• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.4
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• pp.321-340
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• 2017

The purpose of this study is to design a teaching model applying a problem-based learning model and to analyze the educational benefits that students felt. This study initiated a problem-based learning model from an analysis of existing studies. Through the consultation of experts, the scenario was modified. The problem was designed according to the design stage activity (problem analysis, PBL class suitability judgment, contents analysis, learner analysis, environment analysis, PBL operating environment decision, PBL class) and Strategic Design (problem situation design, learning resource design, Facilitation design, operational strategy design, evaluation design, PBL operating environment design). Based on the initial scenarios, the researcher analyzed the results of the problem - based learning through learners' reflective diaries. The researcher was able to confirm that the critical thinking and creativity were improved in the first PBL problem situation, and the method for smooth communication and cooperation was utilized. The results on analyzing the effects of education about the first problem-based learning and students' opinions about modification will be used for the second revision and supplement of the course design. This study introduces a case of PBL course development and expects further application and research.

• Journal of Korean Home Economics Education Association
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• v.20 no.4
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• pp.19-42
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• 2008

The purpose of this study was to develop practical problem-based home economics teaching.learning process plans about a unit 'the youth and consumer life' of middle school eighth-grade Technology and Home Economics by applying blended learning(BL) strategy. According to ADDIE instructional design model, this study was conducted in the following procedure: analysis, design/development, implementation, and evaluation. In the stage of design and development, the selected unit was converted into a practical problem-based unit, and practical problem-based teaching. learning process plans were designed in detail by using BL strategy. An online study room for practical problem-based home economics instruction grounded in BL strategy was prepared by using Edunet(http://community.edunet4u.net/${\sim}$consumer2). Eight-session lesson plans were mapped out, and study aids for students and materials for teachers were prepared. In the implementation stage, the first-session teaching plans that dealt with a minor question 'what preparations should be made to become a wise consumer' were utilized when instruction was provided to 115 eighth graders who were in three different province, and the other one was in a middle school in the city of Daejeon. The experimental teaching was implemented for two weeks in the following procedure: preliminary program, pre-online learning, main instruction and post- online learning. The preliminary program was carried out in a session in the classroom, and pre-online learning was provided before the main instruction was given in a session in the classroom. After the main instruction was completed, post-online learning was offered. In the evaluation stage, a survey was conducted on all the learners and teachers to find out their opinions and suggestions.

• Journal of The Korean Association For Science Education
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• v.32 no.1
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• pp.95-112
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• 2012

The research evaluated the effects of the improvements in scientific inquiry for elementary school students and focused on the development and application of the explicit and reflective learning strategy through observation and classification. The explicit and reflective learning strategy was modified and completed with the review of the experts after the development of the draft based on the theoretical approach. The students were evaluated for their academic achievements in scientific inquiry skills before and after taking the course. The results were as follows: First, the steps of the developed learning strategy (1) to motivate, (2) to explore reflectively, (3) to guide explicitly, (4) to inquire explicitly, and (5) to verify reflectively were set to reflect the verification. Second, the results of applying the developed model to the lessons based on the quantitative analysis was effective for observation and classification skills in the quest for improved performance of the whole (the sum of observation and classification, inquiry skills) and the observed features, but there was no effect on classification. Also, the lessons applied the developed teaching strategy and showed effectiveness in improving academic achievement. Particularly in analyzing the relationship between the academic achievement and exploration capabilities, in order to improve academic achievement, the importance of improving inquiry skills was found. Third, the qualitative analysis of teaching and learning strategy developed by applying the lessons of this teacher guide and small group activities through the explicit and reflective observation and classification of the student learning activities showed the significant improvement of ability of the scientific inquiry skills. In addition to the improvement in the abilities of the classification showed after the formation of the most basic observation skills of the scientific inquiry.

• Communications of Mathematical Education
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• v.28 no.3
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• pp.395-422
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• 2014

In this paper, we obtain the step inteaching high school leve-based class utilizing cooperative learning lessons using level-type tutoring to improve academic achievement and mathematics attitudes. The details are as follows. First, we develop the teaching and learning model for the level-type instructional development and for the application to project work. Second, we seek to height academic achievement by applying the level-type work sheets in conjunction with cooperative learning. For this problem, we will focus on the following issues. First, how will you using level-type tutoring level TAI cooperative learning in order to improve academic achievement and develop the learning ability in mathematics? Second, how can you step utilizing TAI instructional level of cooperative learning in mathematics classes to improve mathematics learning attitudes? Third, how will you some reaction step work sheets utilizing level TAI cooperative learning of students for mathematics. Results of this study are as follows. First, in the experimental group compared to the comparison group was improved academic achievement. Second, in the experimental group compared to the comparison group learning attitudes could help. Third, the level of cooperative learning instructional model utilizing the TAI in the experimental group compared to the comparison group represents a significant response was seen.

• Journal of The Korean Association For Science Education
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• v.35 no.3
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• pp.431-442
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• 2015

SSI instruction can be an effective tool to promote key competencies for future citizens. Our assumption of the study is that applying the concept of collective intelligence in the context of SSI learning would facilitate the learning. Thus, we designed and implemented Collective Intelligence-based SSI instruction over almost a year and observed the effects of the instruction on enhancing students' collaboration, information management, critical thinking, and communication skills. Twenty 9th grade students enrolled in a science-gifted program voluntarily participated. Data was collected by administering a questionnaire to examine the skills before, in the middle of, and after the instruction, and by conducting classroom observations and focus student group interviews. The results indicated some degree of improvement in their targeted skills. First, they experienced the expansion of their thoughts by actively sharing information and ideas using the web platform. Second, they became more flexible and open to different points of views in order to accomplish a common goal. Third, they appreciated having independent time and space to explore their own positions on the issues and to search necessary information, and believed that the process encouraged them to more pro-actively participate and communicate in the group debates. Lastly, they positively perceived the values that collaboration with diverse group members could produce.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1257-1269
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• 2010

The internet which is fast spread over all areas of our lives provides us with benefits of efficiency, productivity, and amusement; however, its features as an anonymous and non-face-to-face medium have raised a serious social issue of the collapse of internet ethics due to the abuse of it. Thereupon, the importance of internet ethics education has been highlighted to prevent side effects resulted from the internet and cultivate human-centered internet culture. In this paper, we suggests desirable methods for internet ethics education based on the investigation and analysis of the status of university freshmen's internet ethics. This research conducted a survey and analyzed its result after categorizing the status of internet ethics into the invasion of private information, invasion of intellectual property rights, harmful information, internet communication culture, cyber violence, internet addiction, and internet fraud. And based on the result of analyzing their internet ethics, this paper suggests desirable methods for internet ethics education. Next, internet ethics education was conducted by applying the proposed methods for internet ethics education, and its educational effect was evaluated. According to the result of verifying the educational effect measured statistically, it has proved that the suggested internet ethics education is effective to improve undergraduates' internet ethics.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.