• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.4
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• pp.610-618
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• 2015

The purpose of this study was to analyze differences in emotional labor strategies, burnout, and work engagement according to general characteristics of school foodservice employees as well as verify differential effects of two emotional labor strategies on burnout and work engagement. Our survey was administered to 400 school foodservice employees in Gyeongbuk from March 3 to April 25, 2014. A total of 358 completed questionnaires were returned, and 350 questionnaires were used for final analysis. For verification of mean differences, the mean scores for surface acting, deep acting, burnout, and work engagement were shown to be 2.38/5.00, 3.46, 2.67, and 3.41, respectively. The mean surface acting was significantly different according to cooking certification (P<0.001), turnover number (P<0.001), salary (P<0.001), and school level (P<0.01). The mean deep acting was significantly different according to educational background (P<0.001), cooking certification (P<0.001), employment status (P<0.001), salary (P<0.001), school level (P<0.01), and meal service time (P<0.05). The mean burnout was significantly different according to educational background (P<0.01), cooking certification (P<0.05), employment status (P<0.001), school level (P<0.001), and meal service time (P<0.001). The mean work engagement was significantly different according to cooking certification (P<0.001), employment satus (P<0.001), salary (P<0.001), school level (P<0.01), and meal service time (P<0.05). Verification of causal models found that surface acting and deep acting increased burnout and deep acting, respectively (research model). Additionally, surface acting did not influence work engagement, and deep acting did not influence burnout (alternative models). In other words, we identified that emotional labor strategies have differential influences on burnout and work engagement. Finally, implications and limitations of this study are discussed.

• Korean Journal of Food Science and Technology
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• v.37 no.3
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• pp.484-491
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• 2005

Quantitative microbial risk assessment (QMRA) analyzes potential hazard of microorganisms on public health and offers structured approach to assess risks associated with microorganisms in foods. This paper addresses specific risk management questions associated with Staphylococcus aureus in kimbab and improvement and dissemination of QMRA methodology, QMRA model was developed by constructing four nodes from retail to table pathway. Predictive microbial growth model and survey data were combined with probabilistic modeling to simulate levels of S. aureus in kimbab at time of consumption, Due to lack of dose-response models, final level of S. aureus in kimbeb was used as proxy for potential hazard level, based on which possibility of contamination over this level and consumption level of S. aureus through kimbab were estimated as 30.7% and 3.67 log cfu/g, respectively. Regression sensitivity results showed time-temperature during storage at selling was the most significant factor. These results suggested temperature control under $10^{\circ}C$ was critical control point for kimbab production to prevent growth of S. aureus and showed QMRA was useful for evaluation of factors influencing potential risk and could be applied directly to risk management.

• Journal of The Korean Association For Science Education
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• v.22 no.4
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• pp.872-881
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• 2002

Student questioning is included in the priority of science literacy, to enable students to solve problems by exploring questions, communicating and constructing knowledge(AAAS, 1989). Also, the essence of student questioning in science lies in its function as a link between thinking and learning. But educators did not pay much attention to students' questioning in Korea. The purpose of this study was to investigate the effects of science question enhancement instruction on students' science questioning level and achievement. Also, this study showed the effects of other variables(logical thinking, science achievement, interest, and gender) on students' science questioning level. The pretest-posttest control group design group design was used. The sample was consisted of 80 second grade middle school students in experimental group(Science question enhancement instruction) and 74 students in control group(Traditional learning). Students in both groups were received identical content instruction on the unit 'Structures and functions of plant'. These groups were treated for 15 hours during 6 weeks. Students' questions were rated using the four levels described by the Middle School Students' Science Question Rating Scale(r= .96,)(Cuccio-Schirripa & Steinner, 2000). Science achievement data were collected using a 17 item multiple choice test(Cronbach ${\alpha}$= .84). To investigate students' logical thinking ability, a abridged GALT(Cronbach ${\alpha}$= .69) was used. Five-way ANOVA, ANCOVA, and multiple regression analysis were used to analyze the results. The results indicated that students who received instruction on researchable questioning outperformed those students who were not instructed on high-order questioning(p< .01). Results of correlations indicated that instruction(r= .640), science achievement(r= .311) and logical thinking ability(r= .212) was significantly and positively related with students' questioning level. But, interest and gender did not show any significant correlation with students' questioning level. Science question enhancement instruction was more effective on science achievement than the traditional instruction(p< .01).

• 대한공업교육학회지
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• v.44 no.2
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• pp.142-163
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• 2019

The purpose of this study is to analyze the effect of problem solving ability and satisfaction of university students who are pre-technology teachers in woodworking products(birdhouse) making program using design thinking. Survey responses are analyzed by statistical programs(SPSS ver.20) such as satisfaction, confidence in problem solving, difficulties and causes of difficulties according to gender and grade of 33 students who conducted experience programs in extra-curricular programs to improve creativity and problem solving ability. The main conclusions of this study are as follows: First, the average of total satisfaction about experience programs is 4.39, which is somewhat high. The highest average response is 'feelings of accomplishment' and 'advice in the surroundings'(M = 4.46). There is no significant difference between male and female, and grade. The students interest in group-based different birdhouse woodworking together with the help of the surrounding people by the process of design thinking rather than practice to follow. Therefore, I'd like to recommend to other students due to this program shows a high self-confidence, sense of accomplishment, and satisfaction. Second, the total average response of students 'self-confidence for problem solving at the group based making experience program using design thinking is 3.80. In result of group activities, the students have self-confidence of 'problem-solving ability and deal with difficult situations'. Later, in making programs, complementing difficulties of making can enhance the satisfaction of the students. Third, in the survey questionnaire related with problem solving ability confidence, between 'I have the ability to solve many problems' and 'I always have the ability to cope with new and difficult business situations' show the highest correlation. Therefore, in order to improve self-confidence of problem solving ability, it is necessary to prepare teaching learning programs that can strengthen problem solving ability. Fourth, in the new design and making process not a given product design, the most difficult step is 'the process of rework and modifying idea product'. The main reason that students have difficulty in the production process is 'lack of knowledge and ability to produce'. To make various woodworking products using design thinking process, it can be helpful to make works if you have enough training on woodworking and design thinking before product making. The students' satisfaction about team-based learning using design thinking that helps improving creativity and problem solving ability is high. Therefore, the result of the research in other making activity program that design thinking is applied and analyzed can improve students' problem solving ability.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Journal of Preventive Medicine and Public Health
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• v.29 no.3 s.54
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• pp.451-469
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• 1996

