• English Language & Literature Teaching
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• v.9 no.2
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• pp.213-241
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• 2003

As an attempt to characterize the English test section of CSAT (College Scholastic Ability Test) and to get some suggestions, this study raised the research questions, as 'What are the main factors that affect students' English test scores in CSAT, and how big influences do they have?' It has been hypothesized that among main factors are the L1 competence, represented by the Korean test scores in CSAT, background knowledge or intelligence, represented by the "total" scores in CSAT, and the two types of L2 knowledge (vocabulary and grammar on one hand and prosody m the other hand), measured by the test devised specially for this study. The individual effect of the L2 vocabulary and grammar (one kind of L2 knowledge) was 70%, that of background knowledge or intelligence 61%, that of the L1 competence 50%, and that of the L2 prosody knowledge (the other kind of L2 knowledge) 32%. According to the stepwise regression, the whole effect of these four factors was 74%. The findings suggest that first, although CSAT is based on the top-down model of comprehension, the bottom-up model of learning should be more emphasized in our English class. Also, since background knowledge or intelligence is the second most influential factor, the top-down model of learning that helps students learn to understand by activating their various schemata must also be very effective.

• English Language & Literature Teaching
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• v.12 no.3
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• pp.1-24
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• 2006

This study investigated differences in beliefs about English learning of 286 EFL college students and 52 English teachers in Korea. Data was collected using Horwitz's Beliefs About Language Learning Inventory and compared between students and teachers in beliefs. To address the research questions, the data were analyzed through descriptive statistics including frequencies, factor analysis, MANOVA, ANOVA, t-test, and reliability coefficients. The results showed four factors in student beliefs: Difficulty of learning English, nature of learning English, importance of correctness in learning English, and motivation and perceived importance of learning English. Clear differences were found in students and teachers' beliefs in English learning aptitude and importance of translation, error correction, and grammar rules. A few belief differences were also identified between Koreans and native-speaking English teachers related to the importance of vocabulary learning, pronunciation, and cultural knowledge. The findings of the study indicated that background variables such as gender and major field of study have an effect on student beliefs about L2 learning. The present study also provided pedagogical considerations to reduce mismatch between students and teachers beliefs and to improve the L2 planning and instruction.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.150-157
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• 2014

This thesis intends to grasp the degree of utilization of visual images by understanding the relational properties between picture and letter and considering the children as users, through the analysis of currently published books of English vocabulary for children. Accordingly, the types of picture used in the books of English vocabulary for children, the degree of utilization of picture, combination types of picture and letter, and semantic consistency of picture and letter are reviewed. As a result of analysis, the degree of utilization of picture is high in general, in order of illustration, cartoon, and the mix of illustration and cartoon. In the combination form of picture and letter, the degree of utilization appears in order of picture plus vocabulary, letters without illustration, and pictorial symbol. In particular, the higher semantic consistency of picture and letter, it is effective in learning, however, semantic consistency is low, generally. Pictorial symbol type shows the frequency of the highest combination type in the five groups of higher semantic consistency. In conclusion, the presented types of picture and letter, shown in the currently published books of English vocabulary for children, are similar types by the publishing companies, thus, effective design research should be required based on diverse levels of children.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.165-172
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• 2010

There are two method of error correction in vocabulary recognition system. one error pattern matting base on method other vocabulary mean pattern base on method. They are a failure while semantic of key-word problem for error correction. In improving, in this paper is propose system of key-word error correction using algorithm of syllable restoration. System of key-word error correction by processing of semantic parse through recognized phoneme meaning. It's performed restore by algorithm of syllable restoration phoneme apply fluctuation before word. It's definitely parse of key-word and reduced of unrecognized. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.3% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• Educational Technology International
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• v.21 no.2
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• pp.155-191
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• 2020

The aim of this study was to examine the trends (e.g., the distribution of the studies by year, country, research methods, and participants' education level) and fundamental findings [e.g., interaction in Virtual Reality (VR) environments, educational content through VR and Augmented Reality (AR) technologies, learning environment in AR, etc.] regarding immersive learning technologies such as VR and AR in English Language Teaching (ELT) between 2010 and 2019. Employing a systematic review research methodology, data was gathered from 59 academic articles published in the following databases: EBSCOhost, ERIC, Web of Science, and Taylor & Francis. The studies were analyzed using a content analysis approach, and findings demonstrated that immersive learning technologies in ELT came to prominence in 2017. Mixed methods research was the most widely employed research method. The most studied language skill was vocabulary for AR and speaking for VR. The results also revealed advantages and challenges with regards to the use of immersive learning technologies in ELT. Further analysis illustrated the findings related to characteristics of immersive learning technologies in ELT. Based on this review, research and design implications for researchers and practitioners are presented.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.209-217
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• 2006

For its maximum impact on the scene of school as the educational equipment, it is necessary to understand equipmental characteristics of PDA and study the basis for utilizing it educationally. In this point of view, to inquire how PDA is helpful for education more than PC, the typical educational equipment in the past, PDA-based English vocabulary learning game is developed in this study, and after that it is applied on the scene of education. The result of study showed PDA can access the content more easily than PC, and learners expressed more curiosity and expectation of PDA than PC in a recent poll. In addition, under the condition of learner's voluntary use, the present study has found that learning with PDA is helpful to enhance the academic achievement more than one with PC.

