop Lee;Cheol-Hwan Yoon;Chan-Sik Park
    • 국제학술발표논문집
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    • The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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    • pp.99-106
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    • 2011
  • Recent demands from construction industry have emphasized the capability for graduates to have improved skills both technical and non-technical such as problem solving, interpersonal communication. To satisfy these demands, problem-based learning that is an instructional method characterized by the use of real world problem has been adopted and has proven its effectiveness various disciplines. However, in spite of the importance of field senses and dealing with real problem, construction engineering education has generally focused on traditional lecture-oriented course. In order to improve limitations of current construction education and to satisfy recent demands from construction industry, this paper proposes a new educational approach that is Failure-Based Learning for using combination of the procedural characteristics of the problem-based learning theory in construction technology education utilizing failure information that has the educational value in the construction area by reinterpreting characteristics of construction industry and construction failure information. The major results of this study are summarized as follows. 1) Educational effect of problem-based learning methodology and limitation of application in construction area 2) The educational value of the information on construction failure and limitation in application of the information in construction sector 3) Anticipated effect from application of the failure-based learning 4) Development and application of the failure-based learning model

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지식확산에 의한 감염병 실험실의 자율적 생물안전관리 학습조직 설계 및 실행 (Design and Implementation of a Learning Organization for Autonomous Biosafety Management of Infectious Disease Laboratories by Knowledge Translation)

  • 신행섭;유민수
    • 한국환경보건학회지
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    • 제41권2호
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    • pp.102-115
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    • 2015
  • Objectives: A learning organization was designed and implemented on the basis of the selection criteria and essential elements of knowledge translation theory. Methods: The learning organization was designed on the basis of biosafety harmonization criteria and risk management strategy and was implemented as the learning organization for biosafety management by the National Institute of Health, Korea Centers for Disease Control & Prevention. The effect of knowledge translation in the research institutions by evidence-based policy was verified. Results: The result of applying the knowledge translation theory involving all stakeholders showed a positive reaction in establishing and implementing biosafety management strategy and embodied risk assessment criteria and evoked sympathy with the necessity of learning and using of expert knowledge about risk assessment and risk management. All stakeholders initiated voluntarily action toward new human-network construction and communication between similar organizations. The learning organization's capability expanded the base of knowledge translation. Conclusion: These results showed that a learning organization could enhance the autonomous safety management system by diffusion of knowledge translation.

Social Dimensions of Peer Interaction: Primary School Children Working with English Learning Software

  • Park, Heekyong
    • 한국영어학회지:영어학
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    • 제3권3호
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    • pp.453-497
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    • 2003
  • The purpose of this study is to investigate social aspects of young EFL learners' interaction at the computer. Data were taken from the interactions of three pairs of fourth-grade primary school children who worked together on English learning software. Their interactions at the computer were videotaped and then all the talk produced by the students and the utterances emitted from the computer were transcribed. As for the analytical tools, the notion of ‘contextualization cues’ (Gumperz, 1982) and the concept of ‘positioning’ (Davies & Harre,1990) were employed. The analysis reveals that the roles of the students were not tied to a certain position, but rather dynamically changed during the course of interactive work according to the situation at hand. The dynamic changes in their positions were realized through various means; their capability in solving problems, their taking responsibility or assigning it to each other, or cooperation. There were also instances of peer teaching and motivated learning. In addition, the students showed autonomy in their learning activity. These findings suggest that both students in a dyad had their own place in performing task activities, contributing to solving problems and getting benefits from peer interaction. Furthermore, students' working together on English learning software may provide an environment which can promote cooperative attitude and responsibility for learning and enhance motivation and autonomy in their learning process.

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역량 인식을 통한 대학생 학습지원 프로그램의 교육요구도 탐색 (Exploring the Educational Needs of Learning Supporting Program on the Students' Perception of Current Competencies and Important Competencies)

  • 엄미리;최원주;송윤희
    • 융합정보논문지
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    • 제8권3호
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    • pp.175-181
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    • 2018
  • 본 연구의 목적은 학습자 역량을 선별, 그 역량에 대한 중요도-수행도 인식 차이를 알아보고, 교육요구도를 분석하여 학습지원 프로그램의 방향성을 제고하고자 함이다. 설문도구를 활용하여 온라인 방식(이메일 발송)과 오프라인 방식(서면 설문)을 병행하여 수합된 159부를 최종 분석에 사용하였다. 기술통계, 대응표본 t-검정(paired t-test), Borich 공식을 활용한 교육요구도 분석을 실시하였다. 연구결과, 1) 3개 영역, 10개 역량별 역량 중요도와 역량 수행도 인식 차이에 있어 모두 유의미한 결과를 확인하였고, 2) Borich 공식을 활용하여 10개 역량별 전체 교육요구도를 살펴본 결과, '전공분야 지식'이 1순위, '창의성'이 2순위, '문제해결력'이 3순위, '글로벌 역량'이 4순위, '테크놀로지 역량'이 5순위 등의 순으로 나타났다. 본 연구결과는 대학생 학습지원 프로그램을 기획 설계하는 측면에서 고려해야 할 학습자의 역량과 교육요구도에 따른 주제의 우선순위를 결정하고, 실행 평가하는 측면에서 프로그램 효과성을 판단하는데 실제적 준거로 활용될 수 있을 것으로 기대한다.

