• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.449-457
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• 2023

The purpose of this descriptive research study was to investigate health beliefs and self-efficacy in respiratory infection management as factors that affect the respiratory infection prevention behavior of college students. The subjects were 178 students attending a university in K city of Gyeongsangbuk-do. Data were collected with a structured questionnaire from September 1st to October 16th of 2020. The results of this study are as follows; Health belief was significantly different from participant's gender (t=-2.86, p=.005), major classification (F=2.95, p=.034), and taking any medications (t=2.18, p=.030). Self-efficacy in respiratory infection management was significantly different from university students' gender (t=-3.56, p=<.001) and major classification (F=4.59, p=.004). Health belief (r=.276, p<.001) and self-efficacy in respiratory infection management (r=.660, p<.001) had a positive correlation with respiratory infection preventive behavior. Multiple regression analysis results show that self-efficacy in respiratory infection management (β=.66, p<.001) significantly affected respiratory infection preventive behavior. The model had an explanatory power of 43%. The findings demonstrate that the major factor influencing the respiratory infection preventive behavior of university students is self-efficacy in respiratory infection management. Therefore, in order to promote behavior to prevent respiratory infection in college students, a program that can strengthen self-efficacy in respiratory infection management should be developed.

• Information Systems Review
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• v.25 no.4
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• pp.233-248
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• 2023

The increasing integration of intelligent information technologies within organizational systems has amplified the risk to personal information security. This escalation, in turn, has fueled growing apprehension about an organization's capabilities in safeguarding user data. While Internet users adopt a multifaceted approach in assessing a company's information security, existing research on the multiple dimensions of information security is decidedly sparse. Moreover, there is a conspicuous gap in investigations exploring whether users' evaluations of organizational information security differ across industry types. With an aim to bridge these gaps, our study strives to identify which information security attributes users perceive as most critical and to delve deeper into potential variations in these attributes across different industry sectors. To this end, we conducted a structured survey involving 498 users and utilized the analytic hierarchy process (AHP) to determine the relative significance of various information security attributes. Our results indicate that users place the greatest importance on the technological dimension of information security, followed closely by transparency. In the technological arena, banks and domestic portal providers earned high ratings, while for transparency, banks and governmental agencies stood out. Contrarily, social media providers received the lowest evaluations in both domains. By introducing a multidimensional model of information security attributes and highlighting the relative importance of each in the realm of information security research, this study provides a significant theoretical contribution. Moreover, the practical implications are noteworthy: our findings serve as a foundational resource for Internet service companies to discern the security attributes that demand their attention, thereby facilitating an enhancement of their information security measures.

• Journal of Industrial Convergence
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• v.21 no.11
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• pp.125-134
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• 2023

This study attemped to examine the effects of health care nursing policy education on nursing students' political efficacy, political participation, and political interest. It attempted to guide the direction of policy education within nursing curriculum. The subjects consisted of 89 nursing students of G-university from March 8, 2023, to June 21, 2023, including 44 in the experimental group and 45 in the control group. The health care nursing policy class was developed using the ADDIE(Analysis, Design, Development, Implementation, Evaluation) model of instructional design. Data analysis used the SPSS 25.0 program through mean, standard deviation, and independent sample t-test. The experimental group that participated in this education showed statistically significant improvement in political efficacy(t=2.34, p<.05) and intrinsic political efficacy(t=2.75, p<.05), as well as passive political participation score(t=2.22, p<.05) compared to before the intervention. Based on the findings of this study, it is suggested that health care nursing policy education should be structured to enhance external political efficacy and promote active political participation in future nursing curriculum.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1506-1520
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• 2023

The purpose of this study was to analyze the mediating effect of self-management in the relationship between the grit of skin care workers and its impact on self-efficacy and job performance. Research participants were 344 workers at skin care shop and hospitals in Seoul and Gyeonggi province, and data were collected through a structured questionnaire. The collected data were analyzed through descriptive statistics, confirmatory factor analysis(CFA), correlation analysis, structural equation model, and mediation effect analysis using bootstrapping method using SPSS, AMOS 26.0 Statistical programs. The conclusions drawn through a series of research procedures are as follows. First, the grit of skin care workers showed a significant positive(+) influence on self-management, self-efficacy, and job performance. Second, Self-management of skin care workers showed a significant positive(+) relationship with self-efficacy and job performance. Third, self-management of skin care workers was found to have a mediating effect in the relationship between grit and job performance. Therefore, it is judged that there is an urgent need to apply human resources management and education programs that can increase self-management, self-efficacy, and job performance through cultivating the grit of beauty industry workers.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.403-409
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• 2024

