• Title/Summary/Keyword: active learning

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A Study on Integrating Digital Application into Foreign Language Education

  • An, Jeong-Whan;Lee, Su-Chul
    • International Journal of Contents
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    • v.12 no.1
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    • pp.54-59
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    • 2016
  • The purpose of this paper is to discover how the use of digital applications can affect students' attitudes toward positive classroom participation and performance in learning a foreign language. Participants of this study were 128 students who took a foreign language class at a high school in central Korea. To find out students' perceptions and attitudes toward the effect of using a digital application for their foreign language study, online questionnaire and focus-group interview were conducted. Our research findings revealed that these students could engage in active language learning and experience learning improvement while studying a foreign language with digital applications. The improvement was possible by creating more interactive activities and quizzes. In addition, the digital application provided students immediate feedback. It gave students and teachers various motivations beyond the traditional 'chalk and talk' format of text-only-classes. This study provides an overview of the usefulness of digital application. In addition, it provides understanding for students' perceptions and involvement using digital application in a foreign language classroom.

A Study on Incremental Learning Model for Naive Bayes Text Classifier (Naive Bayes 문서 분류기를 위한 점진적 학습 모델 연구)

  • 김제욱;김한준;이상구
    • The Journal of Information Technology and Database
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    • v.8 no.1
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    • pp.95-104
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    • 2001
  • In the text classification domain, labeling the training documents is an expensive process because it requires human expertise and is a tedious, time-consuming task. Therefore, it is important to reduce the manual labeling of training documents while improving the text classifier. Selective sampling, a form of active learning, reduces the number of training documents that needs to be labeled by examining the unlabeled documents and selecting the most informative ones for manual labeling. We apply this methodology to Naive Bayes, a text classifier renowned as a successful method in text classification. One of the most important issues in selective sampling is to determine the criterion when selecting the training documents from the large pool of unlabeled documents. In this paper, we propose two measures that would determine this criterion : the Mean Absolute Deviation (MAD) and the entropy measure. The experimental results, using Renters 21578 corpus, show that this proposed learning method improves Naive Bayes text classifier more than the existing ones.

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A self-learning rule-based assembly algorithm (자기학습 규칙베이스 조립알고리즘)

  • 박용길;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.1072-1077
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    • 1992
  • In ths paper a new active assembly algorithm for chamferless precision parts mating, is considered. The successful assembly task requires an extremely high position accuracy and a good knowledge of mating parts. However, conventional assembly mehtod alone makes it difficult to achieve satisfactory assembly performance because of the complexity and the uncertainties of the process and its environments such as imperfect knowledge of the parts being assembled as well as the limitation of the devices performing the assebled as well as the limitation of the devices performing the assembly. To cope with these problems, a self-learning rule-based assembly algorithm is proposed by intergaring fuzzy set theory and neural network. In this algortihm, fuzzy set theory copes with the complexity and the uncertainties of the assembly process, while neural network enhances the assembly schemen so as to learn fuzzy rules form experience and adapt to changes in environment of uncertainty and imprecision. The performance of the proposed assembly algorithm is evaluated through a series of experiments. The results show that the self-learning fuzzy assembly scheme can be effecitively applied to chamferless precision parts mating.

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Data selection method for Incremental learning using prior evaluation of data importance (데이터 중요도의 사전 평가를 이용한 증가학습을 위한 데이터 선택 방법)

  • 이선영;조성준;방승양
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.339-341
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    • 1998
  • 다층 퍼셉트론 학습은 학습 데이터의 능동적인 선택 여부에 따라 능동적 학습(Active learning)과 피동적 학습(Passive learning)으로 구분할 수 있다. 기존의 능동적 학습 방법들은 학습 데이터의 중요도를 측정할 수 있는 기준(measure)을 제시하고 이 기준에 따라 학습 데이터를 선택하는 방법을 취하고 있다. 이 방법들은 학습 데이터 선택을 위해 Hessian Approximation과 같은 복잡한 계산이나 학습 데이터를 선택하는 과정에 있어서 데이터의 중요도를 평가하기 위한 반복적인 계산을 필요로 한다. 본 논문에서는 학습 데이터 선택 시 반복적인 계산이 필요하지 않는 비교사 학습을 이용한 능동적 학습 데이터 선택 방법을 제안하고 그 수렴 특성과 일반화 성능을 분석한다. 또한 비교 실험을 통하여 제안된 방법이 기존의 능동적 학습방법보다 간단한 계산만으로 수렴 속도를 향상시키며 일반화에도 뒤떨어지지 않음을 보인다.

