• English Language & Literature Teaching
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• v.8 no.1
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• pp.1-13
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• 2002

One of the benefits of the internet-assisted instruction is that it can improve L2 Learners' motivation to express themselves in English. The purpose of this paper is to investigate an effective approach to British-American fiction learning in Korean universities, which can emphasize communicative strategies drawing on video-conferencing system, a chat system(CUSeeMe), and an e-mail system. Students are passive participants who cannot assert their creativity in the traditional teaching method of British-American fiction, which mainly relies upon reading and translation far from literature lessons. In CCDL(Cross-cultural distance learning) class, students can play active roles in asserting their own ideas and assuming considerable responsibility for making a presentation in English. A professor can play a role as a coordinator in supporting the students' activities and in winding up the class. The main significance of this article lies in providing a paradigm for CCDL class beyond the limitation of the traditional teaching method of British-American fiction in Korea and futhermore in exploring the eclectic integration of the traditional one and CCDL.

• Asia Pacific Journal of Corpus Research
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• v.2 no.1
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• pp.1-11
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• 2021

Recently, corpus assisted vocabulary instruction has been attracting a lot of interest. Most studies have focused on understanding language learners' receptive vocabulary knowledge. Limited attention has been paid to learners' productive competence. To fill this gap, this study attended to learners' productive lexical development in terms of form, meaning and use respectively. This study introduced EFL learners to the corpus-based language pedagogy to learn COVID-19 theme-based vocabulary. To investigate the gains and views of 33 EFL first-year college students, a sentence completion task and a questionnaire were developed. Learners' productive performances in the three lexical knowledge aspects (i.e., form, meaning and use) were particularly targeted. The results revealed that the students achieved significant gains in all aspects regardless of their proficiency level. In particular, the less proficient students achieved greater knowledge retention compared with their highly proficient counterparts. Meanwhile, students showed positive attitudes towards the corpus-based approach to vocabulary learning.

• Journal of Oral Medicine and Pain
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• v.47 no.2
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• pp.107-108
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• 2022

Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.

• Clinical and Experimental Reproductive Medicine
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• v.51 no.1
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• pp.1-12
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• 2024

This review article discusses the integration of artificial intelligence (AI) in assisted reproductive technology and provides key concepts to consider when introducing AI systems into reproductive medicine practices. The article highlights the various applications of AI in reproductive medicine and discusses whether to use commercial or in-house AI systems. This review also provides criteria for implementing new AI systems in the laboratory and discusses the factors that should be considered when introducing AI in the laboratory, including the user interface, scalability, training, support, follow-up, cost, ethics, and data quality. The article emphasises the importance of ethical considerations, data quality, and continuous algorithm updates to ensure the accuracy and safety of AI systems.

• ETRI Journal
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• v.46 no.1
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• pp.48-58
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• 2024

This paper presents the development of language tutoring systems for nonnative speakers by leveraging advanced end-to-end automatic speech recognition (ASR) and proficiency evaluation. Given the frequent errors in non-native speech, high-performance spontaneous speech recognition must be applied. Our systems accurately evaluate pronunciation and speaking fluency and provide feedback on errors by relying on precise transcriptions. End-to-end ASR is implemented and enhanced by using diverse non-native speaker speech data for model training. For performance enhancement, we combine semisupervised and transfer learning techniques using labeled and unlabeled speech data. Automatic proficiency evaluation is performed by a model trained to maximize the statistical correlation between the fluency score manually determined by a human expert and a calculated fluency score. We developed an English tutoring system for Korean elementary students called EBS AI Peng-Talk and a Korean tutoring system for foreigners called KSI Korean AI Tutor. Both systems were deployed by South Korean government agencies.

• Journal of The Korean Association For Science Education
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• v.22 no.3
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• pp.508-516
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• 2002

This study investigated the influences of group composition in cooperative computer-assisted instruction (CAI) upon students' conceptual understandings, application abilities, learning motivations, and the perceptions of involvement. Seventh graders (N=97) were selected from a co-ed middle school in Seoul, and taught about 'motion of molecules' for 5 class hours. In the two treatment groups with cooperative CAI strategy, homogeneous and heterogeneous small groups were organized by the previous science achievement. Traditional instructions were administered to the comparison group. Two-way ANCOVA results revealed that the scores of the conception test for the treatment groups were significantly higher than those for the comparison group. However, there was no difference between the homogeneous and the heterogeneous groups. The scores of the three groups did not differ significantly in the application test and the learning motivation test. However, the perceptions of involvement for the treatment groups were more positive than those for the comparison group.

• Journal of Korean Academy of Nursing Administration
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• v.12 no.1
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• pp.41-51
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• 2006

Purpose: The purposed of this study was to develop and evaluate a Web-based for medical terminology educational program. Method: For the development of this program, the NBISD model was applied as a basic model and WBI ID Process Action model was applied. It was executed for 15 weeks along with off-line lectures. After the operation of this program to 210 nursing students, learners' responses were analyzed twice(at 5th week and 15th week). Result: The satisfaction with this program was slightly above the center point. But the structure of system and composition of design were high score. The results of the final evaluation were more positive than those of the interim one. This program have the advantage of easy accessibility and easy understandability with picture and testing. Conclusions: This study proved the importance of the suitability of learning contents and learning form in developing WBI programs and showed possibility for applying WBI to medical terminology. In order to enhance the effects of Web-based medical terminology educational program for, it is necessary to perform analytic comparison with the effect of WBI based on self-directed learning.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.9
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• pp.47-52
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• 2020

With the 4th industrial revolution, condition monitoring using machine learning techniques has become popular among researchers. An overload due to complex operations causes several irregularities in MOSFETs. This study investigated the acquired voltage to analyze the overcurrent effects on MOSFETs using a failure mode effect analysis (FMEA). The results indicated that the voltage pattern changes greatly when the current is beyond the threshold value. Several features were extracted from the collected voltage signals that indicate the health state of a switched-mode power supply (SMPS). Then, the data were reduced to a smaller sample space by using a principal component analysis (PCA). A robust machine learning algorithm, the support vector machine (SVM), was used to classify different health states of an SMPS, and the classification results are presented for different parameters. An SVM approach assisted by a PCA algorithm provides a strong fault diagnosis framework for an SMPS.

• The Journal of Korean Association of Computer Education
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• v.13 no.1
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• pp.37-44
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• 2010

Recently, the scientific approach to brain engineering is actively being made for effective foreign language learning and diagnosis. In order to supplement the problem of preexistence paper exam, the study aimed to develop a tool for foreign language fluency diagnosis which based on brain engineering. The proposed tools in the paper indirectly measure the aspects of brain information processing by testing learners' 3 abilities of linguistic memory, comprehension, and language production in 5 different ways.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.207-221
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• 2014

Education environment of modern society is rapidly changing along the usage of various device and development of contents. Learners of diverse age groups and genders are exposed in smart education environment. Thus in order to investigate effective smart education contents production, this study classified interactive types that affect learning satisfaction into CAI (Computer Assisted Instruction) based , NCS (Network Communication System) based , and NTS (New Technology System) based . Then we investigated how each interactive types affect immersion, utility, self-efficacy, practicality, and stimulation. The effects were measured according to the learner's gender and age. As the result, interactive types do affect smart education, where male had higher learning satisfaction for CAI based, game type, and wiki type while female had higher satisfaction for relationship establishment type and experience type. Also, for age group, the 10s preferred NTS based, 20~30s NCS based, and 40s and over CAI based interactive type. Thus, if satisfaction levels according to gender and age are considered when producing smart education contents, it may be possible to create educative contents that meet the dispositions of the learners.