Earticle

Although dialects of a single language could distinctly differ from each other, including their common language, very little is known about interpreters’ comprehensibility of a dialect and the accuracy of interpreting performance of which source language is in the dialect. This paper reports on the findings of an investigation that explored the accuracy of a consecutive interpreting performance from the Jeju dialect that was performed by Jeju dialect speaking interpreters and non-Jeju dialect interpreters. By using a meaning unit-based quality assessment, the accuracy of interpreting performances between the two groups were compared. The results show that the non-Jeju dialect speaking interpreters’ performances were significantly inaccurate with the majority of the information in the source text either being omitted or distorted whereas Jeju dialect speaking interpreters’ performances achieved acceptable accuracy. The incomprehensibility of Jeju dialect seems to be attributed to the inaccurate performances of the non-Jeju dialect speaking interpreters, largely due to unfamiliar words. Although both groups used the same strategy (omissions and making inferences) to cope with incomprehension issues, the effectiveness of the strategies was limited because non-Jeju dialect speaking interpreters were confused by the unique phonetic, morphologic, and lexical features of the dialect.

This study investigates a relationship between explicit knowledge of rules and accuracy in article use for advanced Korean learners on a controlled methodology and a detailed classification system of articles. The purpose is to examine if teaching English article rules to L2 learners improves accuracy in their using articles. The participants were seventy-two college and graduate students. The students completed a fill-in-the-article test and a knowledge-of-rules test. The quantitative analyses of the data revealed that there is a significant correlation between rule knowledge and article use in an overall way. Specifically, explicit knowledge of rules and article accuracy were strongly correlated in the usages of ‘no article’ ∅ such as the zero article ∅1 in Type 1, 3, and 4 and the null article ∅2 in Conventional use. These findings suggest that formal instruction of articles is effective for advanced Korean learners. Teaching materials should be developed with a focus on the usages of ‘no article’ ∅. Teaching explicit article rules and providing sufficient exercises with the global context may contribute to improving advanced Korean learners’ accuracy in using articles.

Purpose: The aim of this study was to determine the reliability and accuracy of measurements in digital models(CEREC AC) compared to stone models. Methods: A master model(500B-1, Nissin Dental Product, Japan) with the prepared upper full arch tooth was used. Conventional impression and then stone model(n=10) were produced from this master model, and on the other hands, digital impressions were made with the CEREC AC intra-oral scanner(n=10). One examiner measured two times the intercanine, intermolar distance, dental arch length. The stone model were measured using a digital caliper. The t-student test for paired samples and intraclass correlation coefficient(ICC) were used for statistical analysis. Results: The measurement of two methods showed very good reliability. At the intra-examiner reliability of measurement, ICC at the stone and CEREC AC model were 0.81 and 0.94. The mean difference between measurements made directly on the stone models and those made on the CEREC AC model was 0.20~0.28 , and was statistically significant(P=0.001). Conclusion: These in vitro studies show that accuracy of the digital impression is similar to that of the conventional impression. These results will have to be confirmed in further clinical studies.

Purpose: The purpose of this study is to evaluate the discrepancy of scan process in dental intra oral scanner by comparing model scanner and anticipate possibility to introduce intra oral scan technique. Methods: 3D superimposition test was conducted to compare the scan discrepancy. The scanners used in this study are the e-oral scanner, the D750 model scanner, and the high precision CMM(3D Coordinate Measuring Machine). The standard of accuracy verification is ISO 5725-1; trueness and precision. Master model was manufactured by dental stone and scanned 5 times by intra oral, model scanner. Reference data was scanned 5 times by high accuracy CMM to evaluate the trueness. Results: Trueness of D750 scanner were 7.4 ㎛ 5.1 ㎛ 6.8 ㎛ at an abutment, an occluasal, a specific area. and trueness of e-scanner were 20.2 ㎛ 27.4 ㎛ 37.8 ㎛ at an abutment, an occluasal, a specific area. Precision of D750 scanner was 7.04 ㎛, e-scanner was 15.95 ㎛. Conclusion: When conducting in vitro test, The mean difference of trueness between e-scanner and D750 were 12.8 ㎛ at an abutment area, 22.3 ㎛ at an occlusal area, 31.0 ㎛ at a specific area and 8.91 ㎛ in precision. The scan discrepancies are within the range of clinical acceptance.

본 연구의 목적은 외국어 읽기의 유창성과 정확성의 언어습득적 의의를 고찰하고, 효율적인 영어 학습 패러다임을 연구하는데 있다. 언어습득 측면에서, 제 2언어학습의 정확성과 유창성사이에서 무엇을 우선 가르치느냐의 문제는 중요한 이슈가 되어왔다. 제 1언어와 제 2언어의 교실상황에서, 많은 언어연구가들의 관심 때문에, 유창성은 중요한 요소로 대두되고 있다. 정확성과 유창성은 둘 다 중요하지만, 외국어의 경우, 유창성 중심의 학습에서 정확성 중심의 학습으로 점진적인 학습 패러다임의 전환이 있어야 한다. 이런 관점에서, 본 연구는 외국어의 유창성 개발을 위한 대안으로 자발적다독법을 제시하고 있다. 빠르고 정확한 단어 인지 기술과 읽기 유창성이 없으면, 좋은 읽기 능력을 가질 수 없다. 그러므로 유창성 개발을 위한 방법들이 개발되어야 하며, 이것에 대한 해법으로, 자발적다독법이 외국어 교육상황에서 읽기유창성을 위한 효과적인 연구방법론임을 입증하고 있다.

This study aims to explore efficient foreign language learning paradigm with a focus on reading fluency and accuracy. From a perspective of language acquisition in the foreign language context, the priority in the L2 learning between accuracy and fluency has been a very important issue. Fluency becomes an important issue due to many researchers’ interests in the L1 and L2 classroom. Although both accuracy and fluency are crucial, the paradigm shift from fluency to accuracy is necessary in the foreign language teaching. In this context, as an alternative methodology for L2 learners' fluency, the extensive reading approach is provided. A number of studies have suggested that extensive reading program could lead to improvement of L2 learners’ reading rate and is an effective approach to improving general language proficiency.

This research was conducted on 16 students at graduate school of interpretation and translation in Seoul, and the findings showed that the accuracy of their simultaneous interpreting, measured between in the beginning of learning (in about 3 months) and the mid-term (in about 6 months), substantially improved. One possible explanation for such an improvement could be the fact that many of these students were able to perform a fairly accurate simultaneous interpretation even during the first few weeks of learning although they had never been trained for simultaneous interpreting previously. Moreover, eight out of the 16 trainees, or 50 percent of the total, showed a steady improvement in terms of accuracy of interpreting from the first to the second and to the third trials. The other students achieved the same or lower accuracy with time while one of them delivered a poorer performance in the third test compared to the first test. Not all learners steadily improved in interpreting accuracy in this study. However, it compares and analyzes their progress in the accuracy of interpretation, thereby helping better understand the learning effects of students and explore how to improve their performance.

金漢植(2014)は、ある学期の初めと終りに、同時通訳の学習者に最大限同じ条件·同じテキストで通訳をさせ、その結果を比較することで、能力の向上を確認する方法を提案した。本研究では、3度にわたり同じテキスト·同じ条件で通訳をさせ、より長期にわたる多様な比較分析を試みた。また、通訳の正確度の評価をより明確に行うため、数字の多いテキストを取り上げて数字部分に重点を置いて評価·比較を行った。 ソウル所在の通訳大学院の学生16人を対象に分析した結果、全般的には、同時通訳の学習初期(約3か月)に比べ、学習中期(約6か月)により大幅に正確度が向上したことが確認された。同時通訳をまったく学習していない最初の週から、すでにある程度正確の通訳ができていたことなどがその理由として考えられる。 また、通訳の1回目、2回目、3回目と回を重ねるごとに正確度が右肩上がりに向上した学習者は16人中8人とちょうど半分で、1回目と2回目·2回目と3回目の比較で正確度が同じスコアにとどまったり低下した学習者が8人、その内1回目より3回目の正確度が低かった学習者は1人いた。 学習者全員が順調に通訳の正確度を向上させたとは言えないが、正確度を比較し確認することで、学習効果を確かめ、改善すべき点について考えるきっかけ作りになるものと思われる。

최근 DNN이 다양한 산업에 확산되면서 IoT 기기 및 엣지 컴퓨팅에 적합한 경량 모델에 관한 연구가 급증하고 있 다. 본 논문에서는 기존에 없던 딥러닝 모델의 파라미터를 1 비트 단위로 조작할 수 있는 자동화 프레임워크를 개발 하며 파라미터 비트와 모델 정확도 사이의 관계를 실험 및 연구한다. 본 연구는 제안된 프레임워크를 사용하여 ImageNet 데이터셋으로 사전 학습된 DNN 모델 중 CNN 모델들의 파라미터를 하위 n-bit를 0, 1 또는 랜덤한 값으로 치환하는 3가지 방법을 통해 각각 정보 손실 발생시키면서 파라미터와 정확도 간의 강인성을 비트 단위로 실험하였다. 주요 모델로는 InceptionV3, InceptionResnetV2, ResNet50, Xception, DenseNet121, Mobile NetV1, MobileNetV2 을 사용하였다. 실험 결과, 성능이 낮은 모델일수록 하위 비트의 정보 손실에 민감하여 성 능이 좋은 모델보다 정확도를 유지하는 비트 수가 적다는 것을 실험적으로 확인했고, 파라미터와 정확도 간의 강인 성이 높다는 것을 확인하였다. 이러한 실험을 바탕으로 모델별 유효 파라미터 비트를 설정하여 파라미터를 줄이며 정확도를 유지할 수 있다.

Recently, with the proliferation of DNNs in various industries, there has been a surge in research on lightweight models suitable for IoT devices and edge computing. In this paper, we propose an automated framework that enables manipulation of deep learning model parameters at a 1-bit level, a capability not previously available. We investigate the relationship between parameter bits and model accuracy. Using the developed framework, we systematically experimented with the parameters of CNN models pre-trained on the ImageNet dataset by setting the lower n-bit to 0, 1, or a random value while each method inducing distinct information loss. The primary models evaluated include InceptionV3, InceptionResnetV2, ResNet50, Xception, DenseNet121, MobileNetV1, and MobileNetV2. Experimental results show that models with lower performance are more sensitive to information loss in the lower bits, requiring fewer bits to maintain accuracy compared to high-performing models. This concludes a high robustness between parameters and accuracy.

This preliminary study is the first in a series of studies aimed at improving the self-assessment of undergraduate translation and interpreting students. Self-assessment is crucial to developing self-directed learning skills and enabling formative assessment - key components of lifelong learning competence. The study looks at the consecutive interpreting performance of two cohorts: eight students (4-5 sessions) from Autumn 2023 and six students (3-4 sessions) from Spring 2024. The accuracy of the students' self-assessments was compared with the teachers' assessments. Three key findings emerged: i) the correlation between student self-assessments and instructor ratings increased progressively from week 1 to week 4; ii) high-performing students' self-assessments were more closely aligned with instructor ratings; and iii) the greatest agreement between student and instructor ratings occurred when rating accuracy. This initial study sets the stage for future research to develop better teaching methods for self-assessment in translation and interpreting education. The findings suggest several implications for teaching, which are discussed along with plans for longer-term research.

This study aims to investigate the impact of AI translation on undergraduate students' Russian writing and to explore ways to teach Russian writing using AI tools. This study examined the differences between texts written by learners themselves and texts generated using AI translation. Furthermore, it examined the differences in writing outcomes using AI translation depending on text genre. The analysis results are as follows: First, AI translation in Russian writing improves syntactic complexity regardless of text genre. Second, AI translation in Russian writing improves fluency regardless of text genre. Third, learners' approaches to AI translation differ depending on text genre. Fourth, AI translation does not improve grammatical accuracy in Russian writing. Fifth, AI translation does not improve vocabulary in Russian writing. Sixth, AI translation in Russian writing ismore effective in tasks involving more difficult text genres. Seventh, AI translation in Russian writing does not contribute to the completeness of the text.

This study investigates the effects of varying the duration of pre-task planning (30 seconds, 3 minutes, 5 minutes) and English language anxiety on speaking performance in a Computer-Based Test(CBT). The study involved 57 participants from a university in Korea, who completed speaking tasks under different planning conditions and completed an anxiety survey. The findings indicated that extended planning time notably enhances discourse quality, with significant improvements in accuracy observed after 5 minutes of planning. Additionally, a decrease in vocabulary usage was correlated with higher anxiety levels, particularly under the shortest planning time condition(30 seconds), suggesting that anxiety can harmfully impact performance, an effect reduced by longer planning duration. Lastly, it was also found that there was a significant trade-off relationship between accuracy and complexity during the 3-minute planning condition. The results suggest that providing extended planning time and incorporating anxiety-reducing strategies, especially for shorter planning durations, can enhance speaking performance. Additionally, adjusting planning time in test design can help balance accuracy and complexity in evaluating speaking skills.

This study compares and analyzes the performance of LIME-based machine learning methods (Gaussian Naive Bayes (GNB), Highly-Efficient Logistic Regression (LR), Linear Support Vector Machine (SVM), and Triple-layer Neural Network (TNN)) using three medical datasets. High-dimensional data increases the likelihood of overfitting in learning algorithms due to the curse of dimensionality. To address this, LIME is utilized to compute the importance of key features contributing to the model's predictions. Based on this, features are selected. The LIME technique generates multiple samples by perturbing the data in the local region. Subsequently, a simple linear model is used to evaluate the impact of each feature on the predictions. Features with high importance derived from this process are selected for model retraining. As a result, it was confirmed that learning time could be reduced while maintaining or even improving performance with a smaller number of features. Consequently, by selecting necessary features, the curse of dimensionality issue is alleviated, and accuracy can be maintained or improved using fewer features in the Hepatitis C Prediction Dataset, Breast Cancer Wisconsin (Prognostic) Dataset, and Glioma Grading Clinical and Mutation Features Dataset.

The purpose of this study is to explore an alternative model for the TOEIC speaking test based on language ‘Complexity’, ‘Accuracy’ and ‘Fluency’ (CAF) by drawing comparisons between task-based CAF (Model 1) and communicative adequacy-based CAF (Model 2). Thirty-two college students participated in the study and carried out CAF based English speaking tests. The results of Pearson analysis revealed that Model 2 has a higher correlation with the TOEIC speaking scores than Model 1. Based on factor analysis, Model 2 was restructured, to create a new format, NCAF (New CAF). Under the NCAF model, ‘Complexity’ has three sub-items: sentence length, sentence elaboration, and lexical density; ‘Accuracy’ has error accuracy 1, and error accuracy 2; and ‘Fluency’ includes pause distribution, speed fluency, and pause frequency. To assess the relationship between the NCAF model and TOEIC speaking scores, a regression analysis was performed. The results showed that NCAF could account for 76.1% of the TOEIC speaking scores. Pedagogical implications and discussions are suggested.

This research examines how ChatGPT characteristics influence user acceptance in finance, exploring the interplay with the Technology Acceptance Model (TAM) (Davis 1989). It emphasizes accuracy, innovation, recommendation, perceived usefulness, and ease of use, analyzing their impact on financial communication and decision-making. Findings from the structural equation model show accuracy significantly affects perceived usefulness, while innovation and recommendation impact ease of use. The study also assesses how digital proficiency moderates the relationship between perceived usefulness, ease of use, and acceptance intentions. The structural equation model employed in the study demonstrates overall suitability, with accuracy significantly affecting perceived usefulness and innovation and recommendation significantly affecting perceived ease of use. Notably, perceived usefulness and ease of use emerge as key factors influencing acceptance intentions, particularly among less digitally skilled financiers. This paper adopts the questionnaire survey method and the questionnaire survey was conducted from September to November 2023 in Korea. 182 copies of the questionnaires were used as final analysis data. SPSS 26.0 and Amos 28.0 software were used to analyze the data. In summary, this paper provides valuable insights into the interplay of ChatGPT characteristics and acceptance intention within the financial sector. By combining these insights with an understanding of the financial landscape, the study contributes to a comprehensive knowledge base on the factors influencing AI adoption in finance, facilitating informed decision-making in this evolving technological landscape.

The present study aimed to explore how pre-service teacher’s individual regulatory focus orientation, currently emerging as an interesting learner variable for language learning, could influence their Englishspeaking abilities. English teaching demonstration videos of 67 pre-service teachers were analyzed in terms of pronunciation, accuracy, and fluency. The regulatory focus orientations of participants were evaluated using a questionnaire. The results of data analysis, using multiple regression analysis, indicated that promotion-focus orientation was a significant positive predictor for pronunciation, fluency (words per minute, ratio of dysfluency), and accuracy (lexical errors, ratio of error-free AS-units). On the other hand, prevention-focus orientation did not emerge as a statistically significant factor affecting accuracy. However, it was observed to have a negative influence on both pronunciation and fluency. In light of the research findings that highlight the favorable impact of a promotion-focus orientation, suggestions were made for future teacher training programs aimed at enhancing the English proficiency of pre-service teachers.

Background: Recently, the single-step genomic best linear unbiased prediction (ssGBLUP) method, which incorporates not only genomic information but also phenotypic information of pedigree, is under study. In this study, we performed a ssGBLUP analysis on a commercial Hanwoo population using phenotypic, genotypic, and pedigree data. Methods: The test population comprised Hanwoo 1,740 heads raised in four regions of Korea, while the reference population used Hanwoo 18,499 heads raised across the country and two-generation pedigree data. Analysis was performed using genotype data generated by the Hanwoo 50 K SNP beadchip. Results: The mean Genome estimated breeding values (GEBVs) estimated using the ssGBLUP methods for carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS) were 7.348, 1.515, -0.355, and 0.040, respectively, while the accuracy of each trait was 0.749, 0.733, 0.769, and 0.768, respectively. When the correlation analysis between the GEBVs as a result of this study and the actual slaughter performance was confirmed, CWT, EMA, BFT, and MS were reported to be 0.519, 0.435, 0.444, and 0.543, respectively. Conclusions: Our results suggest that the ssGBLUP method enables a more accurate evaluation because it conducts a genetic evaluation of an individual using not only genotype information but also phenotypic information of the pedigree. Individual evaluation using the ssGBLUP method is considered effective for enhancing the genetic ability of farms and enabling accurate and rapid improvements. It is considered that if more pedigree information of reference population is collected for analysis, genetic ability can be evaluated more accurately.

