• 제목/요약/키워드: learning methods

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창의적 교수법 활용 사례: '국가 위협요인' 학습 과제 (A Case Study of Using Creative Teaching Methods: 'National Threats' Learning Task)

  • 백진욱;정주호
    • 문화기술의 융합
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    • 제9권2호
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    • pp.373-379
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    • 2023
  • 창의적 교수법은 수업에서 창의성과 자기주도학습 능력을 제고하는 데 도움이 된다. 그러나 일부 특정 학습 과제의 경우에는 창의적 교수법을 적용하기가 어려울 수 있다. 이는 학생들이 해당 학습 과제를 수행하기 전에 필요한 선행학습을 충분히 수행하지 않았기 때문이다. 따라서 이러한 경우에는 과제 결과물의 신뢰성이 낮거나 의미가 거의 없을 수 있다. 본 연구는 충분한 선행학습이 이루어지지 않을 수 있는 학습 과제를 수행할 때 창의성과 자기 주도적인 학습 능력을 향상하는 교수 방법을 제시하는 것이 목적이다. 이를 위해 본 논문에서는 '국가 위협요인'이라는 학습 과제에 창의적 교수법을 적용한 사례를 제시한다. 연구 절차로서, 해당 학습 과제에 적합한 교수법 모형과 세부 절차를 제시하고, 이를 실제 수업에서 적용한다. 본 연구를 통해, 해당 학습 과제에 제시한 교수법을 적용했을 때 의미 있는 결과물을 도출한 학업 성과가 있었다. 이번 연구는 창의성을 증진하기 위한 교육 분야 외에도 교육과 안보와 같은 융합 연구 분야에서도 유용하게 활용될 수 있다.

투자와 수출 및 환율의 고용에 대한 의사결정 나무, 랜덤 포레스트와 그래디언트 부스팅 머신러닝 모형 예측 (Investment, Export, and Exchange Rate on Prediction of Employment with Decision Tree, Random Forest, and Gradient Boosting Machine Learning Models)

  • 이재득
    • 무역학회지
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    • 제46권2호
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    • pp.281-299
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    • 2021
  • This paper analyzes the feasibility of using machine learning methods to forecast the employment. The machine learning methods, such as decision tree, artificial neural network, and ensemble models such as random forest and gradient boosting regression tree were used to forecast the employment in Busan regional economy. The following were the main findings of the comparison of their predictive abilities. First, the forecasting power of machine learning methods can predict the employment well. Second, the forecasting values for the employment by decision tree models appeared somewhat differently according to the depth of decision trees. Third, the predictive power of artificial neural network model, however, does not show the high predictive power. Fourth, the ensemble models such as random forest and gradient boosting regression tree model show the higher predictive power. Thus, since the machine learning method can accurately predict the employment, we need to improve the accuracy of forecasting employment with the use of machine learning methods.

기계학습 기반 강 구조물 지진응답 예측기법 (Machine Learning based Seismic Response Prediction Methods for Steel Frame Structures)

  • 이승혜;이재홍
    • 한국공간구조학회논문집
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    • 제24권2호
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    • pp.91-99
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    • 2024
  • In this paper, machine learning models were applied to predict the seismic response of steel frame structures. Both geometric and material nonlinearities were considered in the structural analysis, and nonlinear inelastic dynamic analysis was performed. The ground acceleration response of the El Centro earthquake was applied to obtain the displacement of the top floor, which was used as the dataset for the machine learning methods. Learning was performed using two methods: Decision Tree and Random Forest, and their efficiency was demonstrated through application to 2-story and 6-story 3-D steel frame structure examples.

A study on non-face-to-face 5AL teaching and learning method applying extended reality (XR)

  • Lee, Byong-Kwon;Lee, Kyoung-A
    • 한국컴퓨터정보학회논문지
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    • 제26권9호
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    • pp.125-132
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    • 2021
  • 코로나(COVD-19)로 인해 비대면 수업이 장기화하고 있는 시점에서 비대면 교수학습 방법에 관한 연구가 필요한 실정이다. 기존에 제시된 교수학습방법은 대면 형태의 실습 및 체험형 교수법을 제시하고 있어 비대면 수업에 적용하기에는 한계가 있다. 본 연구에서는 대학교육혁신원에서 선정된 교수학습 방법인 5AL(5Activity Learning) 교수법을 대상으로 확장현실(XR:eXtended Reality) 기술을 활용하는 방법을 제시한다. 5AL교수법은 문제중심학습(PBL Learning), 하브루타학습(Havruta Learning), 플립드학습(Flipped Learning), 스마트엑티비티학습(Smart Activity Learning) 및 게이미피케이션학습(Gamification Learning)으로 구성된다. 본 연구에서는 출시된 확장현실 콘텐츠를 5AL과 접목하는 방법을 제시했다. 또한, 5AL의 5가지 학습법을 통합한 콘텐츠를 개발하고 시험을 통해서 학습 효과를 확인했다.

