• Journal of Gifted/Talented Education
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• v.15 no.1
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• pp.37-48
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• 2005

Comparing to the other subject, the relationship among physics contents is strong from the perspective of knowledge order as grades go up. That is, The things already that students learned, are learning and will learn are closed related from grade to grade. We expect students to be proactive and creative in studying physics, which is the goal of 21th century, analyzing their knowledge structure based on the knowledge order through assessment. Especially, using computer system, we provide students with substantial feedback for the assessment as well as objective validity is increased along with speedy and exact process in a bid to help students' mathematical understanding grow. This paper seeks to analyze the data from assessment applying knowledge spaces of the scientifical gifted in selective examination and to applicate on development of evaluation method.

• Journal of Gifted/Talented Education
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• v.20 no.3
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• pp.1027-1037
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• 2010

Comparing to the other subject, the relationship among physics contents is strong from the perspective of knowledge order as grades go up. That is, The things already that students learned, are learning and will learn are closed related from grade to grade. We expect students to be proactive and creative in studying physics, which is the goal of 21th century, analyzing their knowledge structure based on the knowledge order through assessment. Especially, using computer system, we provide students with substantial feedback for the assessment as well as objective validity is increased along with speedy and exact process in a bid to help students' mathematical understanding grow. This paper seeks to analyze the data from assessment applying knowledge spaces of the scientifical gifted in the force and the motion concept to applicate on teaching method.

• Informatization Policy
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• v.28 no.1
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• pp.43-63
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• 2021

The purpose of this research is to examine the relationships among data literacy, organizational culture, and data analytics maturity and the moderating effects of organizational culture. Analysis of the relationship between data literacy and data analytics maturity shows that the higher the data literacy competency of employees, the higher the organization's data analytics maturity. In examining the relationship between organizational culture and data analytics maturity, it is found that relationship culture and innovation culture are positively related to data analytics maturity. In addition, relationship culture and hierarchy culture show significant moderating effects. Relationship culture shows a synergistic effect, whereas hierarchy culture has a buffer effect between data literacy and data analytics maturity.

• Journal of the Korean earth science society
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• v.23 no.4
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• pp.349-356
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• 2002

In an effort to properly assess the validity of spaceborne radar altimeter measurements, we made a direct comparison of two different sea surface heights (SSH) acquired by both Topex/Poseidon (T/P) satellite and in-situ tide-gauges (T/G). This comparative analysis was conducted using the data sets collected from three locations along the eastern coast of Korea which include: Ulleungdo, Pohang, and Sokcho. In the course of the analysis of satellite altimeter, information of SSH was extracted from the T/P MGDR data sets through the application of both atmospheric and geophysical corrections. To compare the T/P data sets in parallel basis, the T/G data sets were averaged using the measured values within the peripheral radius of 55km. When compared among different locations, the compatibility between the two methods was much more significant in an offshore location (Ulleungdo) than the two onshore locations (Pohang, Sokcho). If the low-pass filtered results were compared among the sites, the offshore site exhibited the best correlations between the two methods (correlation coefficient of 0.91) than those of the onshore sites. These large differences in the strength of correlations among different locations are due to the deformation of M2, S2, and K1 tidal components used in the tidal model. In case of the offshore location, the compatibility of the two different methods were improved systematically by the low-pass filtering with an increase of the filtering duration such as up to 200 days.

• Information Systems Review
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• v.21 no.4
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• pp.69-97
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• 2019

Knowledge service firms are able to have higher 'Organizational Performance (OP)' by improving efficiency in management processes on customer problem solving. This study explores the role of inefficiency that has been overlooked up to now compared to the management process efficiency. We also suggest in this study 'Hierarchical Culture (HC)' and 'IT Relatedness (IR)' as the factors influencing the inefficiency of management processes, and propose the moderating effect of 'Task Difficulty (TD)' on the relationship between independent factors and 'Inefficiency of Business Process(IP)'. The results of analysis show that 'HC' has a positive effect on 'IP', and 'IR' has a negative effect on 'IP'. 'TD' was significant moderator of between independent variables and 'IP'. 'IP' was shown to play a full mediating role between independent factors and 'OP'. In conclusion, knowledge service firms are desired to reduce 'HC' and enhance 'IR' by minimizing unnecessary formal procedures, securing flexibility in decision making through appropriate empowerment, creating a smooth flow of knowledge, and enhancing the level of IT resource management and utilization. In addition, in order to effectively reduce 'IP', it is required that a company with a high degree of 'TD' to more reduce a 'HC' and a company with a low degree of 'TD' to more enhance a 'IR'.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.7-18
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• 2006

