• Journal of Science Education
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• v.43 no.3
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• pp.271-283
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• 2019

This study examines the effects of virtual reality learning materials on the learners' learning motivation. For this study, we developed a virtual reality learning material for geological learning that allows observation of the characteristics of rocks in Korean topography that is closely related to learning contents. A 15-hour class was conducted with 91 students using virtual reality learning materials developed for first-year science high school students in D city. ARCS learning motivation strategy was used. Pre-test was conducted before the start of the classes and post-test was conducted after the classes. Statistical processing was analyzed using R-3.5.1 version program. As a result, the utilization of virtual reality learning materials has significant effects on attention concentration, satisfaction, and confidence in the learner's motivation factors. Using virtual reality in geological classes, students' interest in learning activities improve their immersion and concentration, which helps them understand the learning contents better.

• The Journal of the Acoustical Society of Korea
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• v.12 no.4
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• pp.57-62
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• 1993

본 논문은 신경망을 이용한 우리말 모음에 대한 인식 연구이다. 음성을 나누거나. 음소별 인식이나, 시간 신축 방법을 사용하지 않고 모음을 인식하였다. 식나의 변화에 따른 음성의 변화를 정적인 음성으로 취급하였다. 10개로 균등히 나눈 프레임에 각 프레임마다 10차의 PARCOR계수를 추출하였다. 신경망의 구조를 간단히 하기 위해서 단모음과 복모음을 구분하여 학습시켰으며, 출력 노드의 수를 감소시키기 위해 이진 코드 형태로 구성하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1557-1564
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using the individual average difference of emotional signal, because an emotional signal pattern depends on each individual. In order to accurately recognize a user's emotion, the proposed model utilizes the difference between the average of the input emotional signals and the average of each emotional state's signals(such as positive emotional signals and negative emotional signals), rather than only the given input signal. With the aim of easily constructing the emotion recognition model without the professional knowledge of the emotion recognition, it utilizes a maximum entropy model, one of the best-performed and well-known machine learning techniques. Considering that it is difficult to obtain enough training data based on the numerical value of emotional signal for machine learning, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of emotional signals per second rather than the total emotion response time(10 seconds).

• Journal of Digital Convergence
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• v.17 no.5
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• pp.41-49
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• 2019

This study aims to investigate the awareness and status of smart attendance systems in the professors and college students who directly use an electronic smart system, a learning management system utilizing IT and to propose a plan for improvement to increase the efficiency of the smart attendance system. As for the research method, this study conducted an online survey with 264 students at S. University to investigate the status of their use and awareness of the smart attendance system. As a result, first, the professors mostly were satisfied with the smart attendance system, and it would be necessary to improve learning ability and the function of self-management in connection with the learning management system. Second, the college students were dissatisfied with the user interface and speed of the smart attendance system, and it would be necessary to improve the delay time, login, update, and false attendance.

• Journal of The Korean Association of Information Education
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• v.4 no.2
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• pp.202-211
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• 2001

Learner-oriented education and distance education based on Information & Communication technology are educational countermeasure to various demands of Information age. Especially Web has the characteristics of providing proper environments for implementing constructivism study theory. Yet, existing web-based evaluation system is implemented by HTML and Java script so it has low interaction and imperfect educational effects. Therefore, We evaluated students' study understanding ability of real-time distance education system and analyzed evaluation results to offer useful information for level study considering individual variation. In this thesis, with these results, we designed and implemented interworking and multimedia databank system without time and space limitations on Client/Server environment.

• 한국정보교육학회:학술대회논문집
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• 2004.08a
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• pp.696-704
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• 2004

제7차 교육과정의 시행과 더불어 정부와 민간에서 모든 교과의 교수 학습에서 ICT를 활용할 수 있는 디지털 컨텐트를 다양하게 만들어 서비스하고 있으나 일관된 계획이나 표준안이 없이 필요에 따라 자료를 분류하여 만들어지다 보니 단위 수업 시간에 직접 투입하기에는 알맞은 자료를 검색하여 재가공을 하여 활용하거나 여과 없이 사용하게 되는 문제점이 제기되고 있다. 따라서, 본 연구에서는 단위 수업 중 자료투입시기를 분석하여 초등학교 교육환경에 필요한 메타데이터 요소를 탐색하고 메타데이터 요소를 추출하여 국제적인 메타데이터 표준인 DC Core Education 의 메타데이터 표준안을 기반으로 하는 멀티미디어 교육자료 검색 및 활용을 위한 베타데이터 요소를 추가 하였다. 초등교육 현장에서 생성되는 다양한 멀티미디어 교육 자료와 원상에 존재한 양질의 교육 정보 자원들을 일반적인 수업 흐름인 도입, 전개, 정리의 메타데이터 요소를 추가하여 통합검색과 체계적인 인터페이스를 제할 수 있는 기반을 마련함으로써 초등학교 교사가 쉽고 편리하게 단위 수업에 유용한 것을 찾아내고 수업에 투입할 수 있을 것이며 향후 교수학습 자료를 수업에 직접 필요한 형태로 분류하여 제공하여 효율적인 교수 학습 자료를 공유하게 함으로써 ICT활용 수업에 실제적인 도움을 줄 수 있을 것으로 기대된다.

