• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.312-322
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• 2010

The aim of this study is to find the effect of action learning on the problem solving process of nursing students during the clinical practice of nursing management. A total of 99 senior nursing students participated in this study. Data was collected from May 2006 to October 2007 and statistical analysis for paired t-test was performed on the data using SPSS/WIN 14.0. The results of the data show that there was a significant increase in the problem solving process for nursing students after the implementation of action learning(t=-4.718, p=.000). In the problem solving process, there was a significant increase in definition of problem(t=-4.123, p=.004), design of problem solution(t=-2.973, p=.002), execution of problem solution(t=-3.264, p=.000) and investigation of problem solving(t=-3.677, p=.000). The only exception in the problem solving process was detection of problem(t=-1.858, p=.066). Therefore, action learning provides nursing students a new alternative for improving the problem solving process and clinical adaptability after graduating from nursing school.

• The Journal of Korean Academic Society of Nursing Education
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• v.7 no.2
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• pp.349-359
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• 2001

The purpose of this study was to find the experiences to be cared of nursing students in the teaching-learning process of nursing education and provided the fundamental data of nursing education. For this study, the analytical theory of Benner's Interpretive Phenomenology was applied and the research question was 'How do the nursing students to be cared in the teaching-learning process of nursing education?' All 64 junior and senior nursing students who volunteered for this study were interviewed. The data was collected by open-ended audiotaped interview or written descriptions of situations they had experienced with a caring faculty member. All the contents of interview were recorded while interviewing with the each participants from the April 1998 to September 2000. The conclusions, obtained from the study on experiences to be cared of nursing students, were as follows ; 1. The nursing students considered the relationship with professor as very important matter. 2. The significant and important themes to nursing student be cared in the teaching-learning process of nursing education were Concern, Support, Information and Acceptance. 3. The result of this study explained the content and stage of nursing education applying 4 themes, therefore its practical use as material of nursing education was considered. Based on this study, the practical use of this results as nursing education data and the experimental study for measuring the effect of caring in the teaching-learning process of nursing education were suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• The Journal of Korean Association of Computer Education
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• v.6 no.3
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• pp.75-85
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• 2003

This study develops the System(MetaGene) to create meta-data for learning object based on SCORM including meta-data of Assets. SCO, Contents Aggregation and metadata of Contents Package. API function cocle is embeded in Learning Object for interfacing API adopter in LMS to support SCORM and for tracking on learning process based on data models. Also, the learning objects are packaged the PIF(Packaged Interchange File) to transmit with LMS. MetaGene is verified by $SCORM^{(TM)}$ Conformance TestSuite for meta-data of learning objects, manifest file of Contents Packaging.

• Educational Technology International
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• v.9 no.2
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• pp.123-142
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• 2008

The purpose of this study was to examine how computer conferencing might facilitate collaborative learning for students to engage in meaningful discussion. The participants in this study consisted of the instructor and the students in a graduate level course. Different sources of evidence were used to triangulate the data: in-depth interviews, content analysis of transcripts of discussion, and other archival data including course syllabus, presentation materials, and lecture notes. Participants perceived web-based learning as collaborative process, providing opportunities to share the idea, respect and evaluate different perspectives, and co-construct new insights. Analysis of the data revealed several challenges related collaboration in a web-based learning environment: absence of a sense of community, technical problems, adaptability to different types of learner, and managing the discussion. The data also indicated that a variety of strategies were used to facilitate learning: building a sense of community, technical support, developing instructional methodologies, class size, and design of the content.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1251-1258
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• 2019

Intelligent tutoring system enables users to effectively learn by utilizing various artificial intelligence techniques. For instance, it can recommend a proper curriculum or learning method to individual users based on their learning history. To do this effectively, user's characteristics need to be analyzed and classified based on various aspects such as interest, learning ability, and personality. Even though data labeled by the characteristics are required for more accurate classification, it is not easy to acquire enough amount of labeled data due to the labeling cost. On the other hand, unlabeled data should not need labeling process to make a large number of unlabeled data be collected and utilized. In this paper, we propose a semi-supervised learning method based on feedback variational auto-encoder(FVAE), which uses both labeled data and unlabeled data. FVAE is a variation of variational auto-encoder(VAE), where a multi-layer perceptron is added for giving feedback. Using unlabeled data, we train FVAE and fetch the encoder of FVAE. And then, we extract features from labeled data by using the encoder and train classifiers with the extracted features. In the experiments, we proved that FVAE-based semi-supervised learning was superior to VAE-based method in terms with accuracy and F1 score.

• Journal of The Korean Association of Information Education
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• v.18 no.1
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• pp.25-33
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• 2014

Due to the recent development of educational robot hardwares, processing speed and scalability have been greatly improved. Thus, the robot hardwares that are compatible with temperature sensor for MBL and gyro sensor made a data logging possible. Students can conduct an experiment on scientific research and prediction, collecting and data analysis with robots that can process data logging. Therefore this research constructed and adopted science project class that introduced a Smart r-Learning that utilizes Class SNS and smartphone. As a result of applying a data logging smart r-Learning to elementary school 5th graders, it has shown that the students' logical thinking ability four of the six areas have been improved in t-test.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.500-501
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• 2019

In the $4^{th}$ generation industry, self-directed learning is very important than Injection learning. Therefore many educational institutions has developed method of self-directed learning. In order for self-directed learning to be effective, it is more important for faculty to manage the overall process of learning rather than being directly involved in the student's academic work. Therefore, learning counseling is an important way to effectively carry out self-directed learning. In this paper, we analyze the status of open data for natural language processing that can implