• Journal of Engineering Education Research
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• v.27 no.1
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• pp.3-12
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• 2024

The degree-linked programs for employees, operated by joint training centers in specialized universities that have implemented work-study integrated programs, are educational programs that require an annual government budget of around 80 billion KRW. However, the 70+ universities running these programs face issues such as a decline in academic achievement and an increase in dropout rates among students. In this paper, I conducted multiple regression analysis based on observed and measured information to examine whether the participating students in these programs are achieving an appropriate level of academic performance and to identify the factors that universities need to invest in to achieve that level. To do this, I hypothesized a causal relationship between the university's input factors and students' academic achievement, and used the SPSS program to analyze the statistical data, confirming the validity of the hypothesis. The collected data for the study were obtained through a survey developed using a Likert 4-point scale, which quantified the distribution of grades among students enrolled in IT-related departments offering the degree-linked programs for employees and the emotional contact efforts made by the universities to motivate them for academic success. Particularly, through the results of multiple regression analysis, it was confirmed that these input factors, unlike those for students in general education programs, require more personalized and frequent interactions.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.37-46
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• 2022

The purpose of this study is to provide basic data onto preparing soft landing plan of future education policy by exploring direction of future education for the common good using big data and keyword network analysis. Based on the big data provided by Textom, data was collected under the keyword 'future education + common Good' and then keyword network analysis was performed. As a result of the research, it was found that 'common good', 'social', 'KAIST future warning', 'measures', 'research', 'future education', 'politics' were common keywords in the social awareness of future education for the common good. The results of this study suggest that the social awareness of future education for the common good is related to factors related to human, physical environment, social response, academic interest, education policy, education plan, and related variables, It was closely related. Based on these results, we suggested implications for the support for the preparation of a soft landing plan of future education for the common good.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.327-351
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• 2023

This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.

• Journal of Korean Academy of Nursing
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• v.24 no.4
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• pp.678-695
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• 1994

The purpose of this study was to investigate knowledge, attitudes and practices of women toward breast self-examination and to identify factors that may influence compliance with breast examination. The subjects for this study were 282 women in three hospitals located in In-Chun. Data were collected during the period from October 15 to 30, 1993 by means of a structured questionnaire. The data were analyzed using the SAS program and include descriptive statistics, 1-test, ANOVA, Pearson correlation coefficient and stepwise multiple regression. The results of study are as follows : 1. The mean knowledge score for the total sample was 13.58. Factors affecting the women's knowledge of breast cancer and BSE were : age, level of education, experience with breast cancer patients, experience in learning BSE, information about BSE, self-practice of BSE, level of intention to perform BSE, and participation in a BSE class. 2. Elements related to attitude included : (a) perceived feeling of susceptibility to breast cancer, and (b) belief about the effectiveness of BSE. The mean perceived susceptibility score was 1.62 and the mean effectiveness score was 4.22. Factors affecting the women's perceived susceptibility to breast cancer were exercise for health, level of intention to perform BSE , intention to recommend to others and self-practice of BSE. The relation between the womens' belief about effectiveness of BSE and level of intention to perform BSE and intention to recommend to others were statistically significant. 3. The mean self-practice score for the total sample was 4.01. Factors affecting the women's practice were experience with breast cancer patients, information about BSE, experience in learning BSE, enlisting the help of significant peers, and level of intention to perform BSE. Results indicated 35.8% of the total sample practiced BSE. The most frequent reason women gave for not performing BSE was “Didn’t knew about BSE technique”, “Didn’t think do it”. 4. No relation was found between knowledge and attitudes and practices. 5. When all the variables were examined for their contribution to the variance in the practice of BSE, it was found that confidence in ability to detect a mass by BSE, knowledge about breast cancer and BSE, and experience with breast cancer patients were significant variables and explained 35.8% of the variance. From the results of this study it can be said that women need to be taught proper BSE technique so they can become more proficient in detecting breast abnormalities.

• Journal of Korean Home Economics Education Association
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• v.27 no.4
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• pp.19-35
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• 2015

The purpose of this study was to develop and evaluate a teaching learning process plan for the practice of caring and sharing to improve character of highschool students through Home Economics subject. The teaching learning process plan consisting of 13-session lessons has been developed and implemented according to the ADDIE model for the unit of 'Happy Family Life and Culture led by Family'. The unit was divided into two themes: Theme I caring through sharing and Theme II caring through practice. Six practice elements of caring and sharing such as communication, gratitude, courage, love, empathy, and environment drawn from Theme I are applied to Theme II. Various activities and teaching materials as well as questionnaire were developed. The plan was applied to 8 classes, 287 freshmen of S highschool in Jeonju-si from March to May, 2014. Three factors were drawn from 35 character-related items: self-perception, perception of caring and sharing, and practice of caring and sharing. These factors were related to respondents' satisfaction with family relationships and school life. Two factors except self-perception improved through 13 lessons. Students evaluated that the whole caring and sharing practice lessons of Theme I and II gave them the chance to realize a actual practice in everyday life was important even with small efforts such as cooking for special family. Also students commented that the praising workbook was impressive. All 23 items of evaluation gained from over 3.5 to 4.2 on 5-point scale. It can be concluded that the teaching learning process plan for the practice of caring and sharing for the unit of 'Happy Family Life and Culture led by Family' would improve character of highschool students through the Home Economics subject.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.411-420
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• 2018

