• The Journal of Korean Association of Computer Education
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• v.15 no.6
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• pp.65-74
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• 2012

Wiki is an online-based collaborative tool, and has been frequently used more recently as it realizes the paradigm of web 2.0 in educational context. Especially, wiki promotes collaborative knowledge building which is the major interest of this study. The purpose of this research is to investigate the relationships among academic self-efficacy, self-efficacy for group work, wiki anxiety, participation in wiki activity, and learning achievement. Fifty nine college students participated in the wiki activity, and the data from fifty three were used for the multiple regression and path analysis. The results reported that academic self-efficacy and wiki anxiety affected participation in wiki activity, and these two variables also had indirect effects on learning achievement, mediated by participation.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.235-243
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• 2013

This study deals with the methods of improving about effects of Teaching-Learning Activities Based Smart learning on Learning Attitudes and the Attention of Students with Intellectual Disorders. Analysis method of the data in this study included comparison pre-and post test among the two groups( experimental group and control group) first, indicated that the experimental group showed that significantly greater improvement in the Learning Attitudes. Seconds, As for the attention of the two groups, the experimental group maintained their attention at relatively similar levels throughout the study period, while the attention of the control group had shortened toward the end of the study. These results suggest that the Teaching-Learning Activities Based Smart learning through authoring tool was highly effective in improving mentally with Intellectual Disorders' Learning Attitudes and attention.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.677-689
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• 2024

The quality of life, frailty, economic activity, and other indicators are crucial for assessing older adults' overall well-being and health status. A comprehensive evaluation using this information helps predict the health status of older adults. This study aims to apply and compare machine learning-based prediction models for comprehensive health indicators of community-dwelling older adults. Utilizing data from 4,652 individuals provided by the Aging Research Panel, we assessed various machine learning techniques to fit the predictor variables. Our findings reveal that the LightGBM Regression model performed the best, with an RMSE of 5.082 and an MSE of 25.83. The Gradient Boosting model best predicted current health status, with an RMSE of 0.588 and an R-Square of 0.456. Additionally, the Random Forest model showed strong performance in predicting economic activity participation among older adults. These machine learning-based models offer valuable insights for evaluating health status and predicting economic activity participation, highlighting the importance of employing diverse methodologies for comprehensive predictions.

• Journal of The Korean Association For Science Education
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• v.35 no.4
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• pp.599-608
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• 2015

This study aims to explore the characteristics of student inquiry found in project-based science practices. The participants were four high school students in a science research club and worked their own project for one semester. During the project, they made their research questions, planned and executed their research procedures, and made their own conclusion. Their activities during the project were videotaped and recorded. They were also interviewed. Group worksheets and written reports were all collected for analyses. The whole processes of the inquiry were analyzed and interpreted qualitatively. The characteristics of student inquiry were presented in the view of the theory-evidence-method coordination. Three different modes of the coordinations that were found recursively in their inquiry were the theory-evidence coordination, the evidence-method coordination, and the theory-evidence-method coordination. It was also revealed that students' tacit knowledge using various tools were exhibited and these skills improved during their group works. The implications for school science inquiry education and research based on this study are discussed.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.18-36
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• 2024

As interest in ESG has been increased, it is easy to find papers that empirically study that a company's ESG activities have a positive impact on the company's performance. However, research on what ESG activities companies should actually engage in is relatively lacking. Accordingly, this study systematically classifies ESG activities of companies and seeks to provide insight to companies seeking to plan new ESG activities. This study analyzes how Chinese manufacturing companies perform ESG activities based on their dynamic capabilities in the global economy and how they differ in their activities. This study used the ESG annual reports of 151 Chinese manufacturing listed companies on the Shanghai & Shenzhen Stock Exchange and ESG indicators of China Securities Index Company (CSI) as data. This study focused on the following three research questions. The first is to determine whether there are any differences in ESG activities between companies with high ESG scores (TOP-25) and companies with low ESG scores (BOT-25), and the second is to determine whether there are any changes in ESG activities over a 10-year period (2010-2019), focusing only on companies with high ESG scores. The results showed that there was a significant difference in ESG activities between high and low ESG scorers, while tracking the year-to-year change in activities of the top-25 companies did not show any difference in ESG activities. In the third study, social network analysis was conducted on the keywords of E/S/G. Through the co-concurrence matrix technique, we visualized the ESG activities of companies in a four-quadrant graph and set the direction for ESG activities based on this.

• Science & Technology Policy
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• v.10 no.4 s.124
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• pp.104-118
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• 2000

• NEWSLETTER 전기공업
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• no.95-5 s.126
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• pp.2-17
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• 1995

• 월간낙농육우
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• v.31 no.11
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• pp.89-95
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• 2011

• Proceedings of the Korea Association of Information Systems Conference
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• 2004.11a
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• pp.366-379
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• 2004

• 월간 한농연
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• s.56
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• pp.32-35
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• 2006