• 제목/요약/키워드: Learning Model

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통합적 정신모형 이론에 기반한 4M 순환학습 수업모형 개발: 이론적 배경과 개발과정을 중심으로 (The Development of 4M Learning Cycle Teaching Model Based on the Integrated Mental Model Theory: Focusing on the Theoretical Basis & Development Procedure)

  • 박지연;이경호
    • 한국과학교육학회지
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    • 제28권5호
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    • pp.409-423
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    • 2008
  • 최근 과학교육 분야의 연구들에 의하면 학생들은 과학수업 시 다양한 어려움을 지각하며 수업 후에도 이러한 어려움이 잘 해소되지 않는다는 연구 결과가 보고되고 있다. 그러나 학생들이 느끼는 과학학습의 어려움과 그 원인을 조사하여 이를 해소시키기 위한 연구는 아직 부족한 실정이다. 따라서 학생들의 과학학습 어려움에 대한 체계적인 분석과 더불어 어려움을 해소하고 학습효과를 향상시킬 수 있는 새로운 수업모형 개발이 필요하다. 본 연구에서는 최근의 과학학습 과정에서 학생의 겪는 어려움과 기존 과학수업 모형에 관한 선행연구들을 조사하여, 이 결과를 통합적 정신모형이론 관점에서 분석하였다. 이러한 과정을 거쳐 과학학습 어려움 해소를 도울 수 있는 통합적 정신모형 이론에 기반한 4M 순환학습 수업모형을 개발하였다.

텐서플로우 튜토리얼 방식의 머신러닝 신규 모델 개발 : 캐글 타이타닉 데이터 셋을 중심으로 (Developing of New a Tensorflow Tutorial Model on Machine Learning : Focusing on the Kaggle Titanic Dataset)

  • 김동길;박용순;박래정;정태윤
    • 대한임베디드공학회논문지
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    • 제14권4호
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    • pp.207-218
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    • 2019
  • The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

양방향 인재매칭을 위한 BERT 기반의 전이학습 모델 (A BERT-based Transfer Learning Model for Bidirectional HR Matching)

  • 오소진;장문경;송희석
    • Journal of Information Technology Applications and Management
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    • 제28권4호
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    • pp.33-43
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    • 2021
  • While youth unemployment has recorded the lowest level since the global COVID-19 pandemic, SMEs(small and medium sized enterprises) are still struggling to fill vacancies. It is difficult for SMEs to find good candidates as well as for job seekers to find appropriate job offers due to information mismatch. To overcome information mismatch, this study proposes the fine-turning model for bidirectional HR matching based on a pre-learning language model called BERT(Bidirectional Encoder Representations from Transformers). The proposed model is capable to recommend job openings suitable for the applicant, or applicants appropriate for the job through sufficient pre-learning of terms including technical jargons. The results of the experiment demonstrate the superior performance of our model in terms of precision, recall, and f1-score compared to the existing content-based metric learning model. This study provides insights for developing practical models for job recommendations and offers suggestions for future research.

공과대학생들의 학습양식을 고려한 수학 교수-학습 모형 개발 및 적용 (Development and application of mathematics teaching-learning model considering learning styles of the students of engineering college)

  • 정수연;강윤수
    • 한국수학교육학회지시리즈E:수학교육논문집
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    • 제27권4호
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    • pp.407-428
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    • 2013
  • 본 연구는 공과대학생들의 수학 학습 능력 향상을 위한 효과적인 교수-학습 모형을 개발하고 활용 방안을 제안하는데 그 목적이 있다. 이를 위해, 교수-학습과정에서 중요한 변인으로 작용하는 학생들의 학습양식과 수학학습태도를 조사하여 둘 사이의 연관성을 분석하였다. 그 결과, 연구대상자들은 의존적이고 참여적인 성향이 강한 것으로 파악되었기 때문에, 이런 성향의 학습자들이 능동적이고 적극적으로 참여할 수 있는 교수-학습 모형을 개발하기 위해 노력하였다. 개발된 교수-학습 모형을 한 학기 공업수학 강좌에 적용한 후 학생들의 반응을 조사한 결과, 이 모형은 공과대학생들이 메타인지적으로 자기 학습과정을 진단하고 조정하는 능력을 향상시켜 자기주도적으로 학습하는데 도움이 될 수 있다는 것을 확인하였다. 또한, 학생들이 수업에 적극적으로 참여하고 수학 학습에 긍정적인 태도를 갖게 하는데도 영향을 미치는 것을 확인하였다.

클라우드 컴퓨팅 환경에서의 u-러닝 교수학습 모형 설계 (A Design of u-Learning's Teaching and Learning Model in the Cloud Computing Environment)

  • 정화영;김윤호
    • 한국항행학회논문지
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    • 제13권5호
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    • pp.781-786
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    • 2009
  • 클라우드 컴퓨팅 환경은 웹을 기반으로 한 응용분야의 새로운 트랜드이다. 이는 많은 사용자들이 쉽게 인터넷을 통해 자원을 할당받고 서비스를 지원받을 수 있는 IT 비즈니스 모델이라 할 수 있다. 또한 u-러닝은 인터넷 기반 학습의 효율성을 극대화한 모델이다. 따라서 본 연구는 이를 인터넷 기반 학습에 응용하는 u-러닝 교수 학습 모형의 설계를 제시하고자 한다. 제안된 교수 학습 모형은 u-러닝에 맞도록 준비, 계획, 수집, 학습 진행, 분석 및 평가, 피드백의 7단계로 구성하였다. 이는 클라우드 u-러닝 서버와 클라우드 LMS를 두어 처리 및 관리하도록 하였으며, 학습자의 이동형 기기 모델의 인식을 위하여 이동형 기기 메타데이터를 두도록 하였다.

