• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.127-134
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• 2022

Recently, policies and research to prevent increasing construction accidents have been actively conducted in the domestic construction industry. In previous studies, the prediction model developed to prevent construction accidents mainly used only structured data, so various characteristics of construction sites are not sufficiently considered. Therefore, in this study, we developed a machine learning-based construction accident prediction model that enables the characteristics of construction sites to be considered sufficiently by using both structured and text-type unstructured data. In this study, 6,826 cases of construction accident data were collected from the Construction Safety Management Integrated Information (CSI) for machine learning. The Decision forest algorithm and the BERT language model were used to train structured and unstructured data respectively. As a result of analysis using both types of data, it was confirmed that the prediction accuracy was 95.41 %, which is improved by about 20 % compared to the case of using only structured data. Conclusively, the performance of the predictive model was effectively improved by using the unstructured data together, and construction accidents can be expected to be reduced through more accurate prediction.

• Korean Medical Education Review
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• v.19 no.3
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.20 no.3
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• pp.239-247
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• 2013

Purpose: This study was done to investigate the relationship between metacognition, learning flow, and problem solving ability in simulation learning of nursing students and to identify the factors influencing problem solving ability. Methods: The study sample was 136 nursing students. Data were collected from September to November, 2012 using a structured questionnaire on metacognition, learning flow and problem solving ability. Descriptive statistics, Pearson correlation and stepwise multiple regression analysis were used with the SPSS win 20.0 program to analyze the data. Results: There were significant positive correlations between metacognition, learning flow and problem solving ability. Learning flow was a significant factor affecting problem solving ability. These variables accounted for 33% of variance. Conclusion: These results suggest that simulation learning has a positive effect on nursing students' learning outcomes.

• The Korean Journal of Emergency Medical Services
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• v.27 no.1
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• pp.59-70
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• 2023

Purpose: This study was designed to identify the effects of social support, learning flow, and learning satisfaction on academic achievement in university students. Methods: This study involved university students who agreed to participate the investigation in D City using a structured online questionnaire from December 1, 2022 to December 31, 2022. Results: Social support, learning flow, learning satisfaction, and academic achievement had significant correlations. The influencing factors of academic achievement were age and learning flow, with an explanatory power of 20%. Conclusion: Further active management and attention are imperative for vulnerable students in high-age groups to search for the ways to improve learning flow.

• Journal of the Korean Geographical Society
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• v.35 no.4
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• pp.549-563
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• 2000

본 연구는 전통적인 교사위주의 설명식 수업을 벗어나 인터넷을 학습에 보다 효과적으로 활용하는 방법을 모색해 보고자 하는 것이다. 이를 위해 인터넷을 통하여 정보를 수집한 후에 그 내용을 재구성하여 홈페이지를 구축한 후 실험수업을 실시하였다. 실험수업의 결과 전통적인 수업반보다 인터넷 홈페이지를 활용한 수업반 학생들의 학업성취수준이 훨씬 높게 나타났다. 한편 인터넷 홈페이지를 활용한 실험수업밥의 겨우 구조적 수업반에 비해 비구조적 수업반 학생들의 학습성취도가 더 높게 나타났으나 그 차이는 유의적이지 않았다. 또한 수업 흥미도, 만족도, 학습의욕 등에도 실험반 학생들은 상당히 긍정적인 평가를 보였다. 본 연구를 통해 지리수업의 학습효과를 높이고 학생들의 흥미도를 높이기 위해서는 인터넷을 활용하는 수업형태가 바람직하다는 결과를 도출하였다. 특히 본 연구를 통해 앞으로 학생들의 학업성취도와 흥미도를 높이기 위해 인터넷을 수업에 활용하는 교수-학습설계의 개발이 필요함을 보여 주었다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.6-10
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• 1996

This paper presents an overview of research results obtained by the authors in a series of publications. Methods are developed both for time-varying and time-invariant for linear and nonlinear. for time domain and frequency domain . and for discrete-time and continuous-time systems. Among the topics presented are: 1. Learning control based on integral control concepts applied in the repetition domain. 2. New algorithms that give improved transient response of the indirect adaptive control ideas. 4. Direct model reference learning control. 5 . Learning control based frequency domain. 6. Use of neural networks in learning control. 7. Decentralized learning controllers. These learning algorithms apply to robot control. The decentralized learning control laws are important in such applications becaused of the usual robot decentralized controller structured.

