• 제목/요약/키워드: L2 Learning

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A Study on e-Learning Contents Quality (e-learning 컨텐츠 품질에 관한 연구)

  • Kim, Young-Ki;Park, Seong-Taek;Lee, Seung-Jun
    • Journal of Digital Convergence
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    • v.6 no.2
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    • pp.135-143
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    • 2008
  • The remarkable growth of the Internet since mid-l990s has expanded the e-learning market and brought the transformation of educational environments and methodology. It can be said that the e-learning has changed the educational paradigm. Korean government is firmly determined to support the diffusion of e-learning because of the benefits of e-learning. People seem to accept the e-learning when its contents have high quality. A lot of research have been conducted on e-learning, however, it was mostly about user's usage intention, satisfaction and educational effect. It can't seem that sufficient research efforts have been put into figuring out the role of e-learning contents quality in the expansion of e-learning. In this paper, we present the empirical study on the influence of e-learning contents quality on user's satisfaction and educational effect. We conducted an questionnaire survey on college students to collect data and found that the quality of e-learning contents has significant influence on the users' satisfaction.

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The effects of corpus-based vocabulary tasks on high school students' English vocabulary learning and attitude (코퍼스를 기반으로 한 어휘 과제가 고등학생의 영어 어휘 학습과 태도에 미치는 영향)

  • Lee, Hyun Jin;Lee, Eun-Joo
    • English Language & Literature Teaching
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    • v.16 no.4
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    • pp.239-265
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    • 2010
  • This study investigates the effects of corpus-based vocabulary tasks on the acquisition of English vocabulary in an attempt to explore the influence of corpus use on EFL pedagogy. For this to be realized, a total of 40 Korean high school students participated in the study over a 4-week period. An experimental group used a set of corpus-based tasks for vocabulary learning, whereas a control group carried out a traditional task (i.e., the L1-L2 translation) for vocabulary learning. To assess learning gains, the students were asked to complete the pre- and post-treatment tests measuring the word form, meaning, and use aspects of target lexical items. Results of the study indicate that in the experimental group the corpus-based vocabulary tasks were beneficial for the learning of word forms and use. In particular, corpus-based benefits were greatest in the low-proficiency EFL learners' collocational aspects of vocabulary use. On the other hand, in the control group, the traditional vocabulary tasks benefited the meaning aspects of target vocabulary items the most. In addition, survey results revealed that most students were positive about the corpus-based learning experience although some expressed reservations about the heavy cognitive load and the time-consuming nature of the analysis of corpus data primarily due to learners' lack of language proficiency.

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Effects of Daejo-hwan(Tatsao-wan) on L-NAME Induced Learning and Memory Impairment and on Cerebral Ischemic Damage of the Rats (L-NAME으로 유발된 학습.기억장애와 뇌허혈 손상에 관한 대조환의 효과)

  • 김근우;구병수
    • The Journal of Korean Medicine
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    • v.21 no.2
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    • pp.25-36
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    • 2000
  • Objectives : This study demonstrates the effects of Daejo-hwan on learning and memory impairment induced by L-NAME (75 mg/kg) treatment and on cerebral ischemic damage induced by middle cerebral artery (MCA) occlusion in rats. Methods : Daejo-hwan emulsion (73.3 mg/100 g/l ml) was administered to rats along a timed study schedule. The Moms water maze was used for learning and memory test of the rats. The MCA was occluded by using the intraluminal thread method. The brain slices were stained by 2 % triphenyl tetrazolium chloride (TTC) and 1 % cresyl violet solution. Infarct size, neuron cell number and size in penumbra was measured by using computer image analysis system. Results : 1. The escape latency of the Daejo-hwan treated group decreased significantly with respect to the control group. 2.The memory score of the Daejo-hwan treated group showed increase tendency, And the swimming distance was not different between the normal, the control, and the Daejo-hwan treated group. 3. The infarct size of the Daejo-hwan treated group decreased significantly with respect to the control group. 4. The total infarct volume of the Daejo-hwan treated group showed decrease tendency. And the brain edema index of the Daejo-hwan treated group decreased significantly with respect to the control group. 5. The neuron cell number and cell size in penumbra of the Daejo-hwan treated group increased significantly with respect to the control group. Conclusions : According to the above results, it is supposed that Daejo-hwan is clinically applicable to the vascular dementia.

