• Journal of Distribution Science
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• v.12 no.11
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• pp.45-53
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• 2014

Purpose - Goal setting is effective in any domain in which an individual or group has some control over the outcomes. It applies not only to work tasks but also to sports and health, and in various other settings. Its success depends on considering the mediators and moderators determining its efficacy and applicability. This study investigates the individual factors influencing academic goal attainability. Unlike previous studies, we focused on the effect of the relationships between individual traits (passion, tenacity, self-control) and specific motivation (vision, self-efficacy, implementation intentions) with academic goal attainability, rather than the effects of the relationship between commitment and the goal shielding mechanism with goal attainability. Research design, data, and methodology - Data collected through questionnaires were analyzed by the SPSS program. A total of 293 school students, who participated in the TOEIC program, participated in the survey. Slightly more than half were female (male: n=145 vs. female: n=148). We verified nine hypotheses through various statistical methods (reliability analysis, exploratory factor analysis, confirmatory factor analysis, structural equation model for the hypothesis test, bootstrapping test for the mediation test). Results - Data was analyzed in three phases. The first phase involved measurement analysis (i.e., item purification and factor structure confirmation), involving the scales of the three variables of individual traits, three mechanism variables, and goal attainability. The second phase involved estimating the proposed structural relationships among the key constructs (see Figure 1), using the results to test H1 to H9. The final phase involved examining the mediating effects of the three variables (vision, implementation intention, and self-efficacy). The research model shows that the independent variable passion has a significant result with both the mediators-vision and self-efficacy. Further, vision and self-efficacy significantly affect goal attainability. The second variable, self-control, shows a significant effect when mediated by implementation intentions, but the direct relationship between implementation intension and goal attainability shows an insignificant result. However, when further mediated by self-efficacy, it showed a significant effect between self-efficacy and goal attainability. Similarly, the third variable, tenacity, shows an insignificant result when mediated by vision. In contrast, the mediator self-efficacy shows a positive effect between tenacity and goal attainability. Conclusions - This study shows how these individual traits, when mediated with the appropriate motivational factors, resulted significantly in the attainability of academic goals. We may identify several theoretical and practical contributions. Theoretically, we developed a step further in the research into consumer goals and related studies. Future research could examine the effects of different learning goal types and their combinations with performance goals (e.g., learning goals first, then performance goals), different types of goal framing (approach success vs. avoid failure), the relation between goals and cognition (which, by implication, entails all of cognitive psychology), goal hierarchies, and macro goal studies with organizations of different sizes. More studies on the relationship between conscious and subconscious goals would also be valuable.

• Journal of The Korean Association of Information Education
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• v.18 no.2
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• pp.357-370
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• 2014

The purpose of this research was to develop the tools needed to evaluate the effectiveness of using digital textbooks and smart education. We then developed the tools to evaluate the effectiveness of smart education and digital textbook utilization, which were an identification of 1) seven essential 21st century skills, definitions of each, and prerequisite abilities; 2) five 21st century teacher competencies, definitions of each, and prerequisite abilities; To develop the questionnaire, we conducted a literature review in this area, consulted experts, observed classes, interviewed members of focus groups, and met with policy makers from the Ministry of Education and KERIS. The student questionnaire(26 Questions developed) included; creativity and innovation, critical thinking and problem solving, communication, collaboration, ICT literacy, self-directed learning, and adaptability. The teacher questionnaire(24 questions developed) included; 21st Century Skills, ICT Literacy, Rapport building with learners, Instructional design, Evaluation and reflection. The tools we developed will be able to use for evaluating the effectiveness of smart education and digital textbooks.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.5
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• pp.277-283
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• 2016

Tetrapod is one of the most widely used concrete armor units for rubble mound breakwaters. The calculation of the stability number of Tetrapods is necessary to determine the optimal weight of Tetrapods. Many empirical formulas have been developed to calculate the stability number of Tetrapods, from the Hudson formula in 1950s to the recent one developed by Suh and Kang. They were developed by using the regression analysis to determine the coefficients of an assumed formula using the experimental data. Recently, software engineering (or machine learning) methods are introduced as a large amount of experimental data becomes available, e.g. artificial neural network (ANN) models for rock armors. However, these methods are seldom used probably because they did not significantly improve the accuracy compared with the empirical formula and/or the engineers are not familiar with them. In this study, we propose an explicit method to calculate the stability number of Tetrapods using the weights and biases of an ANN model. This method can be used by an engineer who has basic knowledge of matrix operation without requiring knowledge of ANN, and it is more accurate than previous empirical formulas.

