• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.1-7
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• 2022

Robots are widely used in industries and services. Traditional robots have been used to perform repetitive tasks in a fixed environment, and it is very difficult to solve a problem in which the physical interaction of the surrounding environment or other objects is complicated with the existing control method. Reinforcement learning has been actively studied as a method of machine learning to solve such problems, and provides answers to problems that robots have not solved in the conventional way. Studies on the learning of all physical robots are commonly affected by noise. Complex noises, such as control errors of robots, limitations in performance of measurement equipment, and complexity of physical interactions with surrounding environments and objects, can act as factors that degrade learning. A learning method that works well in a virtual environment may not very effective in a real robot. Therefore, this paper proposes a weighted sum method and a linear regression method as an effective and accurate learning method in a noisy environment. In addition, the bottle flipping was trained on a robot and compared with the existing learning method, the validity of the proposed method was verified.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1820-1831
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• 2010

When interacting with unknown environments, an autonomous agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. The traditional multiple sequential learning model requires predefined probability of the states' transition. This paper proposes a multiple sequential learning and prediction system with definition of autonomous states to enhance the automatic performance of existing AI algorithms. In sequence learning process, the sensed states are classified into several group by a set of proposed motivation filters to reduce the learning computation. In prediction process, the learning agent makes a decision based on the estimation of each state's cost to get a high payoff from the given environment. The proposed learning and prediction algorithms heightens the automatic planning of the autonomous agent for interacting with the dynamic unknown environment. This model was tested in a virtual library.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.1083-1090
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• 2003

Web-based learning is currently an active area of research and a considerable number of studies have been conducted on its application in the learning environment. However, in spite of many advances in the research and development of the educational contents, questions about how the environment affects learning remains largely unanswered. In this article, we propose a Web-based learning environment to improve the educational effect. The goal of this article is not to provide a complete system to support Web-based learning but rather to describe some meaningful strategies and fundamental design concepts that utilize information technologies to support teaching and learning.

• Korean Journal of Childcare and Education
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• v.8 no.6
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• pp.241-256
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• 2012

This purpose of this study was to examine the mediating effects of child care efficacy on the relationship between professional learning environment and turnover intention. For this purpose, we conducted a questionnaire survey with 237 child care teachers. The results of this study are summarized as follows. First, when child care teachers had low professional learning environment or low efficacy, their job turnover intention and occupational turnover intention improved. Second, job turnover intention and occupational turnover intention was affected by professional learning environment. Third, child care efficacy mediated between professional learning environment and occupational turnover intention.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.1
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• pp.108-117
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• 2011

The purpose of this study was to analyze the association between educational environment (physical environment of cooking institutes and curriculum) and satisfaction with learning of students at local cooking institutes. Self-administered questionnaires were distributed to 300 student enrolled at cooking institutes located in Pohang and Gyeongju, and a total of 265 were usable. Collected data were statistically analyzed using SPSS 12.0 by frequency, factor, reliability, t-test and Duncan's multiple range test. The results can be summarized as follows. Most of the subjects were enrolled at cooking institutes to learn Korean and Western cuisine. There were significant differences in learning according to institution, facility, method and instructor. There were also significant differences in learning according to gender, age, education, and attended classes. Based on the results, the physical environment of cooking institutes contributed to learning in the students, but the operation system also needs to be improved. However, study was limited in sample size and area, the results can-not be generalized.

• Hwankyungkyoyuk
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• v.20 no.3
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• pp.31-44
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• 2007

The solution of the environment problem is the common issue all over the world, for this reason the necessity of the environmental education of school has emphasized. On this a variety method for environmental education is needed, this paper planned and applied the 'ecology & environment' for high school which are based on GBS theory and presented a new model of environment education. GBS(Goal-Based Scenario) is that learners are presented with an end goal that is motivating and challenging. This goal is structured such that, in order to successfully meet it learners are required to build a predetermined core set of skills and knowledge by process mission and scenario. GBS is an active learning environment in which learners are trained in study that have a real-world context. When they are back in real-world they have increased ability to apply what was learned by reflecting on the GBS learning experience. This study was designed on GBS theory and taught a class by using internet Blog. As a result, when carefully reviewing the materials such as final presentation reflect journal, we conclude that the students' awareness of a learning environment is improved and the students seems to try to apply the learning outcome to a real life.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.18 no.3
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• pp.365-372
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• 2011

