• Journal of Digital Convergence
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• v.14 no.5
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• pp.473-483
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• 2016

This study examines the relationship between sport confidence, exercise passion and re-participation intention of collegiate students participating in snow-ski class. The subjects for this study were 416 collegiate students who signed up for snow-ski class as a university curriculum. The reliability and validity test of the questionnaire were conducted by using SPSS & AMOS Window 18.0 program; the results of descriptive analysis, factor analysis, correlation analysis, structural equation model are as follows; First, sport confidence of collegiate students in ski-class affects their exercise passion. Second, sport confidence of collegiate students in ski-class has influence on their re-participation intention. Third, collegiate students' exercise passion in ski-class affects their re-participation intention. Lastly there is a causal relationship between sport confidence, exercise passion and re-participation intention of collegiate students in the snow-ski class.

• The Journal of Korean Association of Computer Education
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• v.16 no.3
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• pp.49-60
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• 2013

This study is aimed to investigate that the blended e-learning could enhance the effectiveness compared to the conventional lecture performed in classroom. At first, both the CbE(Class based E-learning) and the EbC(E-learning based Class) mode have been generated in blended e-learning operation method following the process which analyze the various studies of interest. In addition, the instruction structures of Z Type(Zigzag model) and H-Type(Ladder model) were established as proposed model. The H-Blended e-learning based on CbE mode was introduced in the Excel Spread Sheet subject which held in A University to achieve the goal of this study. Learners were categorized and belonged to either the group 1(over 50% of attendance in cyber lecture) or the group 2(the rest of them). The data analysis was performed with $x^2$-test, t -test to compare the achievement of study between groups. The t -test result showed that the academic achievement in learning with group 1 was statistically significant than the learner in group 2. The effectiveness of the blended e-learning has been proved as the logistic regression analysis showed that the rate of the attendance in the cyber lecture functioned as indicator that enable to predict the acceptance.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.837-849
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• 2019

Latent class models (LCM) are useful tools to draw hidden information from categorical data. This model can also be interpreted as a mixture model with multinomial component distributions. In some cases, however, an available dataset may contain both categorical and count or continuous data. For such cases, we can extend the LCM to a mixture model with both multinomial and other component distributions such as normal and Poisson distributions. In this paper, we consider a LCM for the data containing categorical and count data to analyze the Drug Review dataset which contains categorical responses and text review. From this data analysis, we show that we can obtain more specific hidden inforamtion than those from the LCM only with categorical responses.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.259-267
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• 2020

The purpose of this study is to analyze the effects of computational thinking class using ARCS model to increase students' learning motivation. Then, this study designed the detailed instruction strategy according to each motivation factor(Attention, Relevance, Confidence, Satisfaction) of ARCS through the previous study on computational thinking education and ARCS model. The results of the ARCS test were compared between the experimental group to which the ARCS model was applied and the control group to which the general class was conducted. As a result, students in the experimental group showed significantly higher motivation for learning about computational thinking. In particular, the learning motivation of computer-related majors was significantly higher than that of the control group. In addition, majors were found to have high relevance(R) and non-majors had high satisfaction(S). Therefore, based on these findings, this study suggests an improvement for effective computational thinking class in liberal arts education.

• Journal of Technologic Dentistry
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• v.39 no.4
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• pp.263-273
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• 2017

