• Journal of Korean Home Economics Education Association
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• v.33 no.2
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• pp.115-133
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• 2021

The purpose of this study is to develop a teaching-learning plans for middle school Home Economics that practices clothing life in response to climate change. Four steps of analysis, design, development, and evaluation were used for the research. 'Phenomenon and cause, impact (environmental, economic and social) and response (relaxation and adaptation)' were selected as educational content elements for climate change through reviewing the literature related to climate change. Six types of middle school Technology and Home Economics textbooks under the 2015 revised curriculum were analyzed using the selected content elements for climate change as the basis for analysis according to the data type(reading data, picture data, activity data) and clothing use cycle (production, purchase, use, and disposal). Based on the content elements of climate change in the clothing life area extracted through textbook analysis, a total of 12 teaching-learning plans in response to climate change were developed by utilizing various teaching and learning methods, data and media. The teaching-learning plans were designed based on an integrated understanding of the phenomena, causes, effects, and responses of climate change for the students to realize the seriousness of climate change and to exercise positive influence on families and society.

• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.934-950
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• 2009

This study attempts to identify the relationship between students' images of science and science learning, and their career choices. A total of 163 students (seventh graders) from three different middle schools participated in this study. Students' images of science and science learning were investigated using the Draw-A-Scientist Test (DAST) and the Draw-A-Science-Learner Test (DASLT), respectively. Then, students' drawings were analyzed using the Draw-A-Scientist Test Checklist (DAST-C) and the Draw-A-Science-Learner Test Checklist (DASLT-C). The relationship between each element composing the students' images and their career choices were analyzed. Among several elements constituting the students' image of science, 'expression,' 'lab coat,' 'oddity,' 'knowledge symbol,' 'technology symbol,' 'co-work,' 'danger,' and 'STS' showed significant differences between students who chose a science-related career and students who did not. It was also revealed that the following elements - 'expression,' 'learning type,' 'inquiry symbol,' and 'learning place' - were more significantly associated with a science-related career choice compared to other elements consisting of an image of science learning.

• Journal of Korean Elementary Science Education
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• v.43 no.3
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• pp.446-459
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• 2024

This study aims to examine the development and learning process of the argumentative abilities in elementary school students with regards to learning science. Toward this end, the SSI argumentation education program was implemented in conjunction with the science curriculum for sixth-grade students across 10 months. In this process, the scoring criteria in terms of formal and content aspects were developed and used to assess their argumentative text analysis and expression abilities. The results were as follows: First, the type of SSI influenced their ability to analyze argumentative texts. However, their formal and content aspects improved as learning progressed. Second, with regards to the formal aspect associated with the ability to express argumentative texts, reasons were initially most frequently cited. Over time, incorporating evidence to support these reasons and the use of rebuttal also increased. Third, in terms of content aspect, the level of use of all elements increased as learning progressed; however, level of acknowledgments and rebuttal elements exhibited a relatively slower progress. In summary, ability of the students to analyze and express argumentative texts improved as they increasingly gained experience in learning about argumentation. The study deduced that elementary school students can develop their argumentative abilities through appropriate learning support, such as teacher feedback, along with implementation of the SSI argumentation education program over an extended period. Based on these results, the study proposes the development of SSI materials and incorporation of SSI argumentative writing in the science curriculum.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.14-20
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• 2019

Energy saving is becoming more and more important issue due to lack of resources and limited nature. However, There is a lack of learning status on energy saving in the school field. In particular, in elementary education on energy saving was not linked to practice, and the educational effect was insufficient. Although various kinds of learning tools are utilized, many successful cases of energy saving game strategy are introduced in overseas industry field, and game design is proposed so that energy related education can be played through games. Because energy conservation can not be effective without practice, learning using games as a tool is expected to be more effective than learning based on knowledge transfer in the classroom. We propose a defense game for energy conservation education by using the mission elements, score acquisition element, time limit element, and character element which are the interesting elements of the game designed in the previous research.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.387-393
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• 2022