Purpose: The purpose of this study was to examine the effects of the teaching effectiveness and clinical learning environment on the clinical practice competency in nursing students. Method: Undergraduate nursing students (268) enrolled in one of 4 universities in 2 cities completed a survey questionnaire. Collected data were analyzed using descriptive statistics, Pearson's correlation coefficient and multiple regression with the SPSS/Win 11.0 program. Results: The mean score for teaching effectiveness was 3.09 (${\pm}.53$) on a 5-point scale, for clinical learning environment, 3.09 (${\pm}.50$) on a 5-point scale, and for clinical practice competency, 3.94 (${\pm}.52$) on a 6-point scale. Significant positive correlations were found between teaching effectiveness and clinical learning environment, and clinical practice competency. The regression model explained 8.8% of clinical practice competency. Teaching effectiveness and clinical learning environment were significant predictors of clinical practice competency. Conclusion: The findings of the study suggest that teaching effectiveness and clinical learning environment be considered when developing strategies to increase clinical practice competency in nursing students.

• Journal of muscle and joint health
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• v.30 no.3
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• pp.197-207
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• 2023

Purpose: This study attempted to discern the factors that influence nursing professionalism, learning agility, and the nursing practice environment on the performance of nurses. Methods: Data were collected from 202 clinical nurses who both consented to participate and who have worked for more than one year in one of five small- and medium-sized hospitals located in three regions of Korea. The data were analyzed using the SPSS/WIN 26.0 statistical programs. Results: The nurses' performance showed a statistically significant correlation with nursing professionalism (r=.50, p<.001), learning agility (r=.54, p<.001), and nursing practice environment (r=.37, p<.001). Factors affecting the results of nurses' performance in relation to the subjects are those of learning agility (β=.33, p<.001), nursing professionalism (β=.25, p<.001), clinical career (β=.24, p=.001), education level (β=.16, p=.011), and nursing practice environment (β=.15, p=.016). Conclusion: To improve the performance of nurses in medium-sized hospitals, it is necessary to develop a nursing practice environment, programs, and strategies for enhancing nursing professionalism and learning agility.

• The Journal of Korean Association of Computer Education
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• v.9 no.2
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• pp.27-36
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• 2006

This study intends to present essential models for collaborative learning in e-learning environment as well as to analyze learning behavior elements appearing in collaborative learning activities. In order to achieve goal of the study, the researchers analyzed existing cooperative learning models for face-to-face classroom, collaborative activity models based on instructional theory, and the structures and activities elements of learning community and collaborative activity models focusing on e-learning environment. As a result of the study, the researchers produced a generalizable collaborative learning model for e-learning which include general collaborative learning model, and further analyzed specific learning behaviors performed by learners while they proceed in this model based learning processes. The adequacy of this model and reliability of learning behavior elements were tested through experts' review meetings. The research result, suggesting generalizable collaborative learning model as well as learning behaviors elements which might occur within e-learning based collaborative learning, might work as a foundational model for software infrastructure and e-learning solution business. Moreover, its value might be maximized if its being used for enhancing learning content interoperability and reuse as well as for establishing international standardization for collaborative technology.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.103-113
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• 2018

The purpose of this study supports the establishment of national e-learning policy by analyzing e-learning status and current status of higher education. Enhance the competitiveness of higher education through sharing information between universities. And to improve e-learning quality management. We surveyed the current status of e-learning in 341 universities and questionnaires about e-learning content, e-learning application form, e-learning platform status was surveyed through each school's learning management system. As a result, the infrastructure of e-learning, the rate of platforms secured, and the contents are increasing gradually each year; however, still, not all students can receive the services equally. Dedicated servers and learning management systems were secured by more than 70% of general universities. In the current development status of e-learning content, multimedia, animation, and text forms are gradually decreasing, but video contents are increasing every year. Most of the online contents were used in the e-learning contents by application type, and blended learning, flipped learning, and mooc is not yet actively used since they are still in the beginning stage. Learning analysis techniques should be supported in order to easily use online learning contents such as flipped learning and mooc. We suggest that the effectiveness of e-learning should be measured and the current state of learning analysis for customized learning should be done. This study aims to contribute to the improvement of competitiveness of higher education by sharing information about e-learning among universities as a basis for improvement of e-learning policy. Future tasks are to improve the customized learning environment by adding whether the system environment for learning analysis is provided at the time of the survey.