• Journal of Science Education
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• v.41 no.3
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• pp.281-296
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• 2017

The purpose of this study is to explore the science learning motivation of technical high school students through comparison with general high school students. 596 high school students and 1063 general high school students participated in the study. Three statistical methods were used for data analysis: two-way ANOVA, independent sample t-test, and Pearson correlation analysis. The results showed that the interaction between school type and grade had a significant effect on the difference of students' motivation for science learning. There was a significant difference in learning motivation among general high school students according to academic year, while there was no significant difference between first and second grader of technical high school students. Especially, technical high school students showed low level of science learning motivation compared to the students in general high school. The correlations among five motivational factors of science learning motivation were also significantly lower than that of general high school students. Lastly, the result of correlation analysis between science motivation and academic achievement showed that second year students in technical high school had less correlation coefficients than the first year students. Given these results, it is necessary to develop a educational strategy for enhancing science learning motivation of technical school students. We will discuss the direction of science education for technical high school based on our findings.

• Journal of KIISE:Software and Applications
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• v.37 no.11
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• pp.837-844
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• 2010

Prediction of the prosodic phrase boundary is one of the most important natural language processing tasks. We propose, for the natural prediction of the Korean prosodic phrase boundary, a statistical approach incorporating efficient learning features. These new features reflect the factors that affect generation of the prosodic phrase boundary better than existing learning features. Notably, moreover, such learning features, extracted according to the hand-crafted prosodic phrase boundary prediction rule, impart higher accuracy. We developed a statistical model for Korean prosodic phrase boundaries based on the proposed new features. The results were 86.63% accuracy for three levels (major break, minor break, no break) and 81.14% accuracy for six levels (major break with falling tone/rising tone, minor break with falling tone/rising tone/middle tone, no break).

• Phonetics and Speech Sciences
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• v.12 no.3
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• pp.55-63
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• 2020

Voice conversion can be applied to various voice processing applications. It can also play an important role in data augmentation for speech recognition. The conventional method uses the architecture of voice conversion with speech synthesis, with Mel filter bank as the main parameter. Mel filter bank is well-suited for quick computation of neural networks but cannot be converted into a high-quality waveform without the aid of a vocoder. Further, it is not effective in terms of obtaining data for speech recognition. In this paper, we focus on performing voice-to-voice conversion using only the raw spectrum. We propose a deep learning model based on the transformer network, which quickly learns the voice conversion properties using an attention mechanism between source and target spectral components. The experiments were performed on TIDIGITS data, a series of numbers spoken by an English speaker. The conversion voices were evaluated for naturalness and similarity using mean opinion score (MOS) obtained from 30 participants. Our final results yielded 3.52±0.22 for naturalness and 3.89±0.19 for similarity.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.3
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• pp.267-276
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• 2021

The purpose of this study is to research seasonal constellation experiments and to find out what are effective seasonal constellation experiments according to school salary. we organized seasonal constellation experiments with 24 elementary preparatory teachers and asked them to what effective experiments are for each school class. As a result, constellation learning through direct experience activities through role play is the most effective in elementary school, and in middle and high schools, using the stellarium program to realistically observe and reason about seasonal changes in constellations was selected as an effective experiment. Pre-service teachers recognized that experiments in which direct experience and specific manipulation activities were emphasized in elementary school, and experiments in which observation of realistic natural phenomena and reasoning activities were emphasized were effective in middle and high schools.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.32-40
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• 2009

This research provides a new approach for implementing an educational content for Historic Education in order to provide an effective learning environment. From historic educational point of view, it is important to comprehend a historical fact in the context of the situation at that time. So, this paper suggests that the historic content should describe not only information about various relics and ruins but also historical relationship and background. In this system, we provide versatile type of contents to help learners for collecting manifold informations about their interesting era. And this system proffers natural and residential 3D environments, which give learners to understand conceivably and to think collectively. Using the interactions, the learners navigating this virtual world are able to construct their own information system through selecting a interested one among the offered contents in the system and consequently they are getting a scientific thinking power and a creative imagination.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.465-472
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• 2022

In this paper, the style synthesis network is trained to generate style-synthesized video through the style synthesis through training Stylegan and the video synthesis network for video synthesis. In order to improve the point that the gaze or expression does not transfer stably, 3D face restoration technology is applied to control important features such as the pose, gaze, and expression of the head using 3D face information. In addition, by training the discriminators for the dynamics, mouth shape, image, and gaze of the Head2head network, it is possible to create a stable style synthesis video that maintains more probabilities and consistency. Using the FaceForensic dataset and the MetFace dataset, it was confirmed that the performance was increased by converting one video into another video while maintaining the consistent movement of the target face, and generating natural data through video synthesis using 3D face information from the source video's face.