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Wavelet Neural Network Controller for AQM in a TCP Network: Adaptive Learning Rates Approach

  • Kim, Jae-Man;Park, Jin-Bae;Choi, Yoon-Ho
    • International Journal of Control, Automation, and Systems
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    • v.6 no.4
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    • pp.526-533
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    • 2008
  • We propose a wavelet neural network (WNN) control method for active queue management (AQM) in an end-to-end TCP network, which is trained by adaptive learning rates (ALRs). In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In our method, the WNN controller using ALRs is designed to overcome these problems. It adaptively controls the dropping probability of the packets and is trained by gradient-descent algorithm. We apply Lyapunov theorem to verify the stability of the WNN controller using ALRs. Simulations are carried out to demonstrate the effectiveness of the proposed method.

Enhancing Harmful Animal Recognition At Night Through Image Calibration (이미지 보정을 통한 야간의 유해 동물 인식률 향상)

  • Ha, Yeongseo;Shim, Jaechang;Kim, Joongsoo
    • Journal of Korea Multimedia Society
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    • v.24 no.10
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    • pp.1311-1318
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    • 2021
  • Agriculture is being damaged by harmful animals such as wild boars and water deer. It need to get permission to catch a wild boar and farmers are using a lot of methods to chase harmful animals. The methods through deep learning and image processing capture harmful animals with cameras. It is difficult to analyze harmful animals that are active at night. In this case, In this case, using deep learning by image correction can achieve a higher recognition rate.

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
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    • v.31
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    • pp.263-286
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    • 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.

The effects of active navigation on object recognition in virtual environments (자기주도 탐색(Active navigation)이 가상환경 내 대상재인에 미치는 효과)

  • Hahm, Jin-Sun;Chang, Ki-Won;Lee, Jang-Han;Lim, Seung-Lark;Lee, Kang-Hee;Kim, Sei-Young;Kim, Hyun-Taek
    • 한국HCI학회:학술대회논문집
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    • 2006.02b
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    • pp.633-638
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    • 2006
  • We investigated the importance and efficiency of active and passive exploration on the recognition of objects in a variety of virtual environments (VEs). In this study, 54 participants (19 males and 35 females) were randomly allocated into one of two navigation conditions (active and passive navigation). The 3D visual display was presented through HMD and participants used joysticks to navigate VEs. The VEs consisted of exploring four rooms (library, office, lounge, and conference room), each of which had 15 objects. 'Active navigation' was performed by allowing participants to self-pace and control their own navigation within a predetermined time limitation for each room. 'Passive navigation' was conducted by forced navigation of the four rooms in random order. Total navigation duration and objects for both navigations were identical. After navigating VEs, participants were asked to recognize the objects that had been in the four rooms. Recognition for objects was measured by response time and the percentage of correct, false, hit, and miss responses. Those in the active navigation condition had a significantly higher percentage of hit responses (t (52) = 4.000 p < 0.01), and a significantly lower percentage of miss responses (t (52) = -3.763, p < 0.01) in object recognition than those in the passive condition. These results suggest that active navigation plays an important role in spatial cognition as well as providing a better explanation about the efficiency of learning in a 3D-based program.

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A Study on the Difference between Balanced and Dominant Learning Styles and Learning Strategies by Learning Factors of College Students

  • Kim, Ji Sim;Kim, Kyong Ah;Park, Mi Soon;Ahn, You Jung;Oh, Suk;Jin, Myung Sook
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.8
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    • pp.65-73
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    • 2021
  • This study investigated differences in learning styles and learning strategies according to learning factors: major fields, achievements, and grades and differences in learning strategies according to learning styles for college students. Unlike previous studies that analyzed differences focused on the dominant learning style, the learning style was subdivided into a balanced and dominant learning style. In the analysis of the 179 participants in M colleges, it was found that the difference between the learning style and the learning strategy according to the learning factors was not significant. But, there was a significant difference in the use of cognitive strategies according to the learning style in the dimension of information input, and in the use of all strategies according to the information processing style. It was analyzed that active learners had a high level of using cognitive strategies, visual learners had a high level of using external strategies, and balanced learners had a high level of using internal strategies. Based on the results, the training strategies to understand the learning style and to improve the level of use of the learning strategy in the learning competency improvement program was proposed.

The Analysis of Learners' Perception of Mobile Learning Materials (모바일 학습 자료에 대한 학습자 인식 분석)

  • Han, Hyeong-Jong
    • The Journal of the Korea Contents Association
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    • v.20 no.3
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    • pp.452-461
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    • 2020
  • The purpose of this study is to identify how learners perceive mobile technology-based learning materials. For this purpose, two methods were utilized. Using multi-dimensional scale(MDS), it was identified that how learners perceive each type of learning materials using mobile technology. Through semantic differential scale(SDS), learners' perception of the difference between mobile learning materials and existing traditional learning materials was analyzed. As a result, learning materials using mobile technology were classified into as follows : the dimension of interaction with the content; the sense of presence. Learners perceived that mobile learning materials had characteristics of 'active', 'learner-centric', 'multi-sensory', and 'stimulating interest'. The significance of this study was to empirically and comprehensively investigate learners' perception for the characteristics of various mobile learning materials.