• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.459-469
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• 2021

In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.

• Child Health Nursing Research
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• v.30 no.1
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• pp.31-44
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• 2024

Purpose: This study aimed to identify the infant-rearing experiences of parents during the coronavirus disease 2019 (COVID-19) pandemic and provide foundational data for the development of infant-rearing support programs during pandemic situations. Methods: Convergent mixed methods were used to better understand the research outcomes by converging both quantitative and qualitative data. A total of 149 parents with infant-rearing experiences during the pandemic responded to a self-report survey, and 10 parents participated in the interviews. Data were analyzed using Colaizzi's method, descriptive statistics, t-test, one-way analysis of variance, the Scheffé test, Pearson correlation coefficients, and hierarchical regression. Results: Analysis of qualitative data yielded the following three categories: five theme clusters, ten themes, and thirty-nine subthemes. The factors influencing infant-rearing behavior were nuclear family (β=.34, p<.001) and rearing stress (β=-.39, p<.001). The explanatory power of the regression equation was 26.6%. Conclusion: Infectious disease disasters, such as the COVID-19 pandemic, can quickly alter infant-rearing conditions, causing heightened parental anxiety. This may affect infant-rearing behaviors and hinder healthy infant development. Future research should develop a comprehensive tool to measure holistic health-related parenting behaviors across the different stages of child development. Additionally, pediatric nurse practitioners can play an active role in educating parents, supporting parenting, and promoting healthy infant development in their communities, making pediatric nurse practitioners a highly relevant and necessary healthcare profession during infectious disease disasters. Thus, there is a need to improve institutions and build infrastructure at the national level to support them.

• Korean Journal of Soil Science and Fertilizer
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• v.31 no.4
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• pp.359-367
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• 1998

In order to determine the nitrogen supplying capabilities (NSC) of corn fields, 47 field experiments were performed in Pennsylvania over 3 year from 1986 and NSCs were estimated by the regression analysis with chemical properties and soil attributes. Although the content of $NO_3-N$ in soil showed the best correlation with NSC ($R^2=0.518$), the standardized partial regression coefficient of $NO_3-N$ for NSC was 0.52, with some variations over the years. This value was slightly higher than those of the other properties which ranged from 0.001 to 0.351. Multiple linear regression with soil attributes for the evaluation of NSC was better than simple regression with $NO_3-N$. The coefficient of determination ($R^2$) for the evaluation of NSC was gradually increased; 0.599 with selected chemical properties, 0.698 with quantitative attributes(chemical properties and depth of Ap horizon), and 0.839 with quantitative and selected qualitative soil attributes. Consequently, in order to evaluate NSC, analysis by multiple linear regression with soil attributes was more reliable and better model than by the simple regression model.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.13-30
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• 2020

This study aims to analyze the qualitative and quantitative effects of environmental policies in terms of green space management using logistic regression model(LRM). Landsat satellite imageries in 1985, 1992, 2000, 2008, and 2015 are classified using a hybrid-classification method. Based on these classified maps, logistic regression model having a deforestation tendency of the past is built. Binary green space change map is used for the dependent variable and four explanatory variables are used: distance from green space, distance from settlements, elevation, and slope. The green space map of 2008 and 2015 is predicted using the constructed model. The conservation effect of Ulsan's environmental policies is quantified through the numerical comparison of green area between the predicted and real data. Time-series analysis of green space showed that restoration and destruction of green space are highly related to human activities rather than natural land transition. The effect of green space management policy was spatially-explicit and brought a significant increase in green space. Furthermore, as a result of quantitative analysis, Ulsan's environmental policy had effects of conserving and restoring 111.75㎢ and 175.45㎢ respectively for the periods of eight and fifteen years. Among four variables, slope was the most determinant factor that accounts for the destruction of green space in the city. This study presents logistic regression model as a way of evaluating the effect of environmental policies that have been practiced in the city. It has its significance in that it allows us a comprehensive understanding of the effect by considering every direct and indirect effect from other domains, such as air and water, on green space. We conclude discussing practicability of implementing environmental policy in terms of green space management with the focus on a non-statutory plan.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.91-97
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• 2019