• Journal of Gifted/Talented Education
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• v.11 no.3
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• pp.23-44
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• 2001

In the current classrooms a teacher has been merely able to inculcate the procedural knowledge of how-and-what. In doing so, however, we lose sight of the essence of "doing science."Though desire of the gifted children is qualitatively different from that of normal children, it is an undesirable reality that we have not developed sufficient researches and programs in conformity with the necessary desire and demand of the gifted children. Curriculum for gifted children in the domain of science necessitates markedly the specializations for the specific areas of the contents, the processes, and the products of studies. In an effort to provide the optimum learning experience for the gifted, this paper deals with the development of project-and-discovery-based science program, its method of application to the real field of education, and its effect, however limited and partial that effect may be. What this study has found are the following: on the one hand, the students acquired and developed the higher levels of thinking when they were under the influence of project-and-discovery-based science program that dealt with concrete real-world problems and issues; on the other, the students were capable of solving creatively the complex and real problems through small group activities. This study also suggests the possible implications of project-and-discovery-based science program: the students can not only learn the contents of study but also apply them creatively; the students can cultivate critical thinking skills that can be a fundamental base for a life-time leaner; the students can naturally acquire the abilities of communication and coordination. Project-and-discovery-based program is currently used in the various disciplines. However, the field of gifted education does not yet implement this type of program. So the overall contribution of this study is to show the successful implementation of project-and-discovery-based science program in developing optimal teaming experience for gifted children in the domain of science, since this type of study is most compatible with the characteristic of the gifted children. children.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.613-618
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• 2012

ICT education guidelines revised in 2005 reinforce computer science elements such as algorithm, data structure, and programming covering all schools. And Ministry of Education emphasizes STEAM education. Most important is that "How instruct them". This means necessity of contents. So this paper suggests learning method of Stack and Queue using LEGO MINDSTORMS NXT. The main purpose is that how stack and queue are used, when robot explore realistic maze. Teaching and learning strategies are algorithm, flowchart, and NXT-G programming. Simple maze has path in left or right, but complex maze has three-way intersection. These are developed by authors. Master robot explores maze and push stack, and then return to entrance using stack. Master robot explores maze and transmits path to slave's queue. And then slave robot drives without exploration. Students can naturally learn principles and applications of them. Through these studies, it can improves ability of logical and creative thinking. Furthermore it can apply to ICT and STEAM education.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.331-339
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• 2017

Mathematics has kept the relationships with other studies constantly. However, there is not many researches about the integrated teaching-learning materials for mathematics. In this paper, we review the integrated learning theories and domestic research trends of the integrated learning for the mathematics. Through the literature review, we survey the integrated teaching-learning materials, which integrate the mathematics and other subjects for the secondary school. As a result, it can be seen that integrated teaching-learning materials of mathematics and science, social studies, arts, physical education, and korean literature have recently been developed to help raise awareness of the usefulness of mathematics. Further study on the revision and supplementation of these materials should be carried out based on this paper.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.11-11
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• 2020

18년 물관리일원화 이후 인프라와 사람 중심으로부터 자연과 인간의 조화를 위한 환경·생태계의 자연성 회복으로의 물관리 패러다임 전환이 빠르게 이루어지고 있으며, 대규모 국책사업이후의 하천 관리에 있어서도 기존의 이수, 치수, 환경이라는 단순한 기능적 구분을 벗어나 보다 근본적이고 장기적인 대국민 서비스로의 전환을 도모하고 있다. 또한, ICBAM 등으로 정의되는 4차산업혁명 기반 기술의 접목이 거의 대부분의 분야에서 이루어지고 있는 것을 실질적으로 체감하는 시기가 도래하였다. 그러나, 하천 및 수자원 관리분야에서의 기술은 근대 엔지니어링의 기초가 되는 수로 건설 등으로부터 시발되어 사실상 가장 앞선 과학적 진보의 토대를 갖추었으나 최근의 기술적 트렌드를 잘 추종하지 못하는 것처럼 비추어 지는 것이 사실이다. 주된 이유로서 기후변화라는 광범위하고 장기적인 입력요소를 가진 하천관리 시스템의 특성상 불확실성의 추정 및 즉각적인 응답이 어려운 부분이 분명히 존재하지만, 실질적으로 여전히 해소되지 않는 부분은 하천의 기초자료 수집에 대한 효율성과 신뢰도가 낮은 것이라고 하겠다. 또한, 유역으로부터 댐-다기능보-하천으로 이어지는 의사결정을 위한 다양한 형태의 자료로부터 적절한 정보를 수집하는 체계(거버넌스의 문제이자 기술적/재정적 한계)가 확립되지 않은 점도 고려해야 할 것이다. 본 연구에서는 인공지능을 활용한 하천의 유량 예측 등을 위해 필요한 수자원 기초데이터의 근원적인 수집 및 관리상의 문제점에 대해서 검토하고자 하였으며, ARIMA, Kalman Filtering, MA 및 복합기법을 통한 자료처리 기법을 적용하여 상황에 맞게 오차 및 불확실성의 저감을 위한 방안을 찾고자 하였다. 또한, 이용자 중심의 하천 관리에 근접한다고 볼 수 있는 스마트워터시티 개념에서의 바람직한 하천관리 기법에 대해서 논의하고, 관련하여 근자에 개발한 하천의 물리적 해석 도구들에 대해서 적용 사례를 검토한다. 마지막으로, 지식기반의 하천관리 의사결정 플랫폼 개발을 위해서 기존의 기계학습을 통한 자동화된 의사결정에 부가하여 전문가와 시스템이 상호작용을 통해서 AI를 학습시켜 결정한 사항을 전문가의 의사결정에 참고하는 MCRDR기법의 적용의 적용 가능성과 도입 방향에 대해서 논의하였다.