• Journal of Families and Better Life
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• v.32 no.5
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• pp.87-105
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• 2014

The purpose of this study was to investigate the factors associated with instrumental support (i.e., economic and practical support) from parents to their adult children. We examined both parents' attitudes toward instrumental support for adult children and parents' actual provision of instrumental support. From the data of the 2010 second National Survey of Korean Families, we selected 532 mothers and 524 fathers who were married and had at least one adult child aged over 25. Multiple regression analyses by the parents' gender showed that fathers were more likely to agree with instrumental support for adult children in general when they had unmarried children, had a lower household income level, had a lower evaluation of their socio-economic class, were satisfied with their own household economic situation, had positive attitudes toward caregiving for elderly parents, and were satisfied with their couple relationships. For mothers, they were more likely to agree with instrumental support for adult children in general when they had positive attitudes toward caregiving for elderly parents, were satisfied with their couple relationships, and perceived their child as someone to rely on in times of difficulties. Our analyses of the actual provision of support indicated that fathers tended to provide more support when they perceived that they were healthy, had unmarried children, were less satisfied with their household economic situation, had negative attitudes toward child-rearing, and reported a higher quality of parent-child relationship. For mothers, they were more likely to provide actual support when they were healthy, had unmarried children, had a higher level of household income, were financially preparing for later life, and less satisfied with their couple relationships. The findings of this study imply that it is imperative to distinguish the attitudes toward support from the actual provision of support and to also consider parents' gender in the literature on instrumental support for adult children.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.276-290
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• 2023

The purpose of this study is to analyze the characteristics and specific elements of successful science classes that pre-service elementary school teachers think. For the study, 61 pre-service elementary school teachers (47 females, 14 males) were recruited as research participants. The data used in the study are mutual evaluation papers prepared during class performances by group and individual. The amount of data was a vast amount of qualitative data with a total of 150 pages, and the research results were derived by inductively categorizing this data through qualitative analysis. The summary of the research results is as follows. First, the factors constituting a successful science class were analyzed into 7 categories (14 sub-categories, 33 sub-elements). The elements that make up a successful science class in detail were analyzed as science subject contents, class management, selection of teaching and learning methods and organization of class contents, teaching and learning materials, understanding of students, understanding of teaching situations, and class-related efforts. Second, it was possible to describe the practical classes of pre-service teachers by collecting the details of the elements that make up a successful science class recognized by pre-service teachers. As seen in the above research results, the characteristics and specific elements of successful science classes recognized by pre-service teachers were identified, and based on this, pre-service teachers will be able to develop support for effective science class operation, and continuous analysis should be conducted.

• Information Systems Review
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• v.24 no.4
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• pp.23-40
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• 2022

Although Support Vector Machine(SVM) has been used in various fields such as bankruptcy prediction model, the hyperplane learned by SVM in class imbalance problem can be severely skewed toward minority class and has a negative impact on performance because the area of majority class is expanded while the area of minority class is invaded. This study proposed optimized uneven margin SVM(OPT-UMSVM) combining threshold moving or post scaling method with UMSVM to cope with the limitation of the traditional even margin SVM(EMSVM) in class imbalance problem. OPT-UMSVM readjusted the skewed hyperplane to the majority class and had better generation ability than EMSVM improving the sensitivity of minority class and calculating the optimized performance. To validate OPT-UMSVM, 10-fold cross validations were performed on five sub-datasets with different imbalance ratio values. Empirical results showed two main findings. First, UMSVM had a weak effect on improving the performance of EMSVM in balanced datasets, but it greatly outperformed EMSVM in severely imbalanced datasets. Second, compared to EMSVM and conventional UMSVM, OPT-UMSVM had better performance in both balanced and imbalanced datasets and showed a significant difference performance especially in severely imbalanced datasets.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.393-401
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• 2021

This study is a descriptive research study to verify the relationship between university students' learning flow, self-directed learning, learning outcomes, and online class satisfaction, and to identify factors that influence online class satisfaction. There was a significant positive correlation between university students' learning flow, self-directed learning, learning outcomes, and online class satisfaction. Online class satisfaction had a positive effect on learning flow and learning outcomes, but self-directed learning had no direct effect. The explanatory power of online class satisfaction was 49%. Based on the above results, in order to increase online class satisfaction, a plan is needed to improve university students' learning flow and learning outcomes for online classes. In addition, instructor and university are required to actively endeavor and support to improve the quality of online classes.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.186-187
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• 2021

Education in Korean universities is rapidly expanding to online education due to COVID-19. In response to such changes, this study proposed a means of improving the learning management system of Korean universities and analyzed the effects of using the system. The important results of this study are as follows: the learning management system was composed of 'pre-class learning,' 'team activity,' and 'participation learning' to support team-based learning. The effects that the users (instructors, learners) can obtain by adopting team-based learning and using the system were analyzed. The study concludes that for instructors, teaching work may be alleviated. For learners, it was demonstrated that they could more easily access and use data required for their education.

