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간호대학생의 자기주도학습과 전이동기가 임상실습 중 학습전이에 미치는 영향
한은비(Eunbi Han),조수현(Soohyun Cho),조효진(Hyojin Cho),박수현(Soohyun Park) 한국콘텐츠학회 2021 한국콘텐츠학회논문지 Vol.21 No.2
본 연구는 간호대학생의 임상실습 중 학습전이 정도를 알아보고 학습전이에 영향을 미치는 요인을 파악하고자 시도하였다. 자료 수집은 2019년 6월부터 7월까지 S시에 위치한 일개 간호학과 재학 중인 3, 4학년 학생 113명을 대상으로 편의표집 하였다. 수집된 자료는 서술통계, 독립 t-검정, ANOVA 및 Scheffé test, Pearsons correlation coefficients, Stepwise multiple regression을 사용하여 분석하였다. 대인관계가 좋을수록, 전공만족도가 높을수록, 교내실습 만족도가 높을수록 학습전이가 높게 나타났고, 학습전이는 전이동기와는 강한 양의 상관관계(r=.60, p=<.001), 자기 주도적 학습능력사이에는 다소 강한 양의 상관관계(r=.46, p=<.001), 자기 주도적 학습능력 세부 영역에서는, 학습평가(r=.49, p=<.001), 학습계획(r=.41, p=<.001), 학습실행(r=.32, p=<.001) 순으로 양의 상관관계를 보였다. 학습전이의 영향요인은 전이동기(ß=0.43), 학습평가 (ß=0.21) 및 교내실습 만족도(ß=0.22) 이었고 총 설명력은 43%이었다. 따라서, 실습중인 간호대학생의 학습전이를 높이기 위해서 전이동기를 높이고 자기주도적 학습평가를 높이는 교육전략과 교내실습 만족도를 높이기 위한 실습환경 및 교수학습법 적용이 필요하겠다. The purpose of this study was to identify factors influencing the transfer of learning for nursing students in clinical practice. This study is a descriptive survey research conducted with 113 nursing students. Self-directed learning, motivation to transfer, and transfer of learning were measured. Data were analyzed by descriptive analysis, independent t-test, and ANOVA. The transfer of learning were significantly different according to the interpersonal relationship (t=10.43, p=.002), the satisfaction of nursing major (t=3.81, p=.006), satisfaction of nursing skills laboratory (t=4.61, p=.004). Transfer of learning had a correlation with self-directed learning, motivation (r=.46, p=<.001), and motivation to transfer (r=.60, p=<.001). In addition, motivation to transfer, the satisfaction of nursing skills laboratory, and learning evaluation were significant predictors of transfer of learning. Finally, in order to increase the transfer of learning for nursing students, nursing instructors need to encourage motivation to transfer, and to apply educational strategies that increase self-directed learning, as well as the satisfaction of the nursing skills laboratory.
( Eunbi Ko ),( Kyoungmin Cho ),( Ji Hye Kim ),( Hyun-jung Shin ),( Byung-fhy Suh ),( Hye One Kim ),( Taeyoung Park ) 한국피부장벽학회 2023 한국피부장벽학회지 Vol.25 No.2
Customers have used various skin care and functional cosmetics to prevent their skin aging as well as improve current condition of the skin. It is important to analyzing and understanding their skin to select optimized skin care solutions. The aim of this study is to quantitatively analyze the effect of environment, lifestyle, and innate genes on the current skin condition. For this purpose, degree of hydration, sebum, wrinkles, melanin, dullness and redness in a highly controlled condition were collected in conjunction with a questionnaire survey analyzing their lifestyles and genetic data from about 3000 women. We classified participants based on the types of skin, using 6 kinds of index representing skin properties, questionnaire survey on lifestyle and genetic data with Gaussian Mixture Model and Decision Tree for classification model. Through this study, it was possible to divide the skin of Korean women into 12 clusters according to wrinkles, melanin, redness, dullness and oil/moisture balance with Gaussian Mixture Model. Also, we were able to identify a pattern in which each factor was correlated. Next, we tried to discover factors for predicting skin condition changes through correlation analysis with lifestyle, climate/environment, and innate genes that affect the current skin condition. Ultimate purpose of this study is to predict future skin condition using big data and AI technology. This knowledge will enable us to provide more proactive and personalized solutions not only for cosmetics but also for life care such as lifestyle, eating habits, and environmental response.