• Proceedings of the Korean Society for the Gifted Conference
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• 2003.05a
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• pp.143-144
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• 2003

6차 교육과정부터는 과학 교육에서 학생들의 학습 목표를 과학 개념에 대한 이해 뿐 아니라 탐구 사고력 및 기능 향상도 중요한 목표로서 취급하고 있다(교육부, 1992). 그런데 학생의 탐구 사고력을 향상시킬 수 있는 과학교육이 제대로 이루어지지 못하고 있는 것이 현재의 실정이다. Schwab(1961)가 탐구 학습의 단계를 분류하면서 지적한 바 있듯이 탐구는 주어진 과제를 해결하는 고정적 탐구보다는 스스로 과제를 설정하고 이를 해결하려 하는 유동적 탐구가 더 바람직한 방향이며, 이러한 유형의 탐구를 통하여 학생들은 창의성의 신장과 함께 과학적탐구가 이루어지는 과정을 더 올바르게 이해할 수 있을 것으로 생각된다. 따라서 탐구의 상황을 학교 실험실만이 아닌 좀 더 생활 주변의 여러 가지 경험과 관련된 쪽으로 안내하는 것도 필요하다. 최근 활발한 컴퓨터의 보급과 인터넷 환경의 확대로 인하여 학생들이 이러한 환경에서 교사와 직접 동일한 시간, 동일한 장소에서 대면하지 않고도 의사소통하고 교수-학습이 이루어질 수 있는 기회가 사회적으로 가능해지고 있다. 이러한 원격교육은 교사의 안내에 따른 탐구 교수 형태의 개념 확인 및 검증 실험이 대부분인 전통적 과학학습 방법과 달리 학생 스스로 문제를 찾고 해결하려고 시도하는 것을 통하여 과학적 탐구 기능의 향상은 물론 과학적 개념의 획득, 과학, 사회, 기술에 대한 폭넓은 인식을 형성하는데 도움이 된다. 또한 인터넷 환경을 이용하면 학교 실험실 상황을 벗어나 학생들에게 다양한 탐구 활동 기회를 제공할 수 있고, 또한 그에 따른 의사 소통이 더 용이해질 수 있다. 이에 따라서 본 연구에서는 탐구 과정기술과 사고력을 중시하는 초등학교 과학과목의 특성을 고려하여 이에 적합한 인터넷 원격교수-학습을 위한 교수-학습 모형과 학생들의 과학적 탐구력과 사고력을 신장시킬 수 있는 멀티미디어 학습자료를 개발하고, 이를 실제적으로 적용할 수 있는 웹사이트를 개발, 현장에 적용하여 원격교수학습이 과학적 탐구력과 사고력에 미치는 효과에 대하여 조사하였다.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.409-418
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• 2015

This study was performed to develop and evaluate the effects of Team-Based Learning(TBL) on cardiac problem in adult nursing. The study measured problem-solving ability, critical thinking disposition, academic achievement and, class satisfaction for learning outcomes of course. Pretest-posttest design with nonequivalent control group was utilized to analyze the effects of TBL. Experimental group and control group each consisting of 52, 54 participants was picked from the junior students. The experimental group was given the TBL for 6 hours and control group was given a lecture and case-based announcement class. In results, significant improvements were found in problem-solving ability(F=5.92, p=.017), and class satisfaction(F=5.80, p=.018). Critical thinking disposition and academic achievement of experimental group were improved than those of control group, but there were not statistically significant difference.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.975-980
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• 2019

In this paper, we propose a deep learning-based scheduling scheme for user selection in multi-user multi-antenna networks which is considered one of key technologies for the next generation mobile communication systems. We obtained 90,000 data samples from the conventional optimal scheme to train the proposed neural network and verified the trained neural network to check if the trained neural network is over-fitted. Although the proposed neural network-based scheduling algorithm requires considerable complexity and time for training in the initial stage, it does not cause any extra complexity once it has been trained successfully. On the other hand, the conventional optimal scheme continuously requires the same complexity of computations for every scheduling. According to extensive computer-simulations, the proposed deep learning-based scheduling algorithm yields about 88~96% average sum-rates of the conventional scheme for SNRs lower than 10dB, while it can achieve optimal average sum-rates for SNRs higher than 10dB.

• Journal of Gifted/Talented Education
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• v.25 no.6
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• pp.905-926
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• 2015

This study examined differences among high, medium, and low achievers' motivation, self-regulation strategy, and learning style in an online gifted program. The sample included 788 middle and high school students who participated in the 3-months online gifted program. Participants volunteerly completed 60 questions on their motivation, self-regulation strategy use, and learning style. Multivariate analysis of variance(MANOVA) was conducted for data analysis using SPSS 19.0. The results of this study showed that (1) as levels of students' achievement increased, levels of intrinsic motivation increased as well; (2) statistically significant differences also existed on the levels of elaboration strategy, effort management, and time management strategy use among three levels of achievement and (3) no significant differences in students' learning style preference were found between competitive or cooperative learning style. To sum up, high achieving students' levels of intrinsic motivation, elaboration strategy, effort management strategy, and time management strategy use were the highest compared to medium and low achieving students.