• Journal of Family Resource Management and Policy Review
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• v.13 no.3
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• pp.247-280
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• 2009

The purpose of this study was to investigate the actual conditions of management of the healthy family field practicum and to present suggestions for its improvement. For this purpose, a preliminary investigation, survey, data analysis, interview as secondary source, and final data analysis were processed as research methods. The subjects of this study were the 42 supervisors in the centers which oversee the field practicum experience and the 12 supervisors in the centers which do not oversee the field practicum experience. 3 supervisors were interviewed to inquire about the reformation of field instruction in Healthy Family Support Centers. Analysis was made of the general characteristics of the above-mentioned 54 supervisors, including sex, age, academic background, certificate of qualification, class of position, and length of career related to the healthy family program. The environment of the field practice, such as the numbers of students supervised, time of field practice, practice hours, and so on, was examined in the centers which oversee the field practicum experience. The actual condition of operation investigated was divided into the preparatory stage, the early stage, the midterm stage, and the end stage. Research was conducted on the improvement of the field practicum, including the proper number of students supervised, adequate practice hours, interaction with universities or colleges, obstacles to the field practicum, and of practicum. The possibility and preparation of a further field practicum was conducted for 12 Healthy Family Support Centers, by inquiring about (a) the reasons for not overseeing the field practicum experience and (b) the needs of universities or colleges for a field practicum. The 54 supervisors surveyed suggested a particular need for improvement in human resources, the space of field instruction, system of field practicum, length of practice hours, orientation for students etc. This study investigated the actual conditions and suggested improvements of the field practicum in Healthy Family Support Centers. Therefore, its results should be meaningfully used to develop the Field Practicum for the Healthy Family and to conduct further studies.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.3
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• pp.322-334
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• 2022

This study attempted to understand the difficulties experienced in program development and class operation of instructors in the hands-on science class and the needs for training based on them. For this study, an online survey was conducted on 193 instructors in the hands-on science class in 2022, and interviews were conducted on 13 instructors. As a result, the difficulties of developing programs for hands-on science class instructors were due to lack of class content, lack of program development budget, lack of equipment necessary for class operation, and difficulty in applying various educational methods such as discussion and practice. The preferred training contents were in the order of the latest science and technology, reconstruction methods of existing programs, and regional specialization technology. In addition, it was found that the difficulties experienced by instructors in class management stemmed from the method of operating hands-on science classes using experience kits. Accordingly, instructor education should be provided in the direction of helping instructors to provide the best education in the situation of the hands-on science classroom.

• 한국노년학
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• v.38 no.4
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• pp.963-979
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• 2018

The purpose of this study was to identify frailty profiles based on physical, psychological, and social domains of functioning and to examine the associated factors showing the differences among frailty profiles. Respondents were 70 years and older(n=403) and latent class analysis was applied to determine the optimal subgroups based on Tilberg Frailty Indicators which comprised of three domains(the physical, psychological, and social domain). Also, we performed multinominal logistic regression analysis to find out factors making differences among frailty profiles. Latent class analysis(LCA) identified three distinct types: multi-frail type(27.0%), psychologically frail type(26.8%), inadequate support type(46.2%). All three types had common difficulties in dealing with daily life problems and did not receive enough help with theses difficulties. Based on the results of the LCA three-class models, people in multi-frail type accumulated problems in physical and psychological domains and had partially social domain. On the other hands, psychologically frail type showed a relatively high anxiety disorder and depression. Lastly, people in inadequate support type reported the lack of helps, but they were relatively healthy. Comparing these groups with inadequate support type, people with multi-frail had lower educational level, poor nutritional management status and were less likely to participate in labor market. People in psychologically frail type were more likely to be male, to live in big cities rather than middle and small cities, and less likely to smoke. Based on these results, our results showed the multifaceted concept of frailty among Korean elderly people and we suggested several implications for preventing frail process.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.118-126
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• 2006

There is a greater importance for underground work designed and built in the urban areas when it comes to considering the cost-effectiveness and the period of construction commensurate with an increasing trend of skyscrapers. At this stage of underground work, it's extremely necessary to choose a proper earth retaining method. Therefore, the study has suggested the rational retaining wall method by developing the support vector machine(SVM) model as a tool to choose a proper retaining wall method applied at the stage of selecting the earth retaining method. In order to develop the SVM model, the binary SVM classifier is expanded into a multi-class classifier. and to present the feasibility of our SVM model, we considered 129 projects. Applying the 'SVM Model' developed in the study to the designing and developing stages of the earth retaining work will contribute to the successful outcomes by decreasing any changes of design from implementing the earth retaining.