In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

• The Mathematical Education
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• v.63 no.2
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• pp.187-207
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• 2024

In this study, we explored the feasibility of automatically scoring descriptive assessment items using GPT-4 based ChatGPT by comparing and analyzing the scoring results between teachers and GPT-4 based ChatGPT. For this purpose, three descriptive items from the permutation and combination unit for first-year high school students were selected from the KICE (Korea Institute for Curriculum and Evaluation) website. Items 1 and 2 had only one problem-solving strategy, while Item 3 had more than two strategies. Two teachers, each with over eight years of educational experience, graded answers from 204 students and compared these with the results from GPT-4 based ChatGPT. Various techniques such as Few-Shot-CoT, SC, structured, and Iteratively prompts were utilized to construct prompts for scoring, which were then inputted into GPT-4 based ChatGPT for scoring. The scoring results for Items 1 and 2 showed a strong correlation between the teachers' and GPT-4's scoring. For Item 3, which involved multiple problem-solving strategies, the student answers were first classified according to their strategies using prompts inputted into GPT-4 based ChatGPT. Following this classification, scoring prompts tailored to each type were applied and inputted into GPT-4 based ChatGPT for scoring, and these results also showed a strong correlation with the teachers' scoring. Through this, the potential for GPT-4 models utilizing prompt engineering to assist in teachers' scoring was confirmed, and the limitations of this study and directions for future research were presented.

• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

• Journal of The Korean Association For Science Education
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• v.27 no.9
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• pp.854-869
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• 2007

In this study, we investigated secondary science teachers' internalization of constructivistic science teaching who participated in a collaborative program between teachers and researchers designed by researchers according to constructivist views. The program consisted of lecture, workshop, and small group activities. New trends in science education and framework for science teaching were introduced during lectures, and understanding about the framework were deepened by analyzing school science classes recorded during workshops. In small group activities, participating teachers and researchers cooperated to design science lesson plans using science teaching frameworks. Five secondary science teachers participated in collaborative workshops. Collaborative programs were video-taped. Semi-structured interviews were conducted before and after workshops. All data recorded were transcribed and analyzed. In the process of internalization, participating teachers attended on different parts. Various and discernable factors such as there own background, beliefs, values, and school context produced tensions with or facilitated internalization of constructivistic science teaching. Teaching experiences and student understanding affected teachers' lesson planning activities. Teachers also showed different understandings on inquiry, application, and model from the framework, and they interpret those concepts in the framework based on their prior understanding. They perceived that too much content should be dealt within relatively limited time. Therefore, they tended to separate science class into two parts when developing science lessons: explaining science content by lecture and science laboratory as a constructivistic activity. The results of the study provide meaningful implications to the constructivist teacher education and professional development.

• Journal of The Korean Association For Science Education
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• v.38 no.3
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• pp.305-317
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• 2018

In this study, we investigated the characteristics of participant students' modeling with the blackbox simulation program and epistemic criteria. For this research, we developed a blackbox simulation program, which is an ill-structured problem situation reflecting the scientific practice. This simulation program is applied in the activities. 23 groups, 89 second year students of an education college participated in this activity. They visualized, modeled, modified, and evaluated their thoughts on internal structure in the blackbox. All of students' activities were recorded and analyzed. As a result, the students' models in blackbox activities were categorized into four types considering their form and function. Model evaluation occurred in group model selection. Epistemic criteria such as empirical coherence, comprehensiveness, analogy, simplicity, and implementation were adapted in model evaluation. The educational implications discussed above are as follows: First, the blackbox simulation activities in which the students participated in this study have educational implications in that they provide a context in which the nature of scientific practice can be experienced explicitly and implicitly by constructing and testing models. Second, from the beginning of the activity, epistemic criteria such as empirical coherence, comprehensiveness, analogy, simplicity, and implementation were not strictly adapted and dynamically flexibly adapted according to the context. Third, the study of epistemic criteria in various contexts as well as in the context of this study will broaden the horizon of understanding the nature of scientific practice. Simulation activity, which is the context of this study, can lead to research related to computational thinking that will be more important in future society. We expect to be able to lead more discussions by furthering this study by elaborating and systematizing its context and method.

• 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.