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e-Learning 시스템의 성공요인에 대한 탐색적 연구 (Exploring the Success Factors of the e-Learning Systems)

  • 이문봉;김종원
    • 한국정보시스템학회지:정보시스템연구
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    • 제15권4호
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    • pp.171-188
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    • 2006
  • Information technology and the Internet have had a dramatic effect on education method and individual life. Universities and companies we making large investments in e-Learning applications but are hard to pressed to evaluate the success of their e-Learning systems. e-Learning can be seen as not only one of Internet based information systems which can provide education services but also one of teaching-teaming methods which can implement self-directed teaming. This paper tests the updated model of information system success proposed by Delone and McLean using a field study of a e-Learning. The five dimensions - information quality, system quality, service quality, user satisfaction, net benefit - of the updated model are parsimonious framework for organizing the e-learning success metrics identified in the literature. Questionaires are collected from 107 students who are enrolling a e-learning class using online survey. The model is tested using SPSS and LISREL. The results show that information quality and service quality are significant predictors of user satisfaction with the e-Learning system but system quality is not. Also user satisfaction is found to be a strong predictor of the learning performance. This strong association between user satisfaction and teaming performance suggests that user satisfaction may serve as a valid surrogate for teaming performance. Empirical testing of the updated DeLone & McLean model should therefore be extended to cover a wider variety of systems.

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근사 역모델에 의한 이산시간 학습제어기의 수렴성 개선에 관한 연구 (A Study on the Improvement of Convergence for a Discrete-time Learning Controller by Approximated Inverse Model)

  • 문명수;양해원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1989년도 하계종합학술대회 논문집
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    • pp.101-105
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    • 1989
  • The iterative learning controller makes the system output follow the desired output over a finite time interval through iterating trials. In this paper, first we discuss that the design problem of learning controller is originally the design problem of the inverse model. Then we show that the tracking error which is the difference between the desired output and the system output is reduced monotonically by properly modeled inverse system if the magnitude of the learning operator being introduced is bounded within the unit circle in complex domain. Also it would be shown that the conventional learning control method is a kind of extremely simplified inverse model learning control method of the objective controlled system. Hence this control method can be considered as a generalization of the conventional learning control method. The more a designer model the objective controlled system precisely, the better the performance of the approximated inverse model learning controller would be. Finally we compare the performance of the conventional learning control method with that of the approximated inverse model learning control method by computer simulation.

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A Co-Evolutionary Computing for Statistical Learning Theory

  • Jun Sung-Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제5권4호
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    • pp.281-285
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    • 2005
  • Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors. The global search of evolutionary computing in solution space can settle the local optima problems of learning models. In this research, combining co-evolving algorithm into statistical learning theory, we propose an co-evolutionary computing for statistical learning theory for overcoming local optima problems of statistical learning theory. We apply proposed model to classification and prediction problems of the learning. In the experimental results, we verify the improved performance of our model using the data sets from UCI machine learning repository and KDD Cup 2000.

A study on a model of intercultural learning contents and methods

  • Jong Youl Hong
    • 스마트미디어저널
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    • 제13권4호
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    • pp.104-113
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    • 2024
  • This study is a model study on the contents and methods of intercultural learning. Starting with a discussion of the intercultural learning model construct, it presents key contents important for intercultural learning and learning methods that can increase the effectiveness of intercultural learning. Also, we actually conducted the above learning program at the learning site and discussed the observations and results. It was a case study that allowed us to test the effectiveness of cultural intelligence theory, the latest theory that can improve intercultural competency. In addition, in order for the cultural intelligence theory to be effective in the learning process, it was found that the PBL method, which allows learners to solve problems on their own, rather than cramming education, is useful. Additionally, it was found that the ARCS model was also very effective in motivating and maintaining learners' continuous motivation. At this time, the instructor was also able to see that the effect increases when the role of catalyst becomes the main one.

Design and Implementation of a Content Model for m-Learning

  • Shon, Jin Gon;Kim, Byoung Wook
    • Journal of Information Processing Systems
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    • 제10권4호
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    • pp.543-554
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    • 2014
  • It is difficult for mobile learners to maintain a high level of concentration when learning content for more than an hour while they are on the move. Despite the attention span issue, many m-learning systems still provide their mobile learners with the same content once used in e-learning systems. This has called for an investigation to identify the suitable characteristics of the m-learning environment. With this in mind, we have conducted a survey in hopes of determining the requirements for developing more suitable m-learning content. Based on the results of the survey, we have developed a content model comprised of two types: a segment type and a supplement type. In addition, we have implemented a prototype system of the content model for Apple iPhones and Android smartphones in order to investigate a feasibility study of the model application.