• 한국콘텐츠학회논문지
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• 제5권4호
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• pp.197-203
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• 2005

멀티플랫폼을 지향하는 유비쿼터스 e-Loaming 시스템에서는 보다 다양한 매체를 통한 온라인 학습이 이루어지기 때문에 상호작용 촉진이 매우 중요하다. 본 논문에서는 온라인 학습에서 매우 절실히 요구되는 상호작용 촉진 학습 설계를 사이버강의에 적용하고 피드백을 통해서 고찰하였다. 향후에는 감성공학과 같은 기반기술을 적용한 보다 효율적인 상호작용을 지원하는 학습 설계가 모색되어야 할 것이다.

• 한국학교수학회논문집
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• 제3권1호
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• pp.31-45
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• 2000

The idea to be changed first among the general ideas of mathematics is that, from the standpoint of teachers, one-sided teaching is efficient due to the progress of classwork of excessive quantity, and, from the standpoint of students, they say they gave up mathematics publicly feeling uneasiness in every class because of the deficiency of previous learning and interest, and they think all problems are due to the educational system, neglecting their studies, not participating actively in lessons. Therefore this study is, after giving learning points and problem papers of which the degree of difficulty differs to the groups of students divided into the advanced, intermediate, and elementary by personal abilities of learning and concerns, tried out to remove uniformity and integrity of lessons through solving the problems students can, to convert lessons to the learner-oriented that learners take part in voluntarily through discussing, solving the problems, and correcting the errors of them by group-cooperative actions, for the students to realize that they can solve everything only by their own endeavors.

• 한국어정보학회:학술대회논문집
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• 한국어정보학회 2017년도 제29회 한글및한국어정보처리학술대회
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• pp.111-115
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• 2017

목적 지향적 대화 시스템(Goal-oriented dialogue system)은 텍스트나 음성을 통해 특정한 목적을 수행할 수 있는 시스템이다. 최근 RNN(recurrent neural networks)을 기반으로 대화 데이터를 end-to-end learning 방식으로 학습하여 대화 시스템을 구축하는데에 활용한 연구가 있다. End-to-end 방식의 학습은 도메인에 대한 지식 없이 학습 데이터 자체만으로 대화 시스템 구축을 위한 학습이 가능하다는 장점이 있지만 도메인 지식을 학습하기 위해서는 많은 양의 데이터가 필요하다는 단점이 존재한다. 이에 본 논문에서는 도메인 특정 지식을 결합하여 end-to-end learning 방식의 학습이 가능한 Hybrid Code Network 구조를 기반으로 한국어로 구성된 식당 예약에 관련한 대화 데이터셋을 이용하여 식당 예약을 목적으로하는 대화 시스템을 구축하는 방법을 제안한다. 실험 결과 본 시스템은 응답 별 정확도 95%와 대화 별 정확도 63%의 성능을 나타냈다.

• Journal of Computing Science and Engineering
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• 제5권4호
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• pp.288-293
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• 2011

To resolve ambiguities in speech act classification, various machine learning models have been proposed over the past 10 years. In this paper, we review these machine learning models and present the results of experimental comparison of three representative models, namely the decision tree, the support vector machine (SVM), and the maximum entropy model (MEM). In experiments with a goal-oriented dialogue corpus in the schedule management domain, we found that the MEM has lighter hardware requirements, whereas the SVM has better performance characteristics.

• 한국가정과교육학회지
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• 제14권2호
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• pp.79-95
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• 2002

The Purposes of this study are first to develop the teaching and learning plan for the dress part in high school's Home Economics by the application of the values clarification theory then to apply it to the classroom activities. and lastly to analyze its effects. We developed the master plan for teaching and learning, and developed the 12 hour sub plans including 7 activities and learning materials. The effects of the teaching are as followings: First, When the self-esteem was compared with the whole classes, there was no difference between the twos, but a boy and a girl who were observed as not making a value-oriented life marked higher score in answering the self-esteem. Second. It was found that values clarification theory made student's degree of participation and interest higher and helped them to choose their dresses in the real life.

