• Korean Journal of Child Studies
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• v.25 no.6
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• pp.1-13
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• 2004

The purposes of this study were to investigate whether there were differences in the young children's abilities to use spatial coordinates and to represent spatial locations by children's age and sex, and to examine the relationship between these two abilities. It also explored whether the young children could use coordinates as the frames of reference for representing spatial locations. Seventy 5- and 6-year-old children from two kindergartens in Seoul and in Bucheon participated in this study. Results indicated that there were statistically significant differences between age groups on the children's ability to use spatial coordinates and to represent spatial locations. However, there were no significant differences between boys and girls on these two abilities. A positive correlation was found between theses two abilities of using spatial coordinates and representing spatial locations. Most of the young children used landmarks as the frames of reference to represent spatial locations while some of the children were partially able to use spatial coordinates. Twenty percent of 6-year-old children were fully able to use spatial coordinates as the frames of reference to represent spatial locations.

• School Mathematics
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• v.3 no.2
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• pp.447-473
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• 2001

Since the greater part of mathematical concepts have been developed in the direction of “from the concrete and realistic aspects to the abstract level”, children should be secured to learn mathematics genetically with various manipulative materials. The aim of this study is to instigate the active use of geoboards in mathematics classroom. To achieve this arm, we first embodied the several significances on the use of geoboards in mathematics instruction. And we then performed an instruction that children discover and justify the formula related to the area of trapezoid by exploring with geoboards, and analyzed the instructional episode to support our assertion about some secure merit accompanied by using geoboards. From this study, we obtained the conclusion that geoboard activity contains many significances such as children can explore congruence, symmetry, similarity, fundamental properties of figures, and pattern. Futhermore, geoboard activity enable children to transform a figure into other equivalently, develop spatial sense, have basic experiences for coordinate geometry, build a concrete model to explain abstract ideas, and foster the ability of problem solving and mathematical thinking.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.65-73
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• 2019

Recently commercial mixed-reality devices have be launched and a variety of mixed-reality content has produced, but narrow field of view, which appear to be hardware technical limitations, are mentioned as an important issue for hindering immersion and limiting the scope of use. We propose a new innovative system that cooperate multiple beam projectors and a number of mixed reality devices. Using this technology, users can maximize immersion and minimize frustration of narrow viewing angles through 3D object rendering on background of large 2D screens. This system, named BtS (Beyond the Sight), is implemented on a client-server basis and includes the ability to calibrate between devices, share spatial coordinate systems, and synchronize real-time renderings as core modules. In this paper, each configuration module is described in detail and the possibility of its performance and application is shown through the introduction of mixed reality content case created using BtS system.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.