• Journal of Science Education
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• v.36 no.1
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• pp.153-165
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• 2012

This study investigated the frequent mistakes and the causes of the alternative conceptions in the animal classification by using the questionnaire and interview with the middle school students (N=300). As results, some students have difficulties classifying suggested animals into vertebrates or invertebrates : snakes (31.7%), shrimps (28.3%), turtles (25.6%), frogs (24.7%), and starfish (10.7%) in order of precedence. These errors seemed to be caused by intuitive thinking over characteristics of physical motions and appearance of suggested animals, wrong inference from comparing to features of familiar animals and the lack of observation experience of the vertebrate backbone. Furthermore, the results showed that relatively many students made a mistake classifying subgroup members of vertebrates such as classifying salamanders into the class Reptilia (45.3%) and turtles into Amphibia (40.3%). It is likely that those errors are affected by ambiguousness of classification terminology (e.g. the term of Amphibia) and weak ability in relating the physiological and ecological feature to standard of classification feature. In addition, sociocultural factors could influence animal classification as 'bat in birds', 'whale in fish, and 'penguin in mammals'. The present study implied that teaching and learning animal classification may require an appropriate guide focused on activities to explore major characteristics used for the animal classification standard through providing more chances of animal observation rather than the cramming method of learning induced by technical memorizing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• The Journal of Korean Society for School & Community Health Education
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• v.4
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• pp.79-95
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• 2003

This dissertation aims to analyze various safety accidents taking place during physical education class according to physical education teacher's value orientation, to identify teacher's value orientation that can minimize safety accidents, and to provide basic materials for safe and smooth class management. For this purpose, data have been collected from 261 physical education teachers at some middle and high schools in G City in Kyung-Ki Province and Busan Metropolitan City. The materials were treated as follows: The variables on demographic characteristics of physical education teachers are determined by t-test ; The analysis of one-way ANOVA and relationship between value orientation and safety accident prevention activities was conducted through Pearson's linear correlation analysis and multiple regression; The analysis of the relationship between value orientation and actual conditions of safety accidents was conducted through logistic regression. First, there is almost no awareness difference of physical education teachers' value orientation according to demographical variables. The value orientation physical education teachers consider to be the most important is, however, mainly 'mastery of disciplinary lesson.' There is a statistically significant difference in safety accident prevention activities according to demographical variables. Teachers' focuses in class contents showed a significant difference according to teaching experience and working area, while the dependency on facility has a significant difference according to teaching experience and school type. Second, there is no correlation between physical education teacher's value orientation and safety accident prevention activities because there is virtually no statistically significant difference between them. It means that safety accident prevention activities are not related with on which teachers place emphasis among mastery of disciplinary lesson, social reconstruction, self-realization, ecological integration and value orientation on learning process. Third, the analysis of safety accident prevention activities according to physical education teachers' value orientation revealed that the lower value orientation in social reconstruction is, the more safety accidents teachers experience. It is also found that crashes among students, ball games and leg injuries are inter-related with social reconstruction in value orientation, over-motivation and unskilled motor function ; athletic sports with value orientation on learning process and safety prevention training ; unskilled motor functions with value orientation in ecological integration and disobedience to teacher's directions ; winter accidents with mastery of disciplinary lesson in value orientation. In conclusion, the research indicates that physical education teacher's value orientation according to demographical variables didn't show any significant difference, while one according to safety accident prevention activities showed significant difference. Besides, physical education teachers' value orientation is not related to safety accident prevention activities, but the relationship between value orientation and actual conditions of safety accidents showed correlations according to each variable. Especially, teachers with lower value orientation in social reconstruction experienced more safety accidents. Therefore, physical education teachers can manage physical education class more safely with more emphasis on value orientation in social reconstruction.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.179-185
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• 2021