• Journal of Korean Academy of Nursing Administration
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• v.15 no.1
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• pp.72-80
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• 2009

Purpose: To investigate the influence of a team learning climate on group performance of hospital nurses. Method: The subjects were 386 nurses who have been working in six hospitals. The data were collected by a structured questionnaire from January 20 to April 30 of 2006. The data were analyzed by SAS version 8.2, including descriptive statistics, Pearson correlation coefficient, and stepwise multiple regression. Results: The mean score of group performance was 3.38 and team learning climate was 4.89. The group performance was positively correlated with team learning climate(r=.40, p<.0001). The team learning climate explained 15% of the variance in group performance. Conclusion: The findings showed that team learning climate was an important factor in enhancing group performance in nursing organization. Therefore, the nurse manager will establish the strategies to improve the team learning climate of the nurses in order to promote organizational performance.

• Educational Technology International
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• v.16 no.1
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• pp.1-30
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• 2015

The purpose of this research is to propose a novel social LMS developed for group collaborative learning with a think-aloud tool integrated for sharing cognitive processes in order to improve group collaborative learning performance. In this developmental research, the system was designed with three critical elements: the think-aloud element supports learners through shared cognition, the social network element improves the quality of collaborative learning by forming a structured social environment, and the learning management element provides a understructure for collaborative learning for student groups. Moreover, the three critical elements were combined in an educational context and applied in three directions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.69-81
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• 2020

The objective of this study is to seek ways to maximize learning effects from e-learning by drawing improvement directions through investigating and analyzing an awareness of e-learning among e-learning attendees. The study was conducted among the attendees who are taking the e-learning program operated by K University and collected data from the students taking second semester in 2018 with the use of structured questionnaires. For data processing, SPSS Statistics 22.0 and AMOS were used, along with such analytical methods as frequency anslysis, descriptive statistical analysis, ANOVA (Analysis of Variance), t-analysis and cross tabulation. For significant data, it conducted an analysis by carrying out the Scheffe's test. According to the findings from this study, they showed a significant difference only in gender and curriculum desired to be opened in the question about e-learning participation motives per background factor. As for the learners' motives to study, it was confirmed that they tend to become more biased on time utilization and convenience of learning methods. The analysis of which factor of the three - learning factors, system factors and instructor's factors - has greatest effects on learning satisfaction indicated that learning factors influenced learning satisfaction the most in accordance with values for non-standard coefficient beta, followed by instructor factors which had a direct effect.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.90-99
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• 2016

Purpose: This study was conducted to examine effects of a learning portfolio by identifying the learning of nursing students taking a learning portfolio-utilized nursing management class. Methods: A non-equivalent control group pretest-posttest design was used. Participants were 83 senior students taking the nursing management course in one of the Departments of Nursing at 2 Universities. Experimental group (n=42) received a learning portfolio-utilized nursing management class 15 times over 15 weeks (3 hours weekly). Self-directed learning abilities, approaches to learning and learning flow of the participants were examined with self-report structured questionnaires. Data were collected between September 2 and December 16, 2014, and were analyzed using chi-square test, Fisher's exact test, independent t-test and ANCOVA with SPSS/PC version 21.0. Results: After the intervention the experimental group showed significant increases in self-directed learning abilities, deep approaches to learning and learning flow compared to the control group. However, no significant difference was found between groups for surface approaches to learning. Conclusion: Learning activities using the learning portfolios could be effective in cultivating the learning competency for growth of knowledge, technology and professionalism by increasing personal concentration and organization ability of the nursing students so that they can react to the rapidly changing environment.