Fast switching of nematic liquid crystals using a new alkyl-free bifunctional mesogenic monomer
Lee, Eunbi,Son, Intae,Moon, Gitae,Kim, Chunho,Cho, Chi Hyeong,Bae, Eun Hyoung,Min, Changsu,Kang, Taehyeon,Lee, Jun Hyup Informa UK (TaylorFrancis) 2019 MOLECULAR CRYSTALS AND LIQUID CRYSTALS - Vol.678 No.1
개인 피부 특성, 라이프스타일, 유전자 데이터 기반 진단 알고리즘 개발
고은비 ( Eunbi Ko ),( Kyoungmin Cho ),( Ji Hye Kim ),( Hyun-jung Shin ),( Byung-fhy Suh ),( Hye One Kim ),( Taeyoung Park ) 한국피부장벽학회 2023 한국피부장벽학회지 Vol.25 No.2
Customers have used various skin care and functional cosmetics to prevent their skin aging as well as improve current condition of the skin. It is important to analyzing and understanding their skin to select optimized skin care solutions. The aim of this study is to quantitatively analyze the effect of environment, lifestyle, and innate genes on the current skin condition. For this purpose, degree of hydration, sebum, wrinkles, melanin, dullness and redness in a highly controlled condition were collected in conjunction with a questionnaire survey analyzing their lifestyles and genetic data from about 3000 women. We classified participants based on the types of skin, using 6 kinds of index representing skin properties, questionnaire survey on lifestyle and genetic data with Gaussian Mixture Model and Decision Tree for classification model. Through this study, it was possible to divide the skin of Korean women into 12 clusters according to wrinkles, melanin, redness, dullness and oil/moisture balance with Gaussian Mixture Model. Also, we were able to identify a pattern in which each factor was correlated. Next, we tried to discover factors for predicting skin condition changes through correlation analysis with lifestyle, climate/environment, and innate genes that affect the current skin condition. Ultimate purpose of this study is to predict future skin condition using big data and AI technology. This knowledge will enable us to provide more proactive and personalized solutions not only for cosmetics but also for life care such as lifestyle, eating habits, and environmental response.
Jeong, Eunbi,Oh, Cheol,Lee, Gunwoo,Cho, Hanseon U.S. National Research Council, Transportation Res 2014 Transportation Research Record Vol.2424 No.-
<P> Driver inattentiveness is one of the critical factors that contribute to vehicle crashes. The intervehicle safety warning information system (ISWS) is a technology to enhance driver attentiveness by providing warning messages about upcoming hazards under the connected vehicle environments. A novel feature of the proposed ISWS is its capability to detect hazardous driving events, which are defined as moving hazards with a high potential to cause crashes. The study presented in this paper evaluated the potential effectiveness of the ISWS to reduce crashes and to mitigate traffic congestion. The study included a field experiment that documented actual vehicle maneuvering patterns of accelerations and lane changes, which were used to enhance the realism of simulation evaluations. Probe vehicles equipped with customized onboard units, which consisted of a GPS device, accelerometer, and gyro sensor, were used. A microscopic simulator, VISSIM, was used to simulate a driver’s responsive behavior after warning messages were delivered. A surrogate safety assessment model was used to derive surrogate safety measures to evaluate the effectiveness of ISWS in terms of traffic safety. The results showed a reduced number of rear-end conflicts when the ISWS’s market penetration rate (MPR) and the congestion level of the traffic conditions increased. The reduced number of rear-end conflicts was approximately 84.3%, with a 100% MPR under Level of Service D traffic conditions. Analysis of the standard deviation of speed showed that a reduction of 39.9% was achieved. The outcomes of this study could be valuable to derive smarter operational strategies for ISWS. </P>