• Title/Summary/Keyword: Learning climate

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Group Performance and the Team Learning Climate as Perceived by Hospital Nurse (임상간호사가 인지한 팀학습분위기와 집단성과)

  • Ko, Yu-Kyung
    • 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.

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The Mediating Effects of Participation Motivation on the Relationship between Organizational Learning Transfer Climate and Learning Transfer in Professional Engineers' Continuing Professional Development Activities (조직의 학습전이풍토가 기술사의 학습전이에 미치는 영향 - 계속전문교육(CPD) 참여 동기의 매개효과를 중심으로 -)

  • Bae, Eul Kyoo;Jung, Bo Ra;Lee, Min Young
    • Journal of Engineering Education Research
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    • v.16 no.2
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    • pp.11-23
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    • 2013
  • The main purpose of this study was to examine the mediating effect of participation motivation of continuing professional development between the level of organizational learning transfer climate and learning transfer. In the analysis of the relationship among the level of the organizational learning transfer climate, learning transfer and participation motivation of CPD, organizational learning transfer climate had indirect influence on learning transfer through participation motivation of CPD. Based upon the findings of this study, several suggestions were made to improve professional engineers' participation and learning transfer in CPD and implement future research on professional engineer's CPD.

Comparison of Reflection Hierarchy, Team Learning Climate, and Learning Organization Building on Nursing Competency in Clinical Nurses (간호역량 군집 유형에 따른 성찰 수준, 팀학습 분위기 및 학습조직 구축정도 비교)

  • Kim, Heeyoung;Jang, Keum Seong
    • Journal of Korean Academy of Nursing Administration
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    • v.19 no.2
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    • pp.282-291
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    • 2013
  • Purpose: The purpose of this study was to identify clusters of nursing competency, and investigate the influence of reflective thinking, team learning climate, and learning organization building according to nursing competency clusters. Methods: Participants were 244 clinical nurses who worked in 4 general hospitals in Gwangju Metropolitan City. Data were collected by self-report questionnaires during June and July, 2011. Nursing competency, levels of reflection hierarchy, team learning climate, and learning organization building were measured. Data were analyzed using frequencies, means, t-test, one-way ANOVA, Pearson correlation coefficients, and K-means cluster analysis with SPSS/WIN 20.0 version. Results: Nursing competency correlated positively with intensive reflection, reflection, team learning climate, and learning organization building (p<.001). There were three clusters of nursing competency in a clinical ladder, which were derived from cluster analysis, grouped as high, middle, and low competency. Intensive reflection, reflection, team learning climate, and learning organization building showed significant differences according to grouping of nursing competency. Conclusion: The results indicate that developing intensive reflection, reflection, team learning climate, and learning organization building would be useful strategies for enhancement of nursing competency.

Effects of Climate Change Project Learning on Elementary School Students' Perceptions and Attitudes Toward Climate Change and Environmental Literacy (기후변화 프로젝트 학습이 초등학생의 기후변화에 대한 인식 및 태도, 환경소양에 미치는 영향)

  • Jang, Junyong;Kang, Jihoon;Yoo, Pyoungkil
    • Journal of Korean Elementary Science Education
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    • v.43 no.1
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    • pp.158-169
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    • 2024
  • This study investigated the effects of climate change project learning on elementary students' attitudes toward climate change and environmental literacy. Climate change project learning was conducted on 174 sixth-grade elementary school students in a metropolitan city (77 male, 97 female), after which their perceptions and attitudes toward climate change and environmental literacy were assessed. The climate change project learning had a positive effect on the students' perceptions and attitudes toward climate change, which was surmised because of the climate change content sharing and discussions during the project learning. The climate change project learning also had a positive effect on the students' environmental literacy, especially their environmental attitudes, values, and behavior; however, there were no statistically significant changes found for environmental sensitivity. This study highlights the educational effects and implications of environmentally focused climate change projectbased education for elementary school students.

Calculated Damage of Italian Ryegrass in Abnormal Climate Based World Meteorological Organization Approach Using Machine Learning

  • Jae Seong Choi;Ji Yung Kim;Moonju Kim;Kyung Il Sung;Byong Wan Kim
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.43 no.3
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    • pp.190-198
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    • 2023
  • This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMYnormal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

Deep Dependence in Deep Learning models of Streamflow and Climate Indices

  • Lee, Taesam;Ouarda, Taha;Kim, Jongsuk;Seong, Kiyoung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.97-97
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    • 2021
  • Hydrometeorological variables contain highly complex system for temporal revolution and it is quite challenging to illustrate the system with a temporal linear and nonlinear models. In recent years, deep learning algorithms have been developed and a number of studies has focused to model the complex hydrometeorological system with deep learning models. In the current study, we investigated the temporal structure inside deep learning models for the hydrometeorological variables such as streamflow and climate indices. The results present a quite striking such that each hidden unit of the deep learning model presents different dependence structure and when the number of hidden units meet a proper boundary, it reaches the best model performance. This indicates that the deep dependence structure of deep learning models can be used to model selection or investigating whether the constructed model setup present efficient or not.