본 연구는 한국어능력시험 대담 듣기 텍스트에 나타난 한국어 헤지 양상을 분석하여 한국어교육에서 대담 연구의 기초를 마련하는 것을 목적으로 한다. 대담 듣기 텍스트에 나타난 헤지의 양상을 분석하기 위해 다양한 연구물을 분석하여 ‘명제의 정확성과 신뢰성’, ‘주장의 객관성과 양태성’, ‘체면위협 행위 고려’로 나누어 헤 지 유형을 제시하였다. 대담 듣기 텍스트에서 헤지는 명제에 대한 정확성과 신뢰성을 강 화하고 확보하는 언어 장치로 활용된다. 그리고 화자는 청자에게 전달하는 주장의 진실 성과 객관성을 확보하고자 하며 발화에 대한 부담과 책임을 덜어내기 위해 청자의 수용 성을 높일 수 있는 양태성 표현을 사용한다. 또, 청자의 체면의 위협을 최소화하고자 체 면 고려 헤지를 사용한다. 이를 바탕으로 한국어능력시험 대담 듣기 텍스트에서 헤지 양상을 살펴본 결과 ‘-고 요, -지요’ 헤지를 통해 명제의 신뢰성과 정확성을 나타내고자 하였다. 대담에서 이중구 조의 수신자를 대상으로 하는 화자는 정확한 정보 전달로 주장의 객관성을 유지하면서 책임을 방어할 수 있는 ‘-는 것, -는 것이지요, -는다는 것이지요, -는 것으로 나타나다’를 활용하였다. 반면에 ‘-(으)ㄹ 수 있다, -(으)ㄹ 것 같다, -았/었을 겁니다, -아/어야겠지요, - (으)ㄹ텐데요’ 등의 양태성 표현 활용을 통해 화자로서 부담을 완화하고자 하였다. 그리 고 대담에서 청자의 체면위협 행위를 최소화하기 위해 ‘-(으)ㄹ까요?, -(으)ㄴ/는데요, - 군요, -잖아요?’ 등의 헤지를 적극적으로 활용하였다. 전문적이고 학문적인 주제인 대담에 어려움을 겪는 한국어 학습자들에게 한국어능 력시험 대담 듣기 텍스트의 헤지 양상 분석의 결과는 대담 듣기 학습의 기초적인 자료로 활용될 수 있을 것이다.

This study aims to analyze hedge patterns of Korean in conversation listening texts of Test of Proficiency in Korean and thus establish a basis for the study of conversations in Korean education. To analyze hedge patterns in conversation listening texts, the study analyzed an array of research materials and identified three hedge patterns including "accuracy and reliability of propositions," "objectivity and modality of arguments," and "consideration of face threatening acts." In conversation listening texts, a hedge is used as a linguistic device to reinforce and secure the accuracy and reliability of propositions. The speaker tries to secure the authenticity and objectivity of his or her arguments and uses expressions of modality to increase the acceptance of the listener to relieve his or her burden and responsibility with utterances. In addition, the speaker uses a hedge of considering a face to minimize his or her threat to the speaker's face. Based on these findings, the study examined hedge patterns in conversation listening texts in Test of Proficiency in Korean and found that the hedge of ‘-goyo, and –jyo’was used to show the reliability and accuracy of propositions. Talking to recipients in a dual structure in conversations, the speaker utilized ‘-neun geos, -neun geos-ijiyo, -neun daneungeos-ijiyo, and -neun geos-eulo natanada’ to defend his or her responsibility while maintaining the objectivity of his or her arguments through the delivery of accurate information. The speaker tried to alleviate his or her burden by using expressions of modality such as ‘-(eu)l su issda, -(eu)l geos gatda, -eoss/ass-eul geobnida, -eo/ayagessjiyo, and -(eu)ltendeyo’and made active use of such hedges as ‘-(eu)lkkayo?, -(eu)n/neundeyo, -gun-yo, and –janh-ayo?’ to minimize an act of threatening the face of the listener in conversations. The study analyzed hedge patterns in conversation listening texts in Test of Proficiency in Korean for Korean learners struggling with talking about professional and academic topics. The analysis results will serve as basic data in the study of conversation listening.