To identify the drug abuse status and its determinant factors in high school boys in Taegu, the study was performed from April to May, 1995. Study population were selected by cluster sampling method and total 5,665 students replied to the self-administered questionnaire survey (2,207 in academic high school, 3,458 in business high school). The major findings were as follows; The proportion of drinking, smoking experience was 55.0%, 45.8%, respectively, and the proportion of current drinker, current smoker was 27.2%, 27.5%. The drinking, smoking experience rate of second grade students was higher than first grade and it was higher in business high school boys. The proportion of a stimulant, a hallucinogen, hemp leaf cigarets experience was 3.2%, 1.6%, 0.1%, respectively. Drug abuse had significant association with home environment(lower economic status, frequent move, death of father or mother, apart from family), parents environment(parents' indifference, parents' drinking and smoking, etc.), school life(lower school grades, intimate friend's drug abuse, etc.), generous attitude to drug abuse, higher level of stress. Students who replied that the law prohibited immature person(students) from drinking and smoking showed lower drug abuse rate. In multiple logistic regression analysis, second grade students, business high school students, parents' indifference, lower school grades, intimate friend's drug abuse, no recognition of the fact that the law prohibits high school students from drinking and smoking, generous attitude to drug abuse, higher level of stress were significantly related with alcohol abuse and smoking. Other drugs abuse were related with above factors. On consideration of above findings, to prevent students from drug abuse, we have to try together in house, school, and society.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Management & Information Systems Review
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• v.36 no.3
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• pp.131-150
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• 2017

The purpose of this study is to observe the spread pattern of open source software (OSS) while establishing relations with surrounding actors during its operation period. In order to investigate the change pattern of participants in the OSS, we use a netnography on the basis of online data, which can trace the change patterns of the OSS depending on the passage of time. For this, the cases of three OSSs (e.g. jQuery, MooTools, and YUI), which are JavaScript frameworks, were compared, and the corresponding data were collected from the open application programming interface (API) of GitHub as well as blog and web searches. This research utilizes the translation process of the actor-network theory to categorize the stages of the change patterns on the OSS translation process. In the project commencement stage, we identified the type of three different OSS-related actors and defined associated relationships among them. The period, when a master commences a project at first, is refined through the course for the maintenance of source codes with persons concerned (i.e. project growth stage). Thereafter, the period when the users have gone through the observation and learning period by being exposed to promotion activities and codes usage respectively, and becoming to active participants, is regarded as the 'leap of participants' stage. Our results emphasize the importance of promotion processes in participants' selection of the OSS for participation and confirm the crowding-out effect that the rapid speed of OSS development retarded the emergence of participants.

• Journal of The Korean Association of Information Education
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• v.16 no.4
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• pp.383-395
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• 2012

This study investigated the recognition of teachers on the introduction and use of SMART education, which is an ICT-based customized learning method. Through the investigation, the study was to empirically examine the relationship between the use intention of SMART education and its influential factors, and analyze the difference in the use intention of SMART education by teachers, focusing on the experience of SMART education. For analysis purpose, a structural equation model, which was expanded from the theory of reasoned action, was presented. In addition, the difference in path coefficient, which affects the use intention of SMART education, was compared based on the experience with or without SMART education. The results showed that teacher efficacy in the teacher group without SMART education experience was more negatively significant in class burden. In the teacher group with SMART education experience, it was found that the attitude toward SMART education was more significant in use intention; organizational citizenship behavior was more significant in use intention; teacher efficacy was more significant in the attitude toward SMART education and; teacher efficacy was more significant in organizational citizenship behavior. No significant difference was found in the path coefficient among the groups in other hypotheses. Through these results, the factors for introducing and promoting SMART education and its invigoration measures were presented.

• Journal of the Korean Society of Earth Science Education
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• v.13 no.2
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• pp.147-161
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• 2020

In order to help elementary students understand the astronomical unit in depth, this study applied backward design 2.0 to check the effect on students' science academic achievement, performance evaluation, and science class satisfaction. As a result of the study, there was no statistically significant difference in the science achievement test, but the average score of the experimental group has improved. As a result of the performance evaluation test, there was a statistically significant difference because the feedback was well provided through the process-focused assessment and it helped in-depth understanding. As a result of the science class satisfaction test, there was a statistically significant difference in the areas of science curriculum and peer relation except for the science teacher area. This is because a differentiated science curriculum was designed through analysis of achievement standards, and various teaching methods of student-centered were implemented to reach achievement standards. We hope this study will focus on the impact of backward design 2.0 on learners in elementary science classes and help find ways to effectively apply backward design 2.0 in the field.