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A Study on the Development of Environment Design STEAM Program in Coping with Climate Change for Elementary School Students (초등학생을 위한 기후변화대응 환경디자인 STEAM 교육프로그램 개발 연구)

  • Lee, Yun-Hee;Lee, Myung-A;Han, Hae-Ryon;Ban, Ja-Yuen
    • Korean Institute of Interior Design Journal
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    • v.25 no.6
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    • pp.15-22
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    • 2016
  • Recent changes in the Korean education policies are promoting the advances in science and technology and cultivating people of convergence talent. STEAM (science, technology, engineering, art and math) educational program is Korean styled convergence program for creative competent human resources. Therefore, Therefore the aim of this study is developing convergence hand-on educational program coping with climate change for elementary school students. For development of the program, we investigated the curriculum of the elementary school about the climate change, and allocated in the creative learning standard frame. Also, we selected themes related the climate change in the curriculum and learning activity. For more effective program to build the convergence competency, we analyzed the program based on creative problem based learning process and 4 core competency(creativity, communication, convergence, caring) elements. In conclusion, the STEAM program needs to develop by school curriculum and leaner's ability. For elementary school students, the STEAM program consists with creative problem based learning process. And the convergence educational program would analyze by the creative PBL process and convergence competency elements. So, this developing program has brought the promotion of the creative convergence competent talented person for the future global environment.

An Empirical Study on the Relationships among Employee Silence, Learning Inertia, and Knowledge Sharing Disengagement (구성원 침묵, 학습관성, 지식공유 비열의 간의 관계에 관한 실증연구)

  • Heo, Myung Sook;Cheon, Myun Joong
    • Knowledge Management Research
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    • v.18 no.4
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    • pp.31-62
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    • 2017
  • It found that employee silence negatively impacts both organizations and their employees as shown in findings from many studies and recently there has been a growing interest in it. Silence is described as intentionally withholding job-related ideas, information, concerns, and opinions. Employee silence may decrease organizational change and innovation and reduce employee learning motivation and knowledge sharing engagement as well. The purpose of this study is to examine the relationships among silence motivations, perceived silence climate, and employee silence; the relationships among employee silence, learning inertia and knowledge sharing disengagement; the mediating role of employee silence between antecedents of employee silence and consequences additionally. The results that analyzed using data from 225 employees in 42 organizations are as follows. First, the impact of silence motivation and perceived silence climate on employee silence are positively significant. Second, the influence of defensive silence motivation on the acquiescent and relational silence motivation is positively significant. Third, the influence of employee silence on learning inertia and knowledge sharing disengagement is positively significant. Forth, employee silence mediates the relationship between silence motivation and perceived silence climate and learning inertia and knowledge sharing disengagement. These results suggest that employee silence is another strong expression and message for organizations to try to establish a learning organization from the perspective of knowledge management.

The Mediating Effect of Self-Determined Motivations on Relation between Class Climate Perceived by Middle School Students and Self-Regulated Learning Ability (중학생이 지각한 학급풍토와 자기조절학습능력과의 관계에서 자기결정성동기의 매개효과)

  • Kim, Yoo-Lee
    • The Journal of the Korea Contents Association
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    • v.19 no.6
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    • pp.605-619
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    • 2019
  • This study aimed to examine the mediating roles of self-determined motivations on the effect of class climate perceived by middle school students on self-regulated learning ablility. For this purpose, a total of 589 students were selected as subjects in this research. Structural equation modeling was conducted so as to verify the relationship among all the variables. As a results, first, the perceived autonomous class climate had a direct effect on self-regulated learning ability and an indirect effect on self-regulated learning ability through the mediation effect of identified regulation. Second, the perceived controlled class climate had a direct effect on self-regulated learning ability and an indirect effect on self-regulated learning ability through the mediation effect of identified regulation, introjected regulation, and external regulation. This study implies that facilitating autonomous engagement in learning activities will be a effective educational intervention to improve self-regulated learning ability.

In the relationship between design competency strengthening education for designers and individual performance, Mediating effect of learning self-efficacy and corporate learning transfer climate (디자이너 대상 디자인 역량강화교육과 개인성과와의 관계에서 학습 자기효능감과 기업 학습전이풍토의 매개효과)

  • Kim, Gun-Woo;Kim, Sun-Ah
    • Journal of Digital Convergence
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    • v.20 no.5
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    • pp.897-908
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    • 2022
  • The purpose of this study is to prove the hypothesis that the learning transfer climate, such as individual learning self-efficacy and corporate innovative knowledge transfer, will play a mediating role in the relationship between design competency strengthening education and individual performance considering the designer's characteristics. This is meaningful in expanding the meaning of design education and training by quantitatively analyzing the learning transfer climate that affects learning self-efficacy and organizational culture according to the characteristics of designers, unlike existing studies that simply investigate the satisfaction of education. Specifically, this study set up seven hypotheses, and as a result, it was found that design capacity building education for designers, learning self-efficacy, and learning transfer climate of companies had a significant effect on individual performance.