Purpose: This study aimed to explore the relations between class distracting factors and class satisfaction of the dental technology students and then provide a primary data to help further related studies and develop educational programs with which instructors can efficiently manage their classroom. Methods: For this study we have conducted a survey started from the beginning of May 2017 to the end of June. The subjects of the survey were Dental Technology students of D-city, K-city, W-city, selected by random sampling method. The questionnaire was self-administrated and 437 valid results were chosen for our analysis among 450 distributed questionnaires. Results: The results of the research was as follows. Firstly, The overall average point of class distracting factors was 2.5 point. The environmental factors were the highest point as 2.59 and as for the subcategories tiredness and drowsiness was the highest point as 2.76. Secondly, The overall average point of class satisfaction turned out 3,88 point and compliance with class and attitude factors gained the highest point as 4.06. Of the subcategories strict roll checking was the highest point as 4.17. Thirdly, As for class distracting factors from general characteristics a statistical significance was shown as follows; 'instructor factor'(p<.01), 'learner factor'(p<.05), 'total class distracting factor'(p<.05) in the area of gender, 'environmental factor'(p<.001), 'total class distracting factor'(p<.01), 'learner factor'(p<.05), 'instructor factor'(p<.05) in the area of gender 'learner factor'(p<.001), 'instructor factor'(p<.001), 'environmental factor'(p<.001), 'total class distracting factor'(p<.01) in the area of class grade, 'environmental factor'(p<.05) in GPA. Fourthly, A statistical significance, a negative correlation (p<.01) were shown between class distracting factors and class satisfaction. Class distracting factor that especially affects the class satisfaction was instructor factor(p<.001) and the explanatory power of the model turned out 14.7%, which was statistically meaningful (p<.001). Conclusion : Results of this study reveal that instructor factor is the key to class satisfaction of the students. So it is crucial that the instructor faithfully prepare for the class to reinforce the students' learning. Additionally further studies should be followed with more subjects and newer perspectives to develop innovative teaching methodology.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.495-506
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• 1998

The proposed class of generalized logistic models, indexed by an extra parameter, can be used to model or to examine symmetric or asymmetric discrepancies from the logistic model. When there are a finite number of different design points, we are mainly concerned with maximum likelihood estimation of parameters and in deriving their large sample behavior A score test and a bootstrap hypothesis test are also considered to check if the standard logistic model is appropriate to fit the data or if a generalization is needed .

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.173-177
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• 2020

In this study, the side doors of mid-size sedan vehicles of models A and B which are currently prone to rollover accidents are compared with each other by the structural analyses. As a result of the structural analysis, both models showed the maximum deformation at the point of overturning or impact load, and the model A of the two models was able to withstand greater impact load compared to the model B. In addition, the maximum stress happened at the door edge, and model B was 2.5 times more stressed than model A. In the accident of a crash, model A, which has the smaller maximum stress, is able to withstand greater impact loads than model B. Since model B has a larger deformation than model A, it is considered to be more dangerous than model A in the side impact accident. By applying the impact analysis of automotive side door by the class of vehicle, the study result at this paper is considered to be favorable as the convergent research material which can apply the aesthetic design.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.891-891
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• 2002

Currently there are numerous papers in which many new kinds of customizing stereotypes by UML extension mechanism for different application environments such as real-time system, Geographic Information System (GIS) and so on are proposed. However , these stereotypes that represent different type model elements such as class, association, generalization and so on have not yet been seen in one of the most popular visual modeling tool for software development, Rational Rose. Therefore, in this paper, a design of extended iconic stereotype for GNSS application in the UML class diagram and its implementation as a tool of StereotypeCreator for Rational Rose will be presented.

• Journal of the Semiconductor & Display Technology
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• v.12 no.3
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• pp.53-57
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• 2013

Human emotions are expressed in various ways. It can be expressed through language, facial expression and gestures. In particular, the facial expression contains many information about human emotion. These vague human emotion appear not in single emotion, but in combination of various emotion. This paper proposes a emotional expression algorithm using Active Appearance Model(AAM) and Fuzz k- Nearest Neighbor which give facial expression in similar with vague human emotion. Applying Mahalanobis distance on the center class, determine inclusion level between center class and each class. Also following inclusion level, appear intensity of emotion. Our emotion recognition system can recognize a complex emotion using Fuzzy k-NN classifier.

• Progress in Superconductivity and Cryogenics
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• v.16 no.2
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• pp.47-53
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• 2014

In this paper, the general electromagnetic design process of a 10-MW-class high-temperature superconducting (HTS) synchronous generator that is intended to be utilized for large scale offshore wind generator is discussed. This paper presents three-dimensional (3D) electromagnetic design proposal and electrical characteristic analysis results of a 10-MW-class HTS synchronous generator for wind power. For more detailed design by reducing the errors of a two-dimensional (2D) design owing to leakage flux in air-gap, we redesign and analyze the 2D conceptual electromagnetic design model of the HTS synchronous generator using 3D finite element analysis (FEA) software. Then electrical characteristics which include the no-load and full-load voltage of generator, harmonic contents of these two load conditions, voltage regulation and losses of generator are analyzed by commercial 3D FEA software.