• 공학교육연구
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• 제25권5호
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• pp.55-67
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• 2022

Distance learning has become an efficient tool and is being widely used at work and in school. This research presents the results of a project-oriented entrepreneurship course taught both in classroom and online for a period of 3 years before and after the pandemic caused by COVID-19. Despite the various challenges, the outcome demonstrated that the students were able to attain required knowledge and capabilities in the online learning environment. As such, this paper discusses effective ways to blend in distance learning components so that both instructors and students can benefit from Internet-based education technologies. In the future, both face-to-face and virtual project work and study are likely to get integrated into a 'hyflex' class, which is flexible, on-offline education.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.186-191
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• 2023

Neural Networks are widely used for huge variety of tasks solution. Machine Learning methods are used also for signal and time series analysis, including electrocardiograms. Contemporary wearable devices, both medical and non-medical type like smart watch, allow to gather the data in real time uninterruptedly. This allows us to transfer these data for analysis or make an analysis on the device, and thus provide preliminary diagnosis, or at least fix some serious deviations. Different methods are being used for this kind of analysis, ranging from medical-oriented using distinctive features of the signal to machine learning and deep learning approaches. Here we will demonstrate a neural network-based approach to this task by building an ensemble of 1D CNN classifiers and a final classifier of selection using logistic regression, random forest or support vector machine, and make the conclusions of the comparison with other approaches.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.125-139
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• 2023

Facial expression recognition, a topical problem in the field of computer vision and pattern recognition, is a direct means of recognizing human emotions and behaviors. This paper first summarizes the datasets commonly used for expression recognition and their associated characteristics and presents traditional machine learning algorithms and their benefits and drawbacks from three key techniques of face expression; image pre-processing, feature extraction, and expression classification. Deep learning-oriented expression recognition methods and various algorithmic framework performances are also analyzed and compared. Finally, the current barriers to facial expression recognition and potential developments are highlighted.

• 공학교육연구
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• 제26권4호
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• pp.36-46
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• 2023

This paper presents a case study and online-offline (hybrid) course structure for project-oriented community-based service learning in order to solve real-world problems for society. It examines social issues and conduct student projects to develop solutions that can generate sustainable value. This course helps students to use their major knowledge to assess and solve the problems faced by the local community. The outcomes of this course conducted via online lectures and offline project activities are discussed. The operation of this blended type of social problem-solving course is also stated.

• 정보교육학회논문지
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• 제6권1호
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• pp.64-74
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• 2002

본 연구에서는 외국어 학습에서 상황인지(Situated Cognition)의 중요성을 탐색해 보고 상황인지 원리가 반영된 학습환경 중의 하나로 MOO(Multi-user Object Oriented)의 특성을 살펴보고자 하였다. 다른 분야에서도 그러하겠지만, 외국어 학습은 특히 학습해야 할 어휘 또는 표현법의 개념 이해를 넘어 이를 실제 활용할 수 있는 고차원적 수준으로 전개되어야 한다. 어린이가 실제 생활 속에서 주변 사람들과 상호작용하는 가운데 자연스럽게 모국어를 습득하듯이, 상황적 맥락이 충분히 제시되는 환경 속에서 외국어를 학습해야 이를 실제상황에서 십분 적용할 수 있는 가능성이 높아지는 것이다. 바로 이런 점에서 상황인지의 교육적 의의가 있다고 할 수 있다. 최근 교육 분야에서 관심을 모으고 있는 MOO는 텍스트 기반의 공간적 메타포(Spatial Metaphor)를 적용한 가상현실로서, 학습과정에 상황적 맥락을 제공하고 학습자의 상호작용을 촉진할 수 있다는 점에서 시사점이 매우 크다. 이에 본 연구에서는 MOO의 특성들을 활동중심, 맥락중심, 상호작용 측면에서 접근하여 외국어 학습환경으로서의 적용가능성을 제안하였다.