• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.49-59
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• 2022

This study was conducted to develop a teaching competency scales customized for teaching programs conducted by Center for Teaching & Learning at A University. To achieve this purpose, a preliminary study was set up, which consists of three competency groups (basic competency, practice competency, innovation competency) and 26 learning competency factors through a review of previous studies. In order to verify the reliability and validity of the provisional teaching competency scales, an online survey was conducted on A university teachers in September 2020, The collected questionnaire data were organized and exploratory factor analysis and confirmatory factor analysis were conducted. As a result of exploratory factor analysis, 26 teaching competency was reduced to 17. As a result of the confirmatory factor analysis, the model was found to be good, Also, as a result of analyzing the construct reliability and AVE of the confirmed teaching competency factors, all 17 factors showed a good level of .7 or more. The teaching competency scales developed through this study can be used as basic data for performance evaluation and development of new programs of CTL teaching program.

• Journal of Korean Academy of Nursing
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• v.43 no.5
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• pp.587-594
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• 2013

Purpose: The purpose of this study is to provide researchers with a simplified approach to undertaking exploratory factor analysis for the assessment of construct validity. Methods: All articles published in 2010, 2011, and 2012 in Journal of Korean Academy of Nursing were reviewed and other relevant books and articles were chosen for the review. Results: In this paper, the following were discussed: preliminary analysis process of exploratory factor analysis to examine the sample size, distribution of measured variables, correlation coefficient, and results of KMO measure and Bartlett's test of sphericity. In addition, other areas to be considered in using factor analysis are discussed, including determination of the number of factors, the choice of rotation method or extraction method of the factor structure, and the interpretation of the factor loadings and explained variance. Conclusion: Content validity is the degree to which elements of an assessment instrument are relevant to and representative of the targeted construct for a particular assessment purpose. This measurement is difficult and challenging and takes a lot of time. Factor analysis is considered one of the strongest approaches to establishing construct validity and is the most commonly used method for establishing construct validity measured by an instrument.

• Journal of Korean Clinical Health Science
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• v.6 no.2
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• pp.1126-1135
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• 2018

Purpose. The purpose of this study is to investigate the success model related to the hospital information system accomplishment. It is important to examine the success model of the hospital information system and to analyze the factors affecting the job satisfaction accomplishment. Methods. The method of this study is to 150 copies of the entire survey data were distributed and 135 copies were collected, showing a collection rate of 90%. In order to ensure the reliability of the questionnaire items, Cronbach's Alpha was used to test reliability, and exploratory factor analysis was conducted to determine the convergence of various items. In order to grasp the convergence of various items, exploratory factor analysis was performed. The results of exploratory factor analysis were used to analyze the correlations between variables that were proven to have a single dimensionality before calculating factor loadings and regression analysis by Orthogonal Rotation by Varimax method Results. The results of this study, first, the system quality of the hospital information system has a statistically significant effect on user satisfaction. Second, the information quality of hospital information system is statistically significant for user satisfaction, indicating that information quality improves user satisfaction. Third, service quality of hospital information system was statistically significant in user satisfaction. Finally, the higher the satisfaction of the users who use the hospital information system, the higher the accomplishment of the organization Conclusions. This study is based on the successful model of D & M information system. In addition, the hospital information system, the user satisfaction, and the organizational accomplishment in connection with it can be found significant.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.100-106
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• 2022

A longitudinal study refers to a research method based on longitudinal data repeatedly measured on the same object. Most of the longitudinal analysis methods are suitable for prediction or inference, and are often not suitable for use in exploratory study. In this study, an exploratory method to analyze longitudinal data is presented, which is to find the longitudinal trajectory after determining the best number of clusters by clustering longitudinal data using self-organizing map technique. The proposed methodology was applied to the longitudinal data of the Employment Information Service, and a total of 2,610 samples were analyzed. As a result of applying the methodology to the actual data applied, time-series clustering results were obtained for each panel. This indicates that it is more effective to cluster longitudinal data in advance and perform multilevel longitudinal analysis.

• Nutrition Research and Practice
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• v.16 no.4
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• pp.517-526
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• 2022

BACKGROUND/OBJECTIVES: The increased consumers' interests in health and food safety have increased the demand for organic foods. Many studies have been performed on consumers' purchase intentions for organic foods and their influencing factors, and various studies have shown that the prices of organic foods and the consumers' willingness to pay are important influencing factors. This study examined the payment value of organic foods and agrifood consumer competency index according to the food-related lifestyles in South Korean consumers. SUBJECTS/METHODS: A cross-sectional analysis was performed using the 2019 Consumer Behavior Survey for Food. A total of 6,176 participants aged 19 to 74 years (male: 2,783, female: 3,393) were included in the analysis. RESULTS: Three factors were extracted by factor analysis (rational consumption-seeking type, convenience-seeking type, and health, and safety-seeking type) to explain the consumers' food-related lifestyles. The results of cluster analysis suggested that consumers were classified into 3 food-related lifestyles as the 'exploratory consumers' (n = 2,485), 'safety-seeking consumers' (n = 1,544), and 'passive consumers' (n = 2,147). Exploratory consumers showed a significantly higher willingness to pay for imported organic foods (P < 0.05). Safety-seeking consumers had a significantly higher willingness to pay for domestic organic foods (P < 0.05). For the agrifood consumer competency index, exploratory consumers had the highest score, followed in order by safety-seeking consumers and passive consumers. CONCLUSIONS: These results provide basic data in understanding consumption tendency for organic foods and agrifoods based on food-related lifestyles of South Korean consumers.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.87-102
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• 2024