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Feature Selection via Embedded Learning Based on Tangent Space Alignment for Microarray Data

  • Ye, Xiucai;Sakurai, Tetsuya
    • Journal of Computing Science and Engineering
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    • v.11 no.4
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    • pp.121-129
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    • 2017
  • Feature selection has been widely established as an efficient technique for microarray data analysis. Feature selection aims to search for the most important feature/gene subset of a given dataset according to its relevance to the current target. Unsupervised feature selection is considered to be challenging due to the lack of label information. In this paper, we propose a novel method for unsupervised feature selection, which incorporates embedded learning and $l_{2,1}-norm$ sparse regression into a framework to select genes in microarray data analysis. Local tangent space alignment is applied during embedded learning to preserve the local data structure. The $l_{2,1}-norm$ sparse regression acts as a constraint to aid in learning the gene weights correlatively, by which the proposed method optimizes for selecting the informative genes which better capture the interesting natural classes of samples. We provide an effective algorithm to solve the optimization problem in our method. Finally, to validate the efficacy of the proposed method, we evaluate the proposed method on real microarray gene expression datasets. The experimental results demonstrate that the proposed method obtains quite promising performance.

Effects of Corpus Use on Error Identification in L2 Writing

  • Yoshiho Satake
    • Asia Pacific Journal of Corpus Research
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    • v.4 no.1
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    • pp.61-71
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    • 2023
  • This study examines the effects of data-driven learning (DDL)-an approach employing corpora for inductive language pattern learning-on error identification in second language (L2) writing. The data consists of error identification instances from fifty-five participants, compared across different reference materials: the Corpus of Contemporary American English (COCA), dictionaries, and no use of reference materials. There are three significant findings. First, the use of COCA effectively identified collocational and form-related errors due to inductive inference drawn from multiple example sentences. Secondly, dictionaries were beneficial for identifying lexical errors, where providing meaning information was helpful. Finally, the participants often employed a strategic approach, identifying many simple errors without reference materials. However, while maximizing error identification, this strategy also led to mislabeling correct expressions as errors. The author has concluded that the strategic selection of reference materials can significantly enhance the effectiveness of error identification in L2 writing. The use of a corpus offers advantages such as easy access to target phrases and frequency information-features especially useful given that most errors were collocational and form-related. The findings suggest that teachers should guide learners to effectively use appropriate reference materials to identify errors based on error types.

Identifying Key Grammatical Errors of Japanese English as a Foreign Language Learners in a Learner Corpus: Toward Focused Grammar Instruction with Data-Driven Learning

  • Atsushi Mizumoto;Yoichi Watari
    • Asia Pacific Journal of Corpus Research
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    • v.4 no.1
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    • pp.25-42
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    • 2023
  • The number of studies on data-driven learning (DDL) has increased in recent years, and DDL's overall effectiveness as an L2 (second language) teaching methodology has been reported to be high. However, the degree of its effectiveness in grammar instruction, particularly for the goal of correcting errors in L2 writing, is still unclear. To provide guidelines for focused grammar instruction with DDL in the Japanese classroom setting, we aimed to identify the typical grammatical errors made by Japanese learners in the Cambridge Learner Corpus First Certificate in English (CLC FCE) dataset. The results revealed that three error types (nouns, articles, and prepositions) should be addressed in DDL grammar instruction for Japanese English as a foreign language (EFL) learners. In light of the findings, pedagogical implications and suggestions for future DDL research and practice are discussed.

Development of an integrated machine learning model for rheological behaviours and compressive strength prediction of self-compacting concrete incorporating environmental-friendly materials

  • Pouryan Hadi;KhodaBandehLou Ashkan;Hamidi Peyman;Ashrafzadeh Fedra
    • Structural Engineering and Mechanics
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    • v.86 no.2
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    • pp.181-195
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    • 2023
  • To predict the rheological behaviours along with the compressive strength of self-compacting concrete that incorporates environmentally friendly ingredients as cement substitutes, a comparative evaluation of machine learning methods is conducted. To model four parameters, slump flow diameter, L-box ratio, V-funnel time, as well as compressive strength at 28 days-a complete mix design dataset from available pieces of literature is gathered and used to construct the suggested machine learning standards, SVM, MARS, and Mp5-MT. Six input variables-the amount of binder, the percentage of SCMs, the proportion of water to the binder, the amount of fine and coarse aggregates, and the amount of superplasticizer are grouped in a particular pattern. For optimizing the hyper-parameters of the MARS model with the lowest possible prediction error, a gravitational search algorithm (GSA) is required. In terms of the correlation coefficient for modelling slump flow diameter, L-box ratio, V-funnel duration, and compressive strength, the prediction results showed that MARS combined with GSA could improve the accuracy of the solo MARS model with 1.35%, 11.1%, 2.3%, as well as 1.07%. By contrast, Mp5-MT often demonstrates greater identification capability and more accurate prediction in comparison to MARS-GSA, and it may be regarded as an efficient approach to forecasting the rheological behaviors and compressive strength of SCC in infrastructure practice.

