• Journal of Digital Convergence
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• v.13 no.1
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• pp.77-83
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• 2015

This study, according as the limits on learning and unsatisfaction about e-learning are emerging and the structural contradictions of the e-learning industry are continuing, was carried out to present the policy alternatives for solving these. As a means for overcoming the limitations of e-learning and the healthy growth of e-learning industry, this study presents the application of Bigdata in e-learning and proposes several practical challenges of policy. Policy action plans are technology development support, professional manpower support, SME application support, legal improvement.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1423-1431
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• 2018

IoT(Internet of Things) is applied to technologies such as agriculture and dairy farming, making it possible to cultivate crops easily and easily in cities.In particular, IoT technology that intelligently judge and control the growth environment of cultivated crops in the agricultural field is being developed. In this paper, we propose a method of predicting the growth environment of plants by learning the moisture supply cycle of plants using the intelligent object internet. The proposed system finds the moisture level of the soil moisture by mapping learning and finds the rules that require moisture supply based on the measured moisture level. Based on these rules, we predicted the moisture supply cycle and output it using media, so that it is convenient for users to use. In addition, in order to reduce the error of the value measured by the sensor, the information of each plant is exchanged with each other, so that the accuracy of the prediction is improved while compensating the value when there is an error. In order to evaluate the performance of the growth environment prediction system, the experiment was conducted in summer and winter and it was verified that the accuracy was high.

• Knowledge Management Research
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• v.13 no.2
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• pp.73-93
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• 2012

Although a wide range of theoretical researches have emphasized on the importance of knowledge management in cooperative R&D network, the empirical researches to synthetically examine the role of organizational learning and open innovation which influence on the performance of technological innovation are not enough to meet academic and practical demands. This study is to investigate the effect of open innovation and organizational learning in venture business on technological competitive advantage and establish the mediating role of organizational learning. For the purpose, the questionnaires, made based on the reviewing previous researches, were collected from 274 Korean venture businesses whose managerial focus is on developing technological innovation. As a result of analysis, the relational dimensions of open innovation - network, intensity and trust shared by a firm with external R&D partners - as well as the internal organizational learning system and competence have positive influence on building technological competitive advantage whose sub-variables are technological excellence, market growth potential and business feasibility. In addition, it is identified that organizational learning has the mediating and moderating effect in the relationship between open innovation and technological competitive advantage. These results imply that open innovation complements and expend the range of limited resources and the scope of innovation in technology-intensive small and medium-sized enterprises. Besides, organizational learning activity reinforces the use of knowledge and resources, obtained from external R&D partners. On the basis of these results, detailed issues and discussion were made in the conclusion.

• Journal of the Korea society of information convergence
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• v.7 no.1
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• pp.17-24
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• 2014

This study analyzed on web services status of World Class College(WCC)'s Teaching and Learning Center. WCC refers to colleges equipped with educational environment which can accommodate the needs of industry and growth potential and vision. Web services of WCC's Teaching and Learning Center consist of center introduction, teaching support, learning support, service, and specialized menu. This study analyzed on menu and specialized web services from 9 colleges out of total 21 colleges. This study is to propose a way of Teaching and Learning Center's web services which college's Teaching and Learning Center aims at by analyzing on web services of World Class College's teaching and learning center.

• Korea Journal of Hospital Management
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• v.24 no.4
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• pp.70-84
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• 2019

Purposes: Despite a lot of prior studies on psychological empowerment on positive outcomes, the objectives of this paper were to examine the role of psychological empowerment on informal learning and the mediation role of informal learning between psychological empowerment and outcome variables focused upon physical therapists working in hospital industry. Methodology: Using survey methods, the data were collected from 198 physical therapists who have worked in Ulsan city and attended in annual meeting. Findings: Results showed that psychological empowerment predicted informal learning positively but differences in mediational mechanism. Specifically, the path between psychological empowerment and proactive behavior partially mediated but no mediating effect between psychological empowerment and helping behavior. This study identified the main role of psychological empowerment on informal learning, and it expands on positive functions of the concept to learning area in organizations. The other results help advanced understanding of differential mechanism through informal learning in the process between psychological empowerment and both outcomes. Practical Implications: The current study contributes to expend the area of prior findings on psychological empowerment to learning activities implemented by individual volunteer effort. For hospitals operating the teams of physical therapy, the significance for considering psychological empowerment is highlighted as for individual growth related to job and for change behavior in the individual level.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.151-160
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• 2010

