• Title/Summary/Keyword: self-learning

Search Result 4,093, Processing Time 0.03 seconds

The Development of a Multimedia Courseware to Improve Middle School Students' Communicative Competence (중학생의 의사소통 능력 신장을 위한 멀티미디어 코스웨어 개발)

  • Sohng, Hae-Sung
    • English Language & Literature Teaching
    • /
    • v.8 no.1
    • /
    • pp.199-221
    • /
    • 2002
  • Multimedia-Assisted Language Learning(MALL) has recently been studied by many researchers. It has been reported that MALL is very effective in encouraging students' desire for learning, promoting their self-directed learning, and improving their communicative competence. Also, it has been evident that it depends on the quality of multimedia courseware whether MALL will be successful or not. However, many researchers have pointed out that most of multimedia coursewares coming into the market have little to do with our curriculum and they are not suitable for the use in the regular classroom. More multimedia coursewares that reflect our curriculum need to be developed. This paper first tries to explore the cognitive, constructivist, and psychological theories supportive of the development of multimedia courseware and then presents the overall procedure for designing and developing a multimedia courseware pursuant to the 7th English curriculum in the middle school. The multimedia courseware developed through this research is expected to enhance middle school students' communicative language skills in English and promote the development of multimedia coursewares of high quality.

  • PDF

Adaptive Control of the Nonlinear Systems Using Diagonal Recurrent Neural Networks (대각귀환 신경망을 이용한 비선형 적응 제어)

  • Ryoo, Dong-Wan;Lee, Young-Seog;Seo, Bo-Hyeok
    • Proceedings of the KIEE Conference
    • /
    • 1996.07b
    • /
    • pp.939-942
    • /
    • 1996
  • This paper presents a stable learning algorithm for diagonal recurrent neural network(DRNN). DRNN is applied to a problem of controlling nonlinear dynamical systems. A architecture of DRNN is a modified model of the Recurrent Neural Network(RNN) with one hidden layer, and the hidden layer is comprised of self-recurrent neurons. DRNN has considerably fewer weights than RNN. Since there is no interlinks amongs in the hidden layer. DRNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. To guarantee convergence and for faster learning, an adaptive learning rate is developed by using Lyapunov function. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed algorithm is demonstrated by computer simulation.

  • PDF

Reinforcement Learning with Small World Network (복잡계 네트워크를 이용한 강화 학습 구현)

  • 이승준;장병탁
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 2004.10a
    • /
    • pp.232-234
    • /
    • 2004
  • 강화 학습(Reinforcement Learning)을 실제 문제에 적용하는 데 있어 가장 큰 문제는 차원성의 저주(Curse of dimensionality)이다. 문제가 커짐에 따라 목적을 이루기 위해서 더 않은 단계의 판단이 필요하고 이에 따라 문제의 해결이 지수적으로 어려워지게 된다. 이를 해결하기 위칠 문제를 여러 단계로 나누어 단계별로 학습하는 계층적 강화 학습(Hierarchical Reinforcement Learning)이 제시된 바 있다. 하지만 대부분의 계층적 강화 학습 방법들은 사전에 문제의 구조를 아는 것을 전제로 하며 큰 사이즈의 문제를 간단히 표현할 방법을 제시하지 않는다. 따라서 이들 방법들도 실제적인 문제에 바로 적용하기에는 적합하지 않다. 이러한 문제점들을 해결하기 위해 복잡계 네트워크(Complex Network)가 갖는 작은 세상 성질(Small world Property)에 착안하여 자기조직화 하는 생장 네트워크(Self organizing growing network)를 기반으로 한 환경 표현 모델이 제안된 바 있다. 이러한 모델에서는 문제 크기가 커지더라도 네트워크의 사이즈가 크게 커지지 않기 때문에 문제의 난이도가 크기에 따라 크게 증가하지 않을 것을 기대할 수 있다. 본 논문에서는 이러한 환경 모델을 사용한 강화 학습 알고리즘을 구현하고 실험을 통하여 각 모델이 강화 학습의 문제 사이즈에 따른 성능에 끼치는 영향에 대해 알아보았다.

  • PDF

World Representation Using Complex Network for Reinforcement Learning (복잡계 네트워크를 이용한 강화 학습에서의 환경 표현)

  • 이승준;장병탁
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 2004.04b
    • /
    • pp.622-624
    • /
    • 2004
  • 강화 학습(Reinforcement Learning)을 실제 문제에 적용하는 데 있어 가장 큰 문제는 차원성의 저주(Curse of dimensionality)였다 문제가 커짐에 따라 목적을 이루기 위해서 더 많은 단계의 판단이 필요하고 이에 따라 문제의 해결이 지수적으로 어려워지게 된다. 이를 해결하기 위해 문제를 여러 단계로 나누어 단계별로 학습하는 계층적 강화 학습(Hierarchical Reinforcement Learning)이 제시된 바 있다 하지만 대부분의 계층적 강화 학습 방법들은 사전에 문제의 구조를 아는 것을 전제로 하며 큰 사이즈의 문제를 간단히 표현할 방법을 제시하지 않는다. 따라서 이들 방법들도 실제적인 문제에 바로 적용하기에는 적합하지 않다. 최근 이루어진 복잡계 네트워크(Complex Network)에 대한 연구에 착안하여 본 논문은 자기조직화하는 생장 네트워크(Self organizing growing network)를 기반으로 한 간단한 환경 표현 모델을 사용하는 강화 학습 알고리즘을 제안한다 네트웍은 복잡계 네트웍이 갖는 성질들을 유지하도록 자기 조직화되고, 노드들 간의 거리는 작은 세상 성질(Small World Property)에 따라 전체 네트웍의 큰 사이즈에 비해 짧게 유지된다. 즉 판단해야할 단계의 수가 적게 유지되기 때문에 이 방법으로 차원성의 저주를 피할 수 있다.