In automatic map generalization, the formalization of cartographic principles is important. This study proposes and evaluates the selection method for road network generalization that analyzes existing maps using reverse engineering and formalizes the selection rules for the road network. Existing maps with a 1:5,000 scale and a 1:25,000 scale are compared, and the criteria for selection of the road network data and the relative importance of each network object are determined and analyzed using $T{\ddot{o}}pfer^{\prime}s$ Radical Law as well as the logistic regression model. The selection model derived from the analysis result is applied to the test data, and road network data for the 1:25,000 scale map are generated from the digital topographic map on a 1:5,000 scale. The selected road network is compared with the existing road network data on the 1:25,000 scale for a qualitative and quantitative evaluation. The result indicates that more than 80% of road objects are matched to existing data.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.1-14
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• 2023

The purpose of this study is to discover the possible solutions for the problem faced by academicians during online learning by means of employing qualitative and quantitative approaches. Using a qualitative approach, selected academicians were interviewed, and their feedback was transcribed and used to develop the survey instrument. The quantitative research design was later used to determine the most plausible solutions for the problem that could be obtained and implemented by distributing the questionnaire to academicians at a public university. Multiple regression analysis results indicate that work-life conflict and lack of support are the main contributors to academicians' mental and emotional health issues. The study's major findings help higher education institutions craft appropriate strategies to enhance the effectiveness of online teaching and learning by providing the necessary support to the academicians. The study's findings suggest that academicians should separate work and family requirements to concentrate on their job. Furthermore, the immediate supervisor must be considerate in determining the number of tasks, the deadlines, and the assistance required to complete the task. Lastly, academicians must equip themselves with emotional intelligence to cope with stressors.

• Korean Journal of Occupational Health Nursing
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• v.26 no.2
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• pp.93-104
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• 2017

Purpose: This is a mixed method study to understand the experience regarding the job satisfaction of Physician Assistant (PA) male nurses. Methods: First, factors influencing job satisfaction were analyzed using quantitative approach and job adaptation processes by qualitative research was done through interviews. Finally both of the collected data were comprehensively compared. Results: The factors which had the greatest influence on job satisfaction in the regression analysis were job stress (${\beta}=-.49$, p<.001) and job identity (${\beta}=.46$, p<.001) and the explanatory power explaining these variables was 58% (Adj. $R^2=.58$). The results of qualitative research were categorized using the same four variables with qualitative research variables. Five themes in job satisfaction, three themes in job identity, five themes in job stress and six themes in job value were identified by content analysis. Conclusion: This finding identified that the job stress and job identity were important variables related to job satisfaction. Therefore, the factors influencing job identity have to be strengthened, and a systematic management and interest to develop them are necessary.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.5
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• pp.1273-1289
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• 2015

The purpose of this study was to use the parent of the infant status and their media perception (3-7 five years) the infants' media use by examining the situation looking at the parents' use of media that cause impact on infants' media use parents will be validated accordingly to seek the solutions for the media and the involvement of infants perception. U City and 14 practitioners in preschool infants aged 5-7 target parents from 1307 people based in September 2014, a survey was conducted two months until October. This study was a mixed Methods for quantitative analysis of all the results and qualitative analysis of the results. Results for media use quantitative analysis of the results and impact parents have on infants' media use their media usage status of the parents and the media use of infants by their perceived status has been subjected to frequency analysis and hierarchical multiple regression analysis, parents perception results. Analysis of the solution for the immersion of the media and the infants unit of analysis was used for componential analysis. Through this study, parents would like to establish a plan to take advantage of essential educational content in the media and sought ways for the correct use of infants in the media and practice at home.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.382-392
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• 2023

Objective : The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. Methods : We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. Results : The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters-growth and decay rates, and peak center and heights-of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. Conclusion : The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.910
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• pp.1253-1264
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• 2004

The purpose of this study is to develop clothing shopping orientation[CSO] scale reflecting the conceptual structure of CSO. For this purpose, a questionnaire composed of comprehensive 85 CSO items was developed through 2-step preliminary tests. Data was collected from two samples. One sample(n=559) was for scale development and the other sample(n=235) was for cross validity test. Descriptive analysis, correlation analysis, exploratory factor analysis, regression analysis, ANOVA, and confirmatory factor analysis were used for data analysis. For each lower-dimension within the CSO conceptual structure model, 1-2 items were selected based on the quantitative and the qualitative standards. As a result, a CSO scale composed of 31 items was developed, and reliability, construct validity, cross validity, convergent validity, discriminant validity, and criterion validity of the scale were verified. This study has significance in offering the standardized scale to both the academic and the practical fields.