We performed to explore the applicability of protocol to improve the curriculum literacy for special education pre-teachers. For this, protocol of Park et al (2018), which can be used in the educational field, was partially modified and applied to enhance the special education curriculum expertise of pre-teachers. The literacy protocol of the special education curriculum was applied as Protocols 1 and 2, and Protocol 1 was focused on adaptation the 2015 special education curriculum and understanding literacy. Protocol 2 consisted of reorganizing the subject level centering on the five subjects presented in the special education curriculum, and establishing an integrated theme setting and reorganization plan. We applied the research design during a total of 15 weeks of special education curriculum subjects. The class format was flipped learning (e.g, pre-video lectures, theory lectures (E-Sheets), and learner-led activities (W-Sheets) for each topic was carried out. We found that pre-teachers' thought that the academic achievement and satisfaction of students with disabilities could be increased by adaptation the curriculum. Pre-teachers reported that the experience of reorganizing each subject/intersection helped improve their literacy but found it difficult.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.649-661
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• 2020

Cut-slope management system (CSMS) has been investigated all slopes on the road of the whole country to evaluate risk rating of each slope. Based on this evaluation, the decision-making for maintenance can be conducted, and this procedure will be helpful to establish a consistent and efficient policy of safe road. CSMS has updated the database of all slopes annually, and this database is constructed based on a basic and detailed investigation. In the database, there are two type of data: first one is an objective data such as slopes' location, height, width, length, and information about underground and bedrock, etc; second one is subjective data, which is decided by experts based on those objective data, e.g., degree of emergency and risk, maintenance solution, etc. The purpose of this study is identifying an data application plan to utilize those CSMS data. For this purpose, logistic regression, which is a basic machine-learning method to construct a prediction model, is performed to predict a judging-type variable (i.e., subjective data) based on objective data. The constructed logistic model shows the accurate prediction, and this model can be used to judge a priority of slopes for detailed investigation. Also, it is anticipated that the prediction model can filter unusual data by comparing with a prediction value.

• Quality Improvement in Health Care
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• v.27 no.2
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• pp.57-72
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• 2021

Purpose: At present, there are a variety of serious patient safety incidents related to problems in health information technology (HIT), specifically involving electronic medical records (EMRs). This emphasizes the need for an enhanced electronic medical record system (EMRS). As such, this study analyzed both the nature of and potential to prevent incidents associated with HIT/EMRS based on data from the Korea Patient Safety Reporting and Learning System (KOPS). Methods: This study analyzed patient safety incidents submitted to KOPS between August 2016 and December 2019. HIT keywords were used to extract HIT/EMRS incidents. Each case was reviewed to confirm whether the contributing factors were related to HIT/EMRS (HIT/EMRS-related incidents) and if the incident could have been prevented (HIT/EMRS-preventable incidents). The selected reports were summarized for general clarity (e.g., incident type, and degree of harm). Results: Of the 25,515 obtained reports, 2,664 incidents (10.4%) were HIT-related, while 2,525 (9.9%) were EMRS-related. HIT/EMRS-related incidents were the third largest type of incident followed by 'fall' and 'medication incidents.' More than 80% of HIT/EMRS-related incidents were medication-related, accounting for approximately one-third of the total number of medication incidents. Approximately 10% of HIT/EMRS-related incidents resulted in patient harm, with more than 94% of these deemed as preventable; further, sentinel events were wholly preventable. Conclusion: This study provides basic data for improving EMR use/safety standards based on real-world patient safety incidents. Such improvements entail the establishment of long-term plans, research, and incident analysis, thus ensuring a safe healthcare environment for patients and healthcare providers.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.245-259
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• 2023

The agricultural reservoir is a critical water supply system in South Korea, providing approximately 60% of the agricultural water demand. However, the reservoir faces several issues that jeopardize its efficient operation and management. To address this issues, we propose a novel deep-learning-based water level recognition model that uses CCTV image data to accurately estimate water levels in agricultural reservoirs. The model consists of three main parts: (1) dataset construction, (2) image segmentation using the U-Net algorithm, and (3) CCTV-based water level recognition using either CNN or ResNet. The model has been applied to two reservoirs G-reservoir and M-reservoir with observed CCTV image and water level time series data. The results show that the performance of the image segmentation model is superior, while the performance of the water level recognition model varies from 50 to 80% depending on water level classification criteria (i.e., classification guideline) and complexity of image data (i.e., variability of the image pixels). The performance of the model can be improved if more numbers of data can be collected.