Nowadays, the movement of commercial vehicles has caused severe congestion, environmental problems and damaged pavements in urban area. To solve the Problems, this research has proposed a methodology to build-up a freight network that is enable to manage the movement and demand of commercial vehicles. The network based on urban arterial network has developed according to freight traffic volume that is under the influence of road types among The in study area. Freight network has been developed by assignment method of 4-step transportation forecasting. Once, acceptable limits of freight traffic volume are decided, freight network can be developed using the capacity To confirm the application of the methodology, freight network of Seoul city has developed by the methodology.

• Knowledge Management Research
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• v.22 no.3
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• pp.129-149
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• 2021

Research on social hierarchy is a growing research topic in the studies of management and organization. Despite the abundance of studies demonstrating the relevance of social hierarchy in teams, little understanding exists for status disagreement among team members, specifically how status disagreement reduces team members' contributions to influence team performance. This conceptual study argues that team status disagreement negatively impacts team performance through reduced team member's knowledge contribution, including reduced team knowledge sharing and increased knowledge hiding. In addition, we propose that team skill differentiation aggravates the negative effect of status disagreement, such that when team skill differentiation is high, teams under high status disagreement are more likely to experience detracted team performance. This research mainly discusses status disagreement and its effect on team knowledge contributions by reviewing previous literature and developing several propositions, suggests theoretical contributions and practical implications, and presents an agenda for future research.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.65-75
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• 2015

This paper analyzes the determinants of wage for the college and university graduates utilizing both individual-level and industry-level variables. We note that wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and industry-level (level-2) variables. Then, the assumption that individual wage is independent in the classical regression is violated. Therefore, this paper utilizes the hierarchical linear model (HLM). The major results are the followings. First, the multiple correspondence analysis including level-1 and 2 variables reveals that both level 1 and level 2 variables affects individual wages judging from the fact that the values of level 1 and level 2 variables differ across the different level of individual wage groups. Second, the decision tree analysis including level-1 and 2 variables shows that the most influential variable in wage determination is industry-level wage and the next is industry-level working hour, ages and sex in the decling order in. This suggests that the utilization of the HLM is appropriate since the characteristics of industry is important in determining the individual wage. Third, it is shown that the HLM model is the best compared to the other models which do not take level-1 and level-2 variables simultaneously into account.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.79-84
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• 2021

A feature extraction method capable of reflecting features well while mainaining the properties of data is required in order to process high-dimensional data. The principal component analysis method that converts high-level data into low-dimensional data and express high-dimensional data with fewer variables than the original data is a representative method for feature extraction of data. In this study, we propose a principal component analysis method based on adaptive correlation when selecting principal component variables in principal component analysis for data feature extraction when the data is high-dimensional. The proposed method analyzes the principal components of the data by adaptively reflecting the correlation based on the correlation between the input data. I want to exclude them from the candidate list. It is intended to analyze the principal component hierarchy by the eigen-vector coefficient value, to prevent the selection of the principal component with a low hierarchy, and to minimize the occurrence of data duplication inducing data bias through correlation analysis. Through this, we propose a method of selecting a well-presented principal component variable that represents the characteristics of actual data by reducing the influence of data bias when selecting the principal component variable.

• Journal of The Korean Association For Science Education
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• v.27 no.4
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• pp.346-353
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• 2007

In order to be efficient in teaching, a teacher should understand the current learner's level through diagnostic evaluation. This study has examined the major issues arising from the noble diagnostic assessment tool based on the theory of knowledge space. The knowledge state analysis method is actualizing the theory of knowledge space for practical use. The knowledge state analysis method is very advantageous when a certain group or individual student's knowledge structure is analyzed especially for strong hierarchical subjects such as mathematics, physics, chemistry, etc. Students' knowledge state helps design an efficient teaching plan by referring their hierarchical knowledge structure. The knowledge state analysis method can be enhanced by computer due to fast data processing. In addition, each student's knowledge can be improved effectively through individualistic feedback depending on individualized knowledge structure. In this study, we have developed a diagnostic assessment test for measuring student's learning outcome which is unattainable from the conventional examination. The diagnostic assessment test was administered to middle school students and analyzed by the knowledge state analysis method. The analyzed results show that students' knowledge structure after learning found to be more structured and well-defined than the knowledge structure before the learning.