• Title/Summary/Keyword: Learning tendency

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Teacher's corrective feedback: Focus on initiations to self-repair (학습자의 오류에 대한 교사의 오류 수정: 학습자 자기 교정 유도를 중심으로)

  • Kim, Young-Eun
    • English Language & Literature Teaching
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    • v.13 no.1
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    • pp.111-131
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    • 2007
  • This study explores teacher's corrective feedback types in an error treatment sequence in Korean EFL classroom setting. Corrective feedback moves are coded as explicit correction, recast, or initiations to self-repair. The frequency and distribution of each corrective feedback type are examined. But the special focus was given on feedback types eliciting learner's self-repair (clarification request, metalinguistic feedback, elicitation, and repetition of error) because initiations to self-repair are believed to facilitate language learning more than other strategies. The results of the study are as follows. First, there was an overwhelming tendency for teacher to use recasts whereas initiations to self-repair were not used as much as recast (52.4% vs. 29.5%). Second, the teacher tended to select feedback types in accordance with error types: namely, recasts after phonological, lexical, and translation errors and initiations to self-repair after grammatical errors though the differences were not significant. Finally, teacher's belief and students' expectation on corrective feedback were compared with actual corrective feedback representations respectively and some mismatches were found. Though both teacher and the students acknowledged the importance and necessity of self-repair, self-repair were not put into practice as such. Therefore, this study suggests more initiations to self-repair be used for effective language learning.

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Study on the Development of Diagnosis Algorithm for Induction Motor Using Current and Magnetic Flux Sensors (전류 및 자속센서를 이용한 유도전동기 예방진단 알고리즘 개발에 관한 연구)

  • Han, Sang-Bo
    • Journal of IKEEE
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    • v.23 no.4
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    • pp.1157-1165
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    • 2019
  • This paper discussed the results of the development and application of the machine learning algorithm to the induction motor for the preventive diagnostic system using current and magnetic flux signals. The optimal 29 features were extracted for identifying faulted types of induction motor. In particular, any load rate was derived using the tendency of the difference value from the center of the 7th harmonic frequency to the sideband of the current signal, and the corresponding classification accuracy showed about 84.6% by the KPCA feature reduction technique and the k-NN determination algorithm.

Noise Effects on Foreign Language Learning (소음이 외국어 학습에 미치는 영향)

  • Lim, Eun-Su;Kim, Hyun-Gi;Kim, Byung-Sam;Kim, Jong-Kyo
    • Speech Sciences
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    • v.6
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    • pp.197-217
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    • 1999
  • In a noisy class, the acoustic-phonetic features of the teacher and the perceptual features of learners are changed comparison with a quiet environment. Acoustical analyses were carried out on a set of French monosyllables consisting of 17 consonants and three vowel /a, e, i/, produced by 1 male speaker talking in quiet and in 50, 60 and 70 dB SPL of masking noise on headphone. The results of the acoustic analyses showed consistent differences in energy and formant center frequency amplitude of consonants and vowels, $F_1$ frequency of vowel and duration of voiceless stops suggesting the increase of vocal effort. The perceptual experiments in which 18 undergraduate female students learning French served as the subjects, were conducted in quiet and in 50, 60 dB of masking noise. The identification scores on consonants were higher in Lombard speech than in normal speech, suggesting that the speaker's vocal effort is useful to overcome the masking effect of noise. And, with increased noise level, the perceptual response to the French consonants given had a tendency to be complex and the subjective reaction score on the noise using the vocabulary representative of 'unpleasant' sensation to be higher. And, in the point of view on the L2(second language) acquisition, the influence of L1 (first language) on L2 examined in the perceptual result supports the interference theory.