• Journal of the Korean Society of Costume
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• v.54 no.4
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• pp.97-111
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• 2004

To study the clothing names has been one of the research subjects in the history of clothing since the name could be the basic tool to understand the clothing. In the past, the name of clothing were used in Chinese character which is hieroglyphic. Each character of Chinese has special meaning. They had been changed into Korean after Korean characters were invented. During the period when they were changed into Korean, some of them retained the original meaning while others widened the original meaning. Some of them even translated into totally different meaning. Accordingly, it could be a clue to survey the changing process of Chinese names into Korean by analysing the vocabulary in the books published in Choseon dynasty. In this study, the first step is to survey the children's Chinese vocabulary learning material, Hunmongahoe(1527), Sinzeungliuhap(1576) and Ahackpyun(1804). These books were widely used from 16 to 19 centuries. It has been surveyed how the meaning of clothes names has changed and the special features of changed names. The names appeared in these Chinese vocabulary learning books included headgear, footwear, dress, part names of dress, ornaments, color and names of textile. The followings are observed by studying the names appeared in more than two books above： 1. The same Chinese character were translated differently. 2. Recently the meaning of Chinese character has been reduced or changed into new Chinese character. 3. Some of them retained the same meaning but used different character. It has been observed that some clothing names retained the original meaning but others changed the meaning, or translated into different names. It shows that the appropriate meaning of names should be properly selected when we study the history of clothing.

• KIISE Transactions on Computing Practices
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• v.22 no.9
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• pp.461-466
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• 2016

Topic expansion is an expansion method that reflects external data for improving quality of learned topic. The online learning topic model is not appropriate for topic expansion using external data, because it does not reflect unseen words to learned topic model. In this study, we proposed topic expansion method using infinite vocabulary online LDA. When unseen words appear in learning process, the proposed method allocates unseen word to topic after calculating semantic correlation between unseen word and each topic. To evaluate the proposed method, we compared with existing topic expansion method. The results indicated that the proposed method includes additional information that is not contained in broadcasting script by reflecting external documents. Also, the proposed method outperformed on coherence evaluation.

• English Language & Literature Teaching
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• v.17 no.3
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• pp.27-56
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• 2011

The analysis on the use of lexical discovery and consolidation strategies that have been researched within the area of vocabulary learning strategies (VLS) have not sufficiently drawn the interest of EFL practitioners with regard to vocational high school learners. The results, however, are expected to have implications for the design of vocabulary tasks and instructional materials for EFL learners. The present study investigates EFL vocational high school learners' use of lexical discovery and consolidation strategies with questionnaires, where the use of the learners' lexical discovery strategies were further validated with the think-aloud methodology by asking samples of proficient and less proficient learners to report on their reading process while reading L2 texts that had not been exposed to the learners. The results indicated that there were significant differences between the two groups of learners in the employment of 11 of the strategies which were in the categories of determination, social, memory, and metacognitive strategies, but not for cognitive strategies. The pattern of strategies indicated that different lexical discovery and consolidation strategies were employed relatively more by one proficiency group than another. The study suggests some implications for how strategy-based instruction can be implemented in EFL classrooms.

• Genomics & Informatics
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• v.17 no.2
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• pp.20.1-20.5
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• 2019

Entity normalization, or entity linking in the general domain, is an information extraction task that aims to annotate/bind multiple words/expressions in raw text with semantic references, such as concepts of an ontology. An ontology consists minimally of a formally organized vocabulary or hierarchy of terms, which captures knowledge of a domain. Presently, machine-learning methods, often coupled with distributional representations, achieve good performance. However, these require large training datasets, which are not always available, especially for tasks in specialized domains. CONTES (CONcept-TErm System) is a supervised method that addresses entity normalization with ontology concepts using small training datasets. CONTES has some limitations, such as it does not scale well with very large ontologies, it tends to overgeneralize predictions, and it lacks valid representations for the out-of-vocabulary words. Here, we propose to assess different methods to reduce the dimensionality in the representation of the ontology. We also propose to calibrate parameters in order to make the predictions more accurate, and to address the problem of out-of-vocabulary words, with a specific method.