• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.319-322
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• 2016

본 연구는 온라인교육에서 주로 활성화 되어 있는 데이터 기반의 학습자 평가시스템이 아닌 초 중등학교 면대면 교실 수업 중 실시간으로 발생하는 유의미한 학습활동 정보를 스마트기술을 활용하여 데이터로 축적하고 분석하여 다양하게 제시함으로써, 학습자에게는 학습에 대한 정확한 피드백을 주고 교수자에게는 수업방향을 제고하며 부모들에게는 자녀들의 학습활동에 대한 이해도 높일 수 있는 학습자 분석 및 평가 시스템을 개발 시 요구사항들을 분석하고자 한다. 이를 위해 스마트교육을 위한 교수학습 방법들을 고려하여 적합한 스마트기기 기반 수업지원 도구를 조사하고 도구 사용 후 발생되는 학습활동에 관한 데이터를 분석할만한 데이터 마이닝 기법을 소개하여 향후 학습자평가 시스템에 대해 제언한다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.419-422
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• 2010

사용자와 환경의 변화에 적응하기 위해서 베이지안 네트워크의 다양한 학습 방법들이 연구되고 있다. 기존의 많은 학습방법에서는 학습 데이터로부터 통계적 방법을 통해서 베이지안 네트워크 모델을 학습하는데, 이러한 접근 방법은 학습 데이터를 수집하기 어려운 문제에 적용하기 힘들며, 사용자의 의도를 데이터의 패턴들로만 학습하므로 직접적으로 사용자의 의도를 반영할 수 없다. 본 논문에서는 대화에 기반하여 사용자의 의도를 직접적으로 수집하고, 이로부터 베이지안 네트워크의 파라메터를 학습하는 방법을 연구한다. 제안하는 방법에서는 사용자와의 대화를 통해서 현재의 모델의 잘못된 점 혹은 개선점을 직접적으로 입력 받고, 이를 바탕으로 베이지안 네트워크 모델을 수정하여 데이터의 수집 없이 빠른 시간에 사용자가 원하는 모델을 학습 할 수 있다. 기존의 통계적 기법을 이용한 대표적인 베이지안 네트워크 파라메터 학습 방법인 최대우도 추정(Maximum Likelihood Estimation; MLE) 방법과 제안하는 방법을 비교하여 제안하는 방법의 유용성을 확인한다.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1101-1107
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• 2017

This study explored the effect of ASR-based pronunciation instruction, using a mobile platform, on EFL learners' pronunciation development. Particularly, this quasi-experimental study focused on whether using mobile ASR, which provides voice-to-text feedback, can enhance the perception and production of target English consonants minimal pairs (V-B, R-L, and G-Z) of Korean EFL learners. Three intact classes of 117 Korean university students were assigned to three groups: a) ASR Group: ASR-based pronunciation instruction providing textual feedback by the mobile ASR; b) Conventional Group: conventional face-to-face pronunciation instruction providing individual oral feedback by the instructor; and the c) Hybrid Group: ASR-based pronunciation instruction plus conventional pronunciation instruction. The ANCOVA results showed that the adjusted mean score for pronunciation production post-test on the Hybrid instruction group (M=82.71, SD =3.3) was significantly higher than the Conventional group (M=62.6, SD =4.05) (p<.05).

• Journal of The Korean Association of Information Education
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• v.21 no.4
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• pp.403-413
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• 2017

The purpose of this paper is to verify whether the entry programming course applied with the flow based learning type is to affect the flow of students' learning. The subjects of the study were the students in the 3rd grade of the National University of education who had not experienced the coding before, and conducted two hours of programming lessons per week for three months. Learning contents and learning materials of beginner course in Entry Homepage were used as learning materials. The teaching and learning process consisted of clear goals setting, motivation, follow-up and immediate feedback, providing application problems, and providing reflection time for students. As a result of the study, the nine factors of flow were compared before and after the experiment. The seven factors - A balance between challenges and skills, Immediate feedback, Action and awareness are merged, Distractions are excluded from consciousness, No worry of failure. Self-consciousness disappears, The activity becomes autotelic-were obtained.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.131-136
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• 2016

An appropriate evaluation on learner's pronunciation has been an important part of foreign language education. The learners should be evaluated and receive proper feedback for pronunciation improvement. Due to the cost and consistency problem of human evaluation, automatic pronunciation evaluation system has been studied. The most of the current automatic evaluation systems utilizes underlying Automatic Speech Recognition (ASR) technology. We suggest in this work to evaluate learner's pronunciation accuracy and fluency in word-level using the ASR and non-native teacher's speech model. Through the performance evaluation on our system, we confirm the overall evaluation result of pronunciation accuracy and fluency actually represents the learner's English skill level quite accurately.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.55-64
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• 2017