The article reflects short-term perspectives on the use of information and communication technologies in the training of teachers for higher education. Education is characterized by conservatism, so aspects of systematic development of the industry are relevant to this cluster of social activity. Therefore, forecasting the introduction of innovative elements of ICT training is in demand for the educational environment. Forecasting educational trends are most relevant exactly in the issues of training future teachers of higher education because these specialists are actually the first to implement the acquired professional skills in pedagogical activities. The article aims to consider the existing potential of ICT-based learning, its implementation in the coming years, and promising innovative educational elements that may become relevant for the educational space in the future. The tasks of scientific exploration are to show the optimal formats of synergy between traditional and innovative models of learning. Based on already existing experience, extrapolation of conditions of educational process organization with modeling realities of using information and communication technologies in various learning dimensions should be carried out. Educational trends for the next 3 years are a rather tentative forecast because, as demonstrated by the events associated with the COVID-19 pandemic, the socio-cultural space is very changeable. Consequently, the dynamism of the educational environment dictates the need for a value-based awareness of the information society and the practical use of technological advances. Thus, information and communication technologies are a manifestation of innovative educational strategies of today and become an important component along with traditional aspects of educational process organization. Future higher education teachers should develop a training strategy taking into account the expediency of the ICT component.

• Journal of Creative Information Culture
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• v.5 no.1
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• pp.63-70
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• 2019

In this paper, we analyzed 2015 revised curriculum for elementary school's practical art and middle school's information subject based on core competency. As a result, in 2015 revised curriculum for practical art subject, the ability to use information was well reflected in all achievement criteria and learning objectives. Also, problem solving ability and creativity·convergence ability were well reflected. In 2015 revised curriculum for information subject, the ability to use information was well reflected in all achievement criteria and learning objectives as like practical art subject. However, there were fewer learning elements to develop self-management ability. Therefore, it is proposed in this paper that the learning elements and teaching, learning activities and evaluation contents should be included in the SW curriculum, which can further enhance cooperative capabilities, self-management ability and communication ability.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.47-55
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• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.

• Journal of KIBIM
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• v.11 no.3
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• pp.22-33
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• 2021

In order to maximize the use of BIM, all data related to individual elements in the model must be correctly assigned, and it is essential to check whether it corresponds to the IFC entity classification. However, as the BIM modeling process is performed by a large number of participants, it is difficult to achieve complete integrity. To solve this problem, studies on semantic integrity verification are being conducted to examine whether elements are correctly classified or IFC mapped in the BIM model by applying an artificial intelligence algorithm to the 2D image of each element. Existing studies had a limitation in that they could not correctly classify some elements even though the geometrical differences in the images were clear. This was found to be due to the fact that the geometrical characteristics were not properly reflected in the learning process because the range of the region to be learned in the image was not clearly defined. In this study, the CRF-RNN-based semantic segmentation was applied to increase the clarity of element region within each image, and then applied to the MVCNN algorithm to improve the classification performance. As a result of applying semantic segmentation in the MVCNN learning process to 889 data composed of a total of 8 BIM element types, the classification accuracy was found to be 0.92, which is improved by 0.06 compared to the conventional MVCNN.

• Journal of the Korean earth science society
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• v.43 no.3
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• pp.464-479
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• 2022

In this study, appropriate geosites for geological field trips were explored and measures for their effective utilization in education were discussed, focusing on Okseo-myeon, Sanbuk-dong, Bieung-do, Yami-do, Sinsi-do, and Seonyu-do areas in Gunsan City, Korea. To this end, we analyzed the geological learning elements of the curriculum that were revised in 2015 and selected 7 geosites through field work based on prior research on the study areas. These areas have immense potential as a rich source of information on the Mesozoic geology of the Korean Peninsula, including igneous rocks formed as a consequence of Jurassic and Cretaceous igneous activities, Cretaceous sedimentary rocks, dinosaur footprints, plant fossils, ripple marks, and folds. When the learning elements available at the geosites were compared to those of the curriculum, they contained essentials used in high grade of elementary school and high school, and in particular, they had most of the learning elements used in high school. Accordingly, educational activities that can be carried out in each of the geosites in Gunsan City were proposed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.49-52
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• 1998

Neural Network has good performance in pattern classification, control and many other fields by learning ability. However, there is effective rule or systematic approach to determine optimal structure. In this paper, we propose a new method to find optimal structure of feed-forward multi-layer neural network as a kind of pruning method. That eliminating redundant elements of neural network. To find redundant elements we analysis error and weight changing with Rough Set Theory, in condition of executing back-propagation leaning algorithm.