  • PDF

Design and Implementation of A Self-made learning Courseware for Learning data structure (자료구조 학습을 위한 자기 주도적 코스웨어 설계 및 구현)

  • 민경혜
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 2004.04b
    • /
    • pp.661-663
    • /
    • 2004
  • 본 연구는 웹상에서 학습자들에게 동영상(Flash Animation)학습과 심화학습(Feedback Learning)을 통하여 흥미롭고 자기 주도적으로 학습을 할 수 있도록 하여 홍미를 유발시키고 학습효과를 놓이고자 한다. 전체적으로 자료구조에 대한 기초적이고 전반적인 이론 학습 및 알고리즘 수행과정 실습을 할 수 있도록 하였으며 이해하기 힘든 학습내용을 단순한 텍스트 위주의 설명식 수업에서 탈피하여 자바스크립트 및 플래시 액션 기능을 활용한 코스웨어 상에서의 학습자 상호작용에 기반한 환경을 제공하였다 각 단위별로 기본 학습 밀 동영상 학습, 심화학습, 형성평가로 이루어져 있으며 , 학습화면 구성을 윈도우 운영체제 기본 환경과 유사하게 설정하여 학습에 흥미를 돋우고자 하였다.

  • PDF

A Study of Applying Jigsaw Model to Applied Mathematics (과제분담 협동학습을 응용수학에 적용한 사례 연구)

  • Nam, Hyewon
    • Journal of Engineering Education Research
    • /
    • v.22 no.5
    • /
    • pp.13-19
    • /
    • 2019
  • It is important to encourage students who are having difficulty learning mathematics and majors due to lack of basic knowledge, and encourage them to improve their academic performance by focusing on and participating in class. The purpose of this study is to confirm the applicability of the Jigsaw Method by analyzing the change of the learner's academic achievement and the attitude of the learner's mathematics by applying the Jigsaw Model. During the four weeks, the Jigsaw Model was applied to 30 experimental students and the instructor-led lectures were given to 36 students in the comparative group. As a result of the study, it was confirmed that the average of the experimental groups applying the Jigsaw model was higher than the average of the comparative group in the lecture class. The results of the survey showed that the Jigsaw Model increased class concentration and participation, helped self - directed learning, and had high learning satisfaction.

Application of the Podcasting in Korean Education -Aimed at Education for the Business School Students- (팟캐스팅의 한국어 교육 적용 사례 연구 -경영학 전공 학습자를 대상으로-)

  • Kim, Yu Mi;Park, Tong Kyu
    • Cross-Cultural Studies
    • /
    • v.31
    • /
    • pp.263-286
    • /
    • 2013
  • The goal of this study is to explore the possibility of applying the podcasting in Korean education for foreign students. To achieve this goal, concepts and applicability of the podcasting is discussed. Previous studies on foreign language education are reviewed and the cases on Korean language education based on technology using mobile phones are investigated. Some of the outstanding merits of the podcasting are found to be its accessibility, mobility and variability along with its room for control by the learners. It also enables the learners to be motivated and to enhance their learning ability. In addition, the podcasting with the content-based instruction is applied for the foreign students majoring in business and its results and implications are discussed. Based on the above results of this study, more active discussions are expected on such issues as educational designs through the podcasting, related variables and the performance evaluation.

Deep learning-based scalable and robust channel estimator for wireless cellular networks

  • Anseok Lee;Yongjin Kwon;Hanjun Park;Heesoo Lee
    • ETRI Journal
    • /
    • v.44 no.6
    • /
    • pp.915-924
    • /
    • 2022
  • In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.

Application Prototyping to Support Learning from Online Lectures on Building Construction (건축시공 온라인강의 학습지원용 애플리케이션 프로토타이핑)

  • Kim, Seong-Bin;Jo, Min-Jin;Kim, Jae-Yeob
    • Proceedings of the Korean Institute of Building Construction Conference
    • /
    • 2020.06a
    • /
    • pp.38-39
    • /
    • 2020
  • Currently, attempts are being made to introduce innovative teaching methods in architectural engineering education. However, there is still a lack of research supporting self-directed learners. In this regard, this study sought to develop an application prototype to support learning from online lectures on architectural engineering and conduct prototyping for its evolution. Menus in the application prototype consisted of four main categories: lecture operation, video lectures, eBooks and past exam questions. The lecture operation was classified into eight sub-categories, including assignment submission and notice, so as to support interactions between instructors and learners as well as confirmation of the delivery methods. With respect to video lectures, assignment submissions and notice functions, prototyping connecting the mobile web was implemented to enhance user convenience.

  • PDF

Construction and Validation of a Cognitive Presence Scale for Measuring Online Learners' Engagement

  • KANG, Myunghee;CHOI, Hyungshin
    • Educational Technology International
    • /
    • v.10 no.1
    • /
    • pp.41-57
    • /
    • 2009
  • Cognitive presence, a sense of "being there" cognitively, has recently been considered as an important indicator for students' engagement in e-learning. There is, however, no widely accepted scale to measure the level of cognitive presence since most studies have put their effort to set and clarify the conceptual framework with qualitative methodology. This study reviewed existing theories on cognitive presence and related fields extensively and developed a new self-report scale for measuring the conceived level of cognitive presence. The reliability and validity of the scale was tested against 723 undergraduate students in two consecutive studies, 418 in the preliminary and 305 in the follow-up study. Three major constructs to measure the perceived level of cognitive presence were: 1) clear understanding, 2) knowledge construction, and 3) learning management. This paper reports the final results of the two independent studies.