This study was conducted to identify the effects of interpersonal communication between health care providers after receiving supplementary education. The participants of this study were 433 health care providers who work at 29 general hospitals in Gwangju Metropolitan City and Jeollanamdo Province. Data were collected from June 8 to June 25, 2018 and evaluated by t-tests, dispersion analysis, correlation analysis and stepwise regression. The results were produced by investigating interpersonal communications according to socio-demographic and health-related characteristics including age, education level, bed size of the hospital at which the participant worked, job satisfaction, hospital location, personal health status, experience with health care management and experience with depression. There were significant differences in communication observed according to supplemental education awareness regarding age, bed size of hospital, occupation, wage, type of medical institution of employment, job satisfaction, work location, health status, health care education experience and chronic disease. There were positive correlations between supplemental education awareness in health workers and their interpersonal communication. The factors that had positive effects on interpersonal communication were level of education and health-related education experience, while age, hospital bed size and job dissatisfaction had negative effects. Finally, support environment, learning transfer and results were identified as sub-factors of supplemental education. Based on the results above, it was proposed that educational training to enhance results, provide a supportive environment and foster learning transfer be developed to increase communication between health workers and provide a safe health service for patients.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.295-305
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• 2022

This study aimed to present a realistic policy direction to reduce human rights violations by analyzing the mechanisms of its factors affecting the experience of human rights violations for middle and high school student athletes. The method analyzed the response data of 13,205 student athletes through a structured questionnaire using logistic regression analysis. The independent variable consisted of sexual violence, sexual shame, physical violence, verbal violence, bullying, invasion of privacy and learning rights, and unfair leaders' actions related to exercise. As a result of the analysis, first, the team atmosphere, human rights consciousness in their sports and in the sports field were found to have a significant influence on physical and language violence, bullying, privacy and infringement of learning rights. Second, for the experience of sexual violence, the team atmosphere and the level of awareness of human rights violations in the sports community had a significant effect, but the permission of violence in the sports community and human rights consciousness in their sports did not appear as meaningful variables. Third, it was found that the unfair experience related to exercise had a significant effect on the team atmosphere, the overall level of violence in the sports community, and the its awareness of human rights violations in the sports community.

• Korean Journal of Community Nutrition
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• v.10 no.6
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• pp.905-919
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• 2005

This study raised the necessity of developing performance indicators for measuring the management efficiency and effectiveness of school food service, and as a means of helping its implementation, a balanced score card (BSC) approach developed by Norton and Kaplan was adopted. This study established BSC in seven phases through literature: Phase 1 Defining a school food service and the scope of working activities, Phase 2 Establishing the vision of a school food service, Phase 3 Setting strategic goals, Phase 4 Identifying critical success factors (CSFs), Phase 5 Developing Key Performance Indicators (KPIs), Phase 6 Extracting cause and effect relationship, and Phase 7 Completing a preliminary BSC. The preliminary BSC was fumed into a survey, which was administered to food service related people working at the Office of Education and School Food Service including 16 offices,209 dietitians, 48 school administrators both from self-operated and contract-managed, and 9 experts in areas related to school food service. They were asked questions about strategies from 4 different perspectives,12 CSFs, 39 KPls, and the cause and effect relationships among them. As a result, among the CSFs based on 4 different perspectives, all factors other than ' zero sum on profit/loss ' from the financial perspective turned out to be valid. In terms of KPIs, manufacturing cost percentages, casualty loss count/reduction rates, school foodervice participation rates, and sales goal achievement rates were found to be valid from the financial perspective, while student satisfaction index, faculty satisfaction index, leftover ratio, nutrition educational performance count, index of evaluating nutrition education, customer claim count/reduction rate, handling customer claim count/reduction rate, and parent satisfaction index were found to be valid from the customers' perspective. Besides, nutritional requirement sufficient ratio, nutritional management score, food poisoning outbreak count, employee safety accident count, sanitary inspection assessment index, meals per labor hour (productivity index), computerization ratio, operational management index, and purchase management assessment index were also found to be valid from the perspective of internal business processes. From the perspective of innovation and learning, employee turnover ratio/rate of absenteeism, annual education and training count, employee satisfaction index, human resource management assessment index, annual menu-related customer feedback, food service information index for employees and parents/schools were also found to be valid. The significance of this study is to present indices for measuring overall performance of school lunch food service operations without putting any limitation on types of school food service management, and to help correctly assess the contribution of the current types of school food service management to schools and students. (Korean J Community Nutrition 10(6) : $905\∼919$, 2005)

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.9-22
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• 2008

The purpose of this research is to develop a prototype of the support system in order for team building associated with web-based project learning having applied Kolb's learning style. To accomplish this purpose, the following research tasks were performed. First, core idea in order to embody the system's value, key activities, tools that will support pertinent activities and the strategy so as to develop guidelines, etc. were devised and prepared. Second, a system was designed on the basis of structural model of teaching design, then after, interface was developed. The core factors in this system are inspection of learning style, organizing a team and team building. Above all, it is required to make learners know about learning environments, of which they are in favor, and also its distinctive features through inspection of learning style, and then focusing on learning style, a team should be organized insomuch as to accommodate a variety of learning styles as much as possible. For the purpose of team building, after learning style of each constituent member of the team has been made known, then the roles will be divided among the constituent members of the team so as to suit their individual characteristics referring to each of their learning styles that have been exposed. To verify the value of this system developed and efficiency thereof, a focus group interview was conducted. The focus group consisted of professionals, all from related fields. After the interview, the points required to make further improvements were elicited and taken care of by follow-up actions as needed. And having reflected such improvements made, the final system was developed. With this newly developed system, learners can get the results of inspection of learning style so quickly by performing inspection any time any where, and based on the results from such inspection, a team comprising dissimilar constituents who exhibit a variety of different propensities will be automatically organized. Thus, this system may be used not only for web-based project learning having unspecified persons elected as constituents, but in the offline space also.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.