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Learning Effects of SPACE Instructional Strategy on Children's Conceptual Change of Plants Growth (식물의 생장에 관한 아동들의 개념변화에 미치는 SPACE 수업전략과 효과)

  • Chung, Wan-Ho;Choi, Byung-Soon;Kim, Jeong-Ho
    • Journal of The Korean Association For Science Education
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    • v.13 no.3
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    • pp.327-333
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    • 1993
  • The purpose of this study was to investigate children's ideas about growth of plants and their conceptural change after instruction to apply SPACE (Science Processes And Concepts Exploration) Learning strategy. For this study, a total of 55 students from infants to 5th grade were sampled. Data were obtained by the individual interview procedure and summarized by using network analysis. The major results of this study were as follows : 1. A very small number of students responded reforming or reorganisation of materials about the mechanism of germination and growth inside the seeds. 2. Almost all students confused between conditions necessary for germination and growth. Water and sunlight were mentioned by many students, while air and temperature were mentioned by a few students as the condition. 3. Some of the students showed that growth occurs continuously. Many students explaned occurence of growth about Plants related to the night, monning, or evening. 4. With the explaning about the necessary conditions for caterpillar growth, students mentioned conditions related in terms of human experience. 5. Many young childrens showed tendency of the egocentric and human-centered view of the world. Students scientific concepts increased significantly with age. Many students conceptions depend on the context-specificity ideas.

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A Study on the Operation in Terms of Unit (단위 측면에서 연산에 관한 소고)

  • Roh, EunHwan;Kang, JeongGi;Jeong, SangTae
    • East Asian mathematical journal
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    • v.30 no.4
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    • pp.509-526
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    • 2014
  • The mathematics has moved toward the independence from unit. However, is this tendency also kept up in teaching and learning mathematics? This study starts from this question. We have illuminated this question in respects of a character of unit operation, an essential probability of unit operation and a didactical application of unit. As results, addition and subtraction are operations on identical objects and the result of operation does not also get out of operation's object. On the other hand, multiplication and division are operations on both identical objects and different objects. And the result of operation can generate new unit. We proposed a hypothesis which multiplication and division are transcendental operations from this analysis. The unit operation is not possible essentially. It seems only like unit operation is possible superficially by operational definition on unit. We could discuss on a didactical application of unit from above analysis. And we could deduct implications that the direction of developing mathematic does not necessarily match with the direction of teaching and learning mathematics.

Characterization of Premature Ventricular Contraction by K-Means Clustering Learning Algorithm with Mean-Reverting Heart Rate Variability Analysis (평균회귀 심박변이도의 K-평균 군집화 학습을 통한 심실조기수축 부정맥 신호의 특성분석)

  • Kim, Jeong-Hwan;Kim, Dong-Jun;Lee, Jeong-Whan;Kim, Kyeong-Seop
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.7
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    • pp.1072-1077
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    • 2017
  • Mean-reverting analysis refers to a way of estimating the underlining tendency after new data has evoked the variation in the equilibrium state. In this paper, we propose a new method to interpret the specular portraits of Premature Ventricular Contraction(PVC) arrhythmia by applying K-means unsupervised learning algorithm on electrocardiogram(ECG) data. Aiming at this purpose, we applied a mean-reverting model to analyse Heart Rate Variability(HRV) in terms of the modified poincare plot by considering PVC rhythm as the component of disrupting the homeostasis state. Based on our experimental tests on MIT-BIH ECG database, we can find the fact that the specular patterns portraited by K-means clustering on mean-reverting HRV data can be more clearly visible and the Euclidean metric can be used to identify the discrepancy between the normal sinus rhythm and PVC beats by the relative distance among cluster-centroids.

Pre-Service Secondary Mathematics Teachers' Modification of Derivative Tasks (중등 수학 예비교사의 미분계수 과제 변형)

  • Kim, Ha Lim;Lee, Kyeong-Hwa
    • School Mathematics
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    • v.18 no.3
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    • pp.711-731
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    • 2016
  • The purpose of this study is to investigate how pre-service secondary mathematics teachers modify mathematical tasks from a textbook and learning opportunities they have during the task modification. In the pursuit of this purpose, tasks was selected from derivative units in a textbook and five pre-service teachers was asked to modify the tasks. The findings from analysis are as follows. First, the cognitive demands of modified tasks were maintained or higher than those of the originals. Pre-service teachers' tendency toward conceptual understanding of derivative seems to make the result. Second, task modification provided a lot of learning opportunities for pre-service teachers. They tried to know intention of curriculum and textbook, realized the importance of predicting students' responses, and had opportunities for cooperation and reflective thinking.

Cross-Domain Text Sentiment Classification Method Based on the CNN-BiLSTM-TE Model

  • Zeng, Yuyang;Zhang, Ruirui;Yang, Liang;Song, Sujuan
    • Journal of Information Processing Systems
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    • v.17 no.4
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    • pp.818-833
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    • 2021
  • To address the problems of low precision rate, insufficient feature extraction, and poor contextual ability in existing text sentiment analysis methods, a mixed model account of a CNN-BiLSTM-TE (convolutional neural network, bidirectional long short-term memory, and topic extraction) model was proposed. First, Chinese text data was converted into vectors through the method of transfer learning by Word2Vec. Second, local features were extracted by the CNN model. Then, contextual information was extracted by the BiLSTM neural network and the emotional tendency was obtained using softmax. Finally, topics were extracted by the term frequency-inverse document frequency and K-means. Compared with the CNN, BiLSTM, and gate recurrent unit (GRU) models, the CNN-BiLSTM-TE model's F1-score was higher than other models by 0.0147, 0.006, and 0.0052, respectively. Then compared with CNN-LSTM, LSTM-CNN, and BiLSTM-CNN models, the F1-score was higher by 0.0071, 0.0038, and 0.0049, respectively. Experimental results showed that the CNN-BiLSTM-TE model can effectively improve various indicators in application. Lastly, performed scalability verification through a takeaway dataset, which has great value in practical applications.

Development of Flow Visualization Device with Smoke Generator in Learning Wind Tunnel (학습용 풍동의 연기 유동가시화 장치 개발)

  • Lim, Chang-Su;Choi, Jun-Seop
    • 대한공업교육학회지
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    • v.32 no.2
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    • pp.87-103
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    • 2007
  • The purpose of this study was to develop of the smoke flow visualization device of learning wind tunnel, teaching-learning materials in order to demonstrate air-flow around the fluid-flow field qualitatively and understand the resistance concepts of fluid-flow in secondary school. The contents of this study were consisted of the development and experiment of smoke flow visualization for learning wind tunnel. The main results of this study were as follows: First, this developed teaching-learning material here will help students understand the fundamental physical phenomena related with the resistance of fluid and the various patterns of air-flow in the field of transportation technology. Second, flow visualization has shown the same tendency in both of theoretical and experimental patterns. Third, the airfoil model has the smallest wake region meaning resistance against air-flow of circular cylinder and square rod model. Forth, flow separation point at leading edge and wide wake region began to show under the angle of attack of airfoil model ${\alpha}$ is $20^{\circ}$. Fifth, the wake width of the flow field behind a golf ball with dimple became slightly narrower than that without dimple. Sixth, the developed device was made to apply the teaching and learning materials for the experiment and practice in order to increase students' interest and attitude.

Exploring Collaborative Learning Dynamics in Science Classes Using Google Docs: An Epistemic Network Analysis of Student Discourse (공유 문서를 활용한 과학 수업에서 나타난 학생 담화의 특징 -인식 네트워크 분석(ENA)의 활용-)

  • Eunhye Shin
    • Journal of The Korean Association For Science Education
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    • v.44 no.1
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    • pp.77-86
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    • 2024
  • This study analyzed students' discourse and learning to investigate the impact of using Google Docs in science classes. The researcher, who is also a science teacher, conducted classes for 49 second-year middle school students. The classes included one using Google Docs and another using traditional paper worksheets covering identical content. Students' discourse collected from each class was compared and analyzed using Epistemic Network Analysis (ENA). The findings indicated that in the class using Google Docs, the proportion of discourse related to task was higher compared to the traditional class. More specifically, discourse regarding taking and uploading photos was prominent. However, such discourse did not lead to peer learning as intended by the teacher. An analysis based on achievement levels revealed that the class utilizing Google Docs had a relatively higher proportion of discourse from lower-achieving students. Additionally, differences were observed in the types of utterances and connection structures between the higher and lower-achieving students. The higher-achieving students took a leading role in providing suggestions and explanations, while the lower-achieving students played a role in transcribing them, with this tendency being more pronounced in the class using Google Docs. Lastly, students' changes in perception regarding the cause of static electricity were visualized using ENA. Based on the research findings, this study proposes strategies to enhance collaborative learning using Google Docs, including the use of open-ended problems to allow diverse opinions and outputs, and exploring the potential use of ENA to assess the learning effects of conceptual learning.