Digital transformation refers to the process by which a company or organization changes or innovates its existing business model or sales activities using digital technology. This requires the use of various digital technologies - cloud computing, IoT, artificial intelligence, etc. - to strengthen competitiveness in the market, improve customer experience, and discover new businesses. In addition, in order to derive knowledge and insight about the market, customers, and production environment, it is necessary to select the right data, preprocess the data to an analyzable state, and establish the right process for systematic analysis suitable for the purpose. The usefulness of such digital data is determined by the importance of pre-processing and the correct application of exploratory data analysis (EDA), which is useful for information and hypothesis exploration and visualization of knowledge and insights. In this paper, we reexamine the philosophy and basic concepts of EDA and discuss key visualization information, information expression methods based on the grammar of graphics, and the ACCENT principle, which is the final visualization review standard, for effective visualization.

• Journal of the Korea Safety Management & Science
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• v.26 no.2
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• pp.23-31
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• 2024

In the military, ammunition and explosives stored and managed can cause serious damage if mishandled, thus securing safety through the utilization of ammunition reliability data is necessary. In this study, exploratory data analysis of ammunition inspection records data is conducted to extract reliability information of stored ammunition and to predict the ammunition condition code, which represents the lifespan information of the ammunition. This study consists of three stages: ammunition inspection record data collection and preprocessing, exploratory data analysis, and classification of ammunition condition codes. For the classification of ammunition condition codes, five models based on boosting algorithms are employed (AdaBoost, GBM, XGBoost, LightGBM, CatBoost). The most superior model is selected based on the performance metrics of the model, including Accuracy, Precision, Recall, and F1-score. The ammunition in this study was primarily produced from the 1980s to the 1990s, with a trend of increased inspection volume in the early stages of production and around 30 years after production. Pre-issue inspections (PII) were predominantly conducted, and there was a tendency for the grade of ammunition condition codes to decrease as the storage period increased. The classification of ammunition condition codes showed that the CatBoost model exhibited the most superior performance, with an Accuracy of 93% and an F1-score of 93%. This study emphasizes the safety and reliability of ammunition and proposes a model for classifying ammunition condition codes by analyzing ammunition inspection record data. This model can serve as a tool to assist ammunition inspectors and is expected to enhance not only the safety of ammunition but also the efficiency of ammunition storage management.

• Journal of Digital Convergence
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• v.6 no.2
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• pp.41-53
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• 2008

This research is to redefine the concept of Good School and to validate an effective Good Secondary School Scale in Kyung-gi Province and Seoul. As statistical methods, SPSS 13.0 and AMOS 5.0 were used. Item Analysis and Exploratory Factor Analysis(EFA) were conducted to test the reliability of items and the factor structure. And Confirmatory Factor Analysis(CFA) was conducted to test the validity and fitness of the Good School Scale. The outcomes are as follows: First, six factors(school environment, curriculum, teacher, school-based management system, director) will increase the good schooling effectiveness. Second, As a result of Confirmatory Factor Analysis(CFA), the goodness of fit indices(GFI AGFI, CFI, RMSEA) demonstrate statistically significance and fitness of the model. The final Good School Scale supports 6 Good School Factors obtained in main test. Therefore, we can say that this scale can be used as a valid instrument to measure a real Good Schooling Effectiveness at the secondary school situation in Korea.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.227-237
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• 2014

We use the regression model with the indicator variables in the case that we use qualitative variables as some predictor variables in regression analysis. We use the ANCOVA(Analysis of Covariance) model when comparing the response variable among groups while statistically controlling for variation in the response variable caused by a variation in the covariate. DD-plot can be used as a graphical exploratory data analysis tool before the confirmatory data analysis. With the DD-plot, we can discriminate the difference of groups in the regression model with the indicator variables or the ANCOVA model at a glance. Making DD-plot does not demand the statistical model assumption about error terms in regression model. Several examples show the usefulness of DD-plots as a graphical exploratory data analysis tool for the regression analysis.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.8
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• pp.1168-1179
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• 2007

The objective of this research is to validate the BRQ(Brand Relationship Quality) Construct perceived by fashion product consumers. In order to establish and verify the BRQ scale, qualitative survey and quantitative survey were conducted together. 1592 copies of questionnaire were distributed to women in their 20s to 40s living in Seoul and other metropolitan areas from Dec. 26, 2005 to Jan. 8, 2006, and 723 copies of them were used for statistical data. Samplel(n=482)was used for empirical analysis, and sample2(n=241) was used for cross validity test. The data was analyzed using Exploratory Factor Analysis, Confirmatory Factor Analysis, and Pearson's Correlation Analysis. BRQ emerged from exploratory factor analysis as the hierarchical construct composed of six facets including 'self-connective attachment', 'symbol/mystery', 'trust', 'nostalgia', 'intimacy', and 'knowledge'. As the fit of this structural model was not good as a result of Confirmatory Factor Analysis, it was revised to have better fitting. Finally, empirical survey results indicate the hierarchical construct consisting of eight distinct BRQ facets including 'love/commitment', 'self-connection', 'symbol', 'mystery', 'trust', 'nostalgia', 'intimacy', and 'knowledge' as best representing the final 39item BRQ Scale. Reliability, construct validity, and cross validity of the construct were verified.