• Korean Journal of Adult Nursing
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• v.26 no.6
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• pp.653-667
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• 2014

Purpose: This study was aimed to develop frequently-used clinical scenarios and scoring rubrics to assess core basic nursing skills in adult health nursing clinical practice for clinical evaluation based on program learning outcomes (PO). Methods: This study was a methodological research combining focus group interviews and questionnaires to select and construct scenarios. Data were collected from clinical practitioners, adult health nursing professors, and new nurses from November, 2013 to April, 2014. The developed scenarios and rubrics were applied to nursing students by way of showing an example. Results: The 12 frequently-used clinical scenarios were developed. The proportion of the evaluation rubrics were 30% for clinical instructors where as 70% for college instructors. In order for students to achieve the important learning outcomes from the courses for clinical practice, four program outcomes (POs) were selected as well as a rubric for each POs was developed. Students who had situation-based clinical practices showed higher levels of satisfaction on mastery of core basic nursing skills and communication skills. Conclusion: This findings of the study suggested the strategies for complementing pitfalls in clinical setting and achieving PO during students' clinical practicum.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.71-77
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• 2008

This study conducted to tried to find a way of on-line assessment of learner's interest and comprehension during interactive learning process. The result of experiment confirmed hat learners' behavior patterns acquired from log data could be good predictors of learner's level of interest and comprehension in actual performance on KORI program. To predict learning outcome depending on the behaviors of individual learners, self-efficacy and mastery goal orientation were measured as individual differences. Then, participants were asked to use TA program KORI program at home for ten days and their response patterns were recorded through network. After using KORI, the levels of interest and comprehension were measured. As the result of multiple regression analysis, each learner's interest and comprehension were predicted depending on the combination of log data captured on real-time. This prediction process was done differently depending on learners' characteristics. Since equations which predict learners' interest and comprehension are different depending on learners' characteristics, differential interfaces should be provided depending upon changes in their level of interest and comprehension.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1117-1128
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• 2002

This study suggests the most efficient teaching method by using multi-media. Based on the outcome of the engineering study, the multi-media and their contents will be applied to teaching methods, at first needing to provide concept and educational expecting effect of them. For multi-media using teaching methods, the study suggests the following 4; (1) teaching method for instructional learning, (2) teaching method for detective learning by guild, (3) teaching method for receptive loaming, (4) teaching method for exploration. Challenges still remained is to examine principles of teaching planning and relevant theories in order to apply the multi-media for the existing education, which should ask teachers in field to select more efficient teaching methods.

• Journal of the Korean Home Economics Association
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• v.41 no.3
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• pp.73-91
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• 2003

This research tested the path model which examined the direct and indirect effects of family violence experience on perpetration of dating violence among college students. Two family violence variables such as witnessing parents' marital violence and being abused by parent were the exogeneous variables in the path model, while the mediated variables were consisted of (1) the social-learning-theory-derived variables such as acceptance of violence, positive outcome expectations of using violence, and aggressive conflict-coping behavior, and (2) control-theory-derived variables such as attachment, belief, and commitment. Data were from self-administered questionnaires completed by 332 male and 469 female students selected by stratified quota sampling method. The path analysis was done for males and females separately, since females reported significantly higher degree of dating violence than males. Results of the path analysis showed that first, for both males and females, being abused by parents directly and indirectly influenced dating violence, while witnessing parents' marital violence did not have effect on dating violence either directly or indirectly. Second, for male students, acceptance of violence and conflict coping behavior found to be the mediated variables in the effect of being abused by parents on dating violence. Third, for females, a control-theory-derived variable of belief as well as all three social learning theory-derived variables mediated the influence of being abused by parents on dating violence.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.330-334
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• 2022

In light of the decreasing crop production and shortage of food across the world, one of the crucial criteria of agriculture nowadays is selecting the right crop for the right piece of land at the right time. First problem is that How Farmers can predict the right crop for cultivation because famers have no knowledge about prediction of crop. Second problem is that which algorithm is best that provide the maximum accuracy for crop prediction. Therefore, in this research Author proposed a method that would help to select the most suitable crop(s) for a specific land based on the analysis of the affecting parameters (Temperature, Humidity, Soil Moisture) using machine learning. In this work, the author implemented Random Forest Classifier, Support Vector Machine, k-Nearest Neighbor, and Decision Tree for crop selection. The author trained these algorithms with the training dataset and later these algorithms were tested with the test dataset. The author compared the performances of all the tested methods to arrive at the best outcome. In this way best algorithm from the mention above is selected for crop prediction.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.75-88
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• 2022