Learning progression is an advantageous way to describe the development of learner understanding about a topic. In the present study, learning progression is introduced to characterize novice teachers' professional knowledge and competence and to help designing teacher professional development programs in the developmental approach. The development and validation phases of learning progression are proposed in the paper. In addition a case study is presented to demonstrate the process of developing a learning progression for teaching-through-inquiry using ICT. The learning progression in novice teacher professional development can be used to assess the level of teacher understanding in specific topic and to effectively support the development of teachers' professional knowledge and competence via professional development programs in the longitudinal view.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.4
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• pp.534-547
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• 2014

Purpose: This study verifies the meaning on application experiences of learning portfolio in nursing students. Method: Participants of this study included 22 nursing students divided into 3 focus groups who had experienced on application of Learning Portfolio in university Y and university S in Kyungpook and Daegu, respectively. Data were collected from December 2013 to January 2014 through in-depth, recorded focus group interviews and subsequently analyzed via Colaizzi's (1978) phenomenological methodology. Results: The essential theme of this study is 'Finding a vision from confusion and suffering.' From 35 significant statements, 5 theme clusters, 16 themes and 32 sub themes were extracted from the essential meaning of the practical use of nursing student experiences. The five theme clusters were: Being a learning guide, Being a medium for communication, Providing an opportunity for inner growth, Difficulties about new learning, and Would like to no more in a better way. Conclusion: The results of this study contribute to providing direction to the formation of learning portfolios, which in turn enable nursing student to develop competency in self-directed learning. These findings indicate that an outcome-based nursing curriculum needs to consider the importance for nursing student's effective application of leaning portfolio.

• Educational Technology International
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• v.15 no.2
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• pp.89-115
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• 2014

This research aims to develop an elementary school English e-learning system based on the 'Self-determination theory (SDT)', which is widely applied to traditional face-to-face foreign language classes. The study also attempts to verify whether SDT-a traditional motivational theory that has been applied to face-to-face classes- is effective in an e-Learning environment with students who use this newly developed system. For the purposes of this project, the following three actions were carried out. First, a motivational strategy based on SDT was deduced. In SDT, the needs for autonomy, competence, and relatedness were introduced as basic psychological needs, and assumed that these three needs provided the natural motivation for learning, growth, and development. Second, an e-Learning system was created based on the deduced motivational strategy. Third, the system was implemented in 115 private tuition academies, and education was provided to 1,400 users for one year across the country. Afterwards, by surveying users, correlation between the role of the three psychological needs in learning English, and also the correlation between each need and motivation were investigated. Research results showed that traditional motivational theories used in face-to-face classes so far were effective in an e-Learning environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.27-33
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• 2023

Demands for eco-friendly food materials are increasing rapidly because of increased interest in well-being and health care, deterioration of air quality due to fine dust, and various soil and water pollution. Aquaponics is a system that can solve various problems such as economic activities, environmental problems, and safe food provision of the elderly population. However, techniques for deriving the optimal growth environment should be preceded. In this paper, we intend to design an intelligent plant growth measurement system that considers the characteristics of existing aquaponics. In particular, we would like to propose a module configuration plan for learning data and judgment systems when providing a uniform growth environment, focusing on designing systems suitable for production sites that do not have high-performance processing resources among intelligent aquaponics production management modules. It is believed that the proposed system can effectively perform deep learning with small analysis resources.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.48-60
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• 2024

With the exponential growth of satellite data utilization, machine learning has become pivotal in enhancing innovation and cybersecurity in satellite systems. This paper investigates the role of machine learning techniques in identifying and mitigating vulnerabilities and code smells within satellite software. We explore satellite system architecture and survey applications like vulnerability analysis, source code refactoring, and security flaw detection, emphasizing feature extraction methodologies such as Abstract Syntax Trees (AST) and Control Flow Graphs (CFG). We present practical examples of feature extraction and training models using machine learning techniques like Random Forests, Support Vector Machines, and Gradient Boosting. Additionally, we review open-access satellite datasets and address prevalent code smells through systematic refactoring solutions. By integrating continuous code review and refactoring into satellite software development, this research aims to improve maintainability, scalability, and cybersecurity, providing novel insights for the advancement of satellite software development and security. The value of this paper lies in its focus on addressing the identification of vulnerabilities and resolution of code smells in satellite software. In terms of the authors' contributions, we detail methods for applying machine learning to identify potential vulnerabilities and code smells in satellite software. Furthermore, the study presents techniques for feature extraction and model training, utilizing Abstract Syntax Trees (AST) and Control Flow Graphs (CFG) to extract relevant features for machine learning training. Regarding the results, we discuss the analysis of vulnerabilities, the identification of code smells, maintenance, and security enhancement through practical examples. This underscores the significant improvement in the maintainability and scalability of satellite software through continuous code review and refactoring.