하이브리드법에 의한 HMM-Net 분류기의 학습 (On Learning of HMM-Net Classifiers Using Hybrid Methods)

  • 김상운;신성효
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 추계종합학술대회 논문집
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    • pp.1273-1276
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    • 1998
  • The HMM-Net is an architecture for a neural network that implements a hidden Markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria used for learning HMM-Net classifiers are maximum likelihood (ML), maximum mutual information (MMI), and minimization of mean squared error(MMSE). In this paper we propose an efficient learning method of HMM-Net classifiers using hybrid criteria, ML/MMSE and MMI/MMSE, and report the results of an experimental study comparing the performance of HMM-Net classifiers trained by the gradient descent algorithm with the above criteria. Experimental results for the isolated numeric digits from /0/ to /9/ show that the performance of the proposed method is better than the others in the respects of learning and recognition rates.

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자기 학습 능력을 가진 퍼지 제어기를 이용한 차량의 속력 제어기 개발 (A SPEED CONTROLLER FOR VEHICLES USING FUZZY CONTROL ALGORITHM WITH SELF0LEARNING)

  • 정승현;김상우
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.880-883
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    • 1996
  • This paper suggests a speed control algorithm for the ICC(Intelligent Cruise Controller) system. The speed controller is designed using the fuzzy controller which shows the good performance in nonlinear system having the complex mathematical model. The fuzzy controller was equipped with the capability of a self-learning in real time in order to maintain the good performance of the speed controller in a time-varying environment the self-learning properties and the performance of the fuzzy controller are showed via computer simulation. The suggested fuzzy controller will be applied to the PRV-III which is our test vehicle.

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HMM-Net 분류기의 효율적인 학습법 (An efficient learning method of HMM-Net classifiers)

  • 김상운;김탁령
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.933-935
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    • 1998
  • The HMM-Net is an architecture for a neural network that implements a hidden markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria used for learning HMM-Net classifiers are maximum likelihood(ML) and minimization of mean squared error(MMSE). In this paper we propose an efficient learning method of HMM_Net classifiers using a ML-MMSE hybrid criterion and report the results of an experimental study comparing the performance of HMM_Net classifiers trained by the gradient descent algorithm with the above criteria. Experimental results for the isolated numeric digits from /0/ to /9/ show that the performance of the proposed method is better than the others in the repects of learning and recognition rates.

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효과적인 패턴분할 방법에 의한 하이브리드 다중 컴포넌트 신경망 설계 및 학습 (Hybrid multiple component neural netwrok design and learning by efficient pattern partitioning method)

  • 박찬호;이현수
    • 전자공학회논문지C
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    • 제34C권7호
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    • pp.70-81
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    • 1997
  • In this paper, we propose HMCNN(hybrid multiple component neural networks) that enhance performance of MCNN by adapting new pattern partitioning algorithm which can cluster many input patterns efficiently. Added neural network performs similar learning procedure that of kohonen network. But it dynamically determine it's number of output neurons using algorithms that decide self-organized number of clusters and patterns in a cluster. The proposed network can effectively be applied to problems of large data as well as huge networks size. As a sresutl, proposed pattern partitioning network can enhance performance results and solve weakness of MCNN like generalization capability. In addition, we can get more fast speed by performing parallel learning than that of other supervised learning networks.

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학습 가능한 실시간 다단위 신경 신호의 분류에 관한 연구 (Classification of Multi-Unit Neural Action Potential by Template Learning)

  • 김상돌;김경환;김성준
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 추계학술대회
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    • pp.99-102
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    • 1997
  • A neural spike sorting technique has been developed that also has the capability of template learning. A system of software has been written that first obtains the templates by learning, and then performs the sorting of the spikes into single units. The spike sorting can be done in real time. The template learning consists of spike detection based on the discrete Haar transform (DHT), feature extraction by clustering of spike amplitude and duration, classification based on rms error, and fabrication of templates. The developed algorithms can be implemented into real time systems using digital signal processors.

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기하문제해결에서의 GSP를 활용한 탐구학습 신장 (A experimental model of combining exploratory learning and geometry problem solving with GSP)

  • 전영국;주미
    • 대한수학교육학회지:수학교육학연구
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    • 제8권2호
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    • pp.605-620
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    • 1998
  • This paper suggested a geometry learning model which relates an exploratory learning model with GSP applications, Such a model adopts GSP's capability of visualizing dynamic geometric figures and exploratory learning method's advantages of discovering properties and relations of geometric problem proving and concepts associated with geometric inferencing of students. The research was conducted for 3 middle school students by applying the proposed model for 6times at computer laboratory. The overall procedure was videotaped so that the collected data was later analyzed by qualitative methodology. The analysis indicated that the students with less than van Hiele 4 level took advantages of adoption our proposed model to gain concrete understandings of geometric principles and concepts with GSP. One of the lessons learned from this study suggested that the roles of students and a teacher who want to employ the proposed model need to change their roles respectively.

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