진화 적응성을 이용한 신경망의 학습률 선택 (Off-line Selection of Learning Rate for Back-Propagation Neural Ntwork using Evolutionary Adaptation)

  • 김흥범;정성훈;김탁곤;박규호
    • 한국지능시스템학회논문지
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    • 제6권2호
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    • pp.52-56
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    • 1996
  • 신경망을 학습하는데 있어서, 망의 학습속도는 학습율에 의해 크게 좌우된다. 그러나 대부분의 정적인 학습율 선택 방법들은 몇몇 결정적인 방법들을 제외하곤 경험적인 방식에 의존해 왔다. 경험적인 방식을 사용하여 좋은 학습율을 찾아내는 것은 배우 지류하고 어려운 일이다. 또한 결정적인 방법들은 학습율의 질을 보장하지는 못한다. 본 논문에서 우리는 새로운 학습율 선택 방법을 제안한다. 우리의 방법은 진화 프로그래밍기법을 사용하여 통계적인 방식으로 접근함으로써 좋은 학습율을 찾을 수 있다. 모의 실험을 통하여 우리의 방식이 경험적인 방식들이나 결정적인 방식보다 우수함을 보였다.

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가정과 수업의 협동학습이 학생의 교과에 대한 흥미와 태도에 미치는 영향 (The Effect of Cooperative Learning method in Home Economics on students′Interest and Attitude about Subject matter)

  • 양정혜;신상옥
    • 한국가정과교육학회지
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    • 제10권1호
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    • pp.137-151
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    • 1998
  • The purpose of this study is (1)to develop the teaching plan based on Cooperative Learning approach and (2)to investigate the effect of students'Interest on Subject matter and Teaching method and Attitudes to others of the area of Foreign food in Home Economics class. Among those various types of Cooperative Learning's models, this study adopted 'Learning Together'developed by Johnsons. To investigate these purpose, subject matter were analyzed and reconstructed for Cooperative Learning. The tests were developed to evaluate the interest on the Subject matter and teaching methods, and the attitude to others of the students. 108 femail high school students were divided into two groups with 54 students-traditional learning condition, Cooperative Learning condition-and had a 5 session. The subject of the class was Foreign food including Western, Chinese, and Japanes food. Before and after the class, students were tested. The statistical methods used for the study methods used for the study were t-test. The research findings are as follows : When the students in the Cooperative Learning classes were compared before and after the test, (1)Interest on Subject matter were improved considerably(p〈.001) (2)Interest on Teaching methods were improved considerably(p〈.05) (3)Attitude to Others were improved considerably(p〈.001) Therefore when the teaching-learning model based on Cooperative Liarning was used in Home Economics class, their interest on the subject and teaching methods and attitude to others were improved.

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EPL 교육에서 연역적 및 귀납적 교수·학습방법 비교연구 (A comparative study of deductive and inductive teaching and learning methods for EPL education)

  • 박재연;마대성
    • 정보교육학회논문지
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    • 제22권5호
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    • pp.575-583
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    • 2018
  • 본 연구는 EPL학습을 문법 교수 학습방법인 연역적 교수 학습방법과 귀납적 교수 학습방법으로 접근했다. 엔트리 사이트에서 초등 5~6학년 학생을 대상으로 제공하는 강의를 연역적 학습과정으로 정했다. 이를 바탕으로 귀납적 학습 과정을 개발하고 각 학습과정을 12차시로 구성했다. 연구를 진행한 후 두 그룹 간 EPL 활용능력평가, 학습 만족도 및 몰입도 검사를 실시했다. 연구결과 두 그룹 간 통계적으로 의미 있는 결과를 얻기는 어려웠다. 하지만 세 가지 검사에서 귀납적 교수 학습방법을 적용한 그룹의 평균값이 모두 높았다. 학습과정을 장기적으로 구성하여 연구를 실행한다면 두 그룹 간 통계적으로 의미 있는 결과를 나태 낼 것으로 생각한다.

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.

딥러닝 기반 객체 인식 기술 동향 (Trends on Object Detection Techniques Based on Deep Learning)

  • 이진수;이상광;김대욱;홍승진;양성일
    • 전자통신동향분석
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    • 제33권4호
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    • pp.23-32
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    • 2018
  • Object detection is a challenging field in the visual understanding research area, detecting objects in visual scenes, and the location of such objects. It has recently been applied in various fields such as autonomous driving, image surveillance, and face recognition. In traditional methods of object detection, handcrafted features have been designed for overcoming various visual environments; however, they have a trade-off issue between accuracy and computational efficiency. Deep learning is a revolutionary paradigm in the machine-learning field. In addition, because deep-learning-based methods, particularly convolutional neural networks (CNNs), have outperformed conventional methods in terms of object detection, they have been studied in recent years. In this article, we provide a brief descriptive summary of several recent deep-learning methods for object detection and deep learning architectures. We also compare the performance of these methods and present a research guide of the object detection field.

창의성 증진을 위한 가정과 교수-학습에 관한 연구 (A Study on Teaching and Learning to Improve Creativity in Home Economics Education)

  • 권유진;신상옥
    • 한국가정과교육학회지
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    • 제10권2호
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    • pp.57-65
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    • 1998
  • The purpose of the study is to search for on teaching and learning to improve creativity in home economics education. It has been important for students to formulate and solve problems about home and family through creative thinking, home economics educators have to provide these teaching and learning methods. This research's methods were to search the importance of creativity in home economics education and the relevance between home economics and creativity, then to find the problems of some recent creativity education and formulate the assumption for creativity education in home economics education. Finally, it was presented the examples of teaching and learning to improve creativity. In above the process, we have to recognize as belows; 1. The teaching and learning methods in home economics education need the creativity for formulating problems and finding the elements which effect on practical problems. 2. It is properly selected to some teaching and learning methods in home economics education, and many methods to improve creativity may be included the assumptions for self-realization and moral responsibility.

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