With the development of the sharing economy, existing recommender services are changing from user-item recommendations to user-user recommendations. The most important consideration is that all users should have the best possible satisfaction. To achieve this outcome, the matching service adds information between users and items necessary for the existing recommender service and information between users, so higher-level data mining is required. To this end, this paper proposes a user-to-user matching service (UTU-MS) employing the prediction of mutual satisfaction based on learning. Users were divided into consumers and suppliers, and the properties considered for recommendations were set by filtering and weighting. Based on this process, we implemented a convolutional neural network (CNN)-deep neural network (DNN)-based model that can predict each supplier's satisfaction from the consumer perspective and each consumer's satisfaction from the supplier perspective. After deriving the final mutual satisfaction using the predicted satisfaction, a top recommendation list is recommended to all users. The proposed model was applied to match guests with hosts using Airbnb data, which is a representative sharing economy platform. The proposed model is meaningful in that it has been optimized for the sharing economy and recommendations that reflect user-specific priorities.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.744-751
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• 2022

Construction is among the most dangerous industries with numerous accidents occurring at job sites. Following an accident, an investigation report is issued, containing all of the specifics. Analyzing the text information in construction accident reports can help enhance our understanding of historical data and be utilized for accident prevention. However, the conventional method requires a significant amount of time and effort to read and identify crucial information. The previous studies primarily focused on analyzing related objects and causes of accidents rather than the construction activities. This study aims to extract construction activities taken by workers associated with accidents by presenting an automated framework that adopts a deep learning-based approach and natural language processing (NLP) techniques to automatically classify sentences obtained from previous construction accident reports into predefined categories, namely TRADE (i.e., a construction activity before an accident), EVENT (i.e., an accident), and CONSEQUENCE (i.e., the outcome of an accident). The classification model was developed using Convolutional Neural Network (CNN) showed a robust accuracy of 88.7%, indicating that the proposed model is capable of investigating the occurrence of accidents with minimal manual involvement and sophisticated engineering. Also, this study is expected to support safety assessments and build risk management systems.

• Journal of the Korea Safety Management & Science
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• v.25 no.3
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• pp.63-71
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• 2023

The construction industry stands out for its higher incidence of accidents in comparison to other sectors. A causal analysis of the accidents is necessary for effective prevention. In this study, we propose a data-driven causal analysis to find significant factors of fatal construction accidents. We collected 14,318 cases of structured and text data of construction accidents from the Construction Safety Management Integrated Information (CSI). For the variables in the collected dataset, we first analyze their patterns and correlations with fatal construction accidents by statistical analysis. In addition, machine learning algorithms are employed to develop a classification model for fatal accidents. The integration of SHAP (SHapley Additive exPlanations) allows for the identification of root causes driving fatal incidents. As a result, the outcome reveals the significant factors and keywords wielding notable influence over fatal accidents within construction contexts.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.209-219
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• 2024

We studied the effects of science high school students on the change of epistemological beliefs in chemistry and the academic achievement of chemistry by completing 'advanced chemistry'. For seven months from July 2023 to January 2024, 80 first-year students at G Science High School in Gyeongnam were surveyed and analyzed for epistemological beliefs about chemistry before and after classes in advanced chemistry. Chemistry academic achievement was classified by 'upper' and 'lower' levels based on the end-of-semester grades of 'advanced chemistry' in the second semester of the first year and analyzed with the SPSS 28 program. After completing advanced chemistry, the epistemological belief in chemistry increased in the proportion of favorable responses. After completing advanced chemistry, the proportion of favorable responses increased in detailed factors such as 'effort', 'math link', 'outcome', 'reality link', and 'concepts', while the 'visualization' factor decreased. Although completing 'advanced chemistry' positively changed students' epistemological beliefs about chemistry, visual expression showed little contribution to understanding chemical concepts. Based on the above results, we will have to focus on the design of instructors' teaching-learning, such as learner-centered inquiry experiments, creative visual expressions, etc., for successful chemistry teaching-learning.

• Journal of Research and Publication Ethics
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• v.5 no.2
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• pp.7-10
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• 2024

Purpose: The effectiveness of research ethics education in enabling researchers to think and judge ethically in conducting research. It is a fundamental solution for the establishment of research ethics in the research field, not only for current researchers but also for the next generation. It measured various variables related to ethics that can lead to ethical behavior through a quasi-experimental design to support the reliability of the study. Research Design, data and methodology: Examine prior research on research ethics and explore current research ethics education and practice. It aims to study how to effectively implement and validate specific aspects of research ethics. To investigate, study, and validate research ethics education and research ethics systems. Results: It is defined as the effectiveness or value of training as measured by changes in knowledge and behavior in reaction, learning, behavior, and outcome evaluations measured after learning. Conclusions: For the effectiveness of research ethics education, various support measures need to be mobilized for the spread and establishment of research ethics education. Formalized and continuous research ethics education is needed. It is important that the knowledge acquired through long-term and consistent research ethics training is transferred to ethical behavior in the research field.