The purpose of this study is to identify the difficulties of learners who started programming after entering college and to search an effective software education method as university liber arts for non-science major students. In order to do this, we analyzed the difficulties of learners in Python programming classes composed of students from various majors at H University through questioning and taught them using flipped class model with pre-questions. The questions that students submit are collected online before class every time, the data on the degree of the difficulty of feeling and the understanding of feeling were obtained through the questionnaire. As a result, for learners who are new to programming, the learners should allocate the process of making the problem into a logical abstraction at the beginning of the curriculum before learning the basic concept of computer language, each lesson should be practiced through the bottom-up problems enough to provide a logical understanding before actual coding. In addition, detailed curriculum should be developed according to characteristics of learner's major, contents and conducting level.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.106-113
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• 2019

The purpose of this paper is aimed to derive suggestions for convergence technology for effective management of distance education by analyzing a long-term case. The experiment was designed with notebook, smartphone or tablet based robot controlled by a remote instructor and a learner, who have experience of distance learning including robot assisted learning. The tablet based robot has the display system of feedback to speakers. During five months, three types of experiments were conducted randomly and a participant was interviewed thoroughly. The result, like the previous research, demonstrates that the task performance of the learner in telepresence robot-assisted learning was better than that in the notebook, and smartphone based. However, it is believed to be necessary to adjust the system for eye-contact and voice transmission for the remote instructor. The instructor required an additional sight by supplementing an extra camera and automatic direction control to source of sound.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.483-485
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• 1999

인터넷의 자유로운 접근을 통해 웹기반의 가상 교육이 널리 퍼지게 되었고, 웹에서의 교육이 하나의 교육의 형태로 자리잡게 되었다. 따라서 가상 교육을 통한 새로운 지식창조를 위한 인재양성을 위하여 정보 인프라와 정보서비스의 활용이 중요시되는 지식기반사호로 진입하고 있다는 점에서 종래의 단순한 지식 전달에만 중요시되었던 가상교육의 학습형태에서 벗어나 새로운 지식의 창출을 도와주는 바람직한 지식정보화 방향정립이 필요하다. 이를 통해 본 논문은 학습 정보를 구조적으로 구성하고 관리하여 학습자에게 빠른 피드백과 적응적인 학습물을 제공한다. 또한, 능동적인 학습내용의 체계화로 학습자 스스로 학습에 대한 주도적인 역할하며 전달받은 정보를 자신의 내면적 지식으로 바꿀 수 있는 빠른 학습효과를 가져올 수 있다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.339-345
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• 2023

Pre-service teachers have established and developed their own teaching strategies and professional language teaching skills based on their pedagogical and learning experiences. In this regard, it is conceivable that pre-service teachers' feedback may have distinct viewpoints and focuses. Therefore, the purpose of this study is to analyze pre-service teachers' feedback to microteaching demonstrations. Participants in the study were 40 prospective elementary school teachers. They were invited to offer feedback on microteachings video-recorded by their peers. According to the findings, we identified a total of 708 comments. The majority of feedback was categorized as teacher talk(40.1%) , followed by teaching and learning activity (20.9%), interaction (12.6%), teaching materials (11.4%), classroom atmosphere and learning environment (8.9%), lesson flow (3.7%), review and evaluation (1.3%), and introduction and objectives (1.1%). The most frequent types of feedback were the teacher's use of appropriate speaking rate, tone, and intonation. This finding reflects the fact that English teachers realize the importance of the teacher's English proficiency, therefore we suggest that teacher education institutions need raise awareness not just of teachers' English skills but also of their diverse perspectives.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.685-690
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• 2021

In this paper, we propose a deep learning-based transmit power control scheme to maximize the sum-rates while satisfying the minimum data-rate in downlink non-orthogonal multiple access (NOMA) systems. In downlink NOMA, we consider the co-channel interference that occurs from a base station other than the cell where the user is located, and the user feeds back the signal-to-interference plus noise power ratio (SINR) information instead of channel state information to reduce system feedback overhead. Therefore, the base station controls transmit power using only SINR information. The use of implicit SINR information has the advantage of decreasing the information dimension, but has disadvantage of reducing the data-rate. In this paper, we resolve this problem with deep learning-based training methods and show that the performance of training can be improved if the dimension of deep learning inputs is effectively reduced. Through simulation, we verify that the proposed deep learning-based power control scheme improves the sum-rate while satisfying the minimum data-rate.