Two Dimensional Slow Feature Discriminant Analysis via L2,1 Norm Minimization for Feature Extraction

  • Gu, Xingjian;Shu, Xiangbo;Ren, Shougang;Xu, Huanliang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3194-3216
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    • 2018
  • Slow Feature Discriminant Analysis (SFDA) is a supervised feature extraction method inspired by biological mechanism. In this paper, a novel method called Two Dimensional Slow Feature Discriminant Analysis via $L_{2,1}$ norm minimization ($2DSFDA-L_{2,1}$) is proposed. $2DSFDA-L_{2,1}$ integrates $L_{2,1}$ norm regularization and 2D statically uncorrelated constraint to extract discriminant feature. First, $L_{2,1}$ norm regularization can promote the projection matrix row-sparsity, which makes the feature selection and subspace learning simultaneously. Second, uncorrelated features of minimum redundancy are effective for classification. We define 2D statistically uncorrelated model that each row (or column) are independent. Third, we provide a feasible solution by transforming the proposed $L_{2,1}$ nonlinear model into a linear regression type. Additionally, $2DSFDA-L_{2,1}$ is extended to a bilateral projection version called $BSFDA-L_{2,1}$. The advantage of $BSFDA-L_{2,1}$ is that an image can be represented with much less coefficients. Experimental results on three face databases demonstrate that the proposed $2DSFDA-L_{2,1}/BSFDA-L_{2,1}$ can obtain competitive performance.

Learning from the L2 Expository Text

  • Kim, Jung-Tae
    • English Language & Literature Teaching
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    • v.10 no.3
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    • pp.21-40
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    • 2004
  • This study Questioned what happens in L2 reading comprehension of the expository text, as measured by recall and inference-making abilities, when a L2 reader was induced to develop a content schema about the topic of a target text, but the structure of that schema departs from the structure of the target text Seventy-four. Korean university students read either the same version text twice (consistent condition) or two different version texts (inconsistent condition) with a three-day interval between the two readings. The results of a verification test indicate that, for those subjects with higher L2 reading proficiency, the inconsistent condition was more beneficial than the consistent condition for the inference-making task. On the other hand, for lower-level L2 readers, the consistent condition was more favorable for the recall task. It was concluded that inducing a structurally inconsistent schema through an L2 pre-reading would be beneficial only when the reader's L2 linguistic ability is proficient enough to produce necessary propositions from the pre-reading.

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A Longitudinal Study of Korean Vowel Production by Chinese Learners of Korean (중국인 학습자가 발음한 한국어 단모음에 대한 종단 연구)

  • Kim, Jooyeon
    • Phonetics and Speech Sciences
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    • v.5 no.2
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    • pp.71-79
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    • 2013
  • This study provided longitudinal examination of the Chinese learners' acquisition of the Korean vowels. Specifically the author examined whether Korean monophthongs are acquired rapidly in early stages of learning (Flege, Munro and Skelton, 1992; Munro and Derwing, 2008) or they develop rather gradually in proportion to the learners' experience (Byee, 2001; Ellis, 2006). This study collected the Korean vowel production by 23 Chinese learners for a year, and then analysed F1 and F2 of each Korean vowel. The results showed that 1) Most of the second language (L2) vowels were rapidly improved during the first six or nine months of Korean learning before reaching the constant stage; and 2) The exact acquisition trajectories varied across the seven vowels. Specifically the vowels which were acquired in the early stage of learning were /i, e, ɨ/ for F1 and /ʌ, e, o, u/ for F2. Thus this study supports the hypothesis of Flege et al. (1992) and Munro and Derwing (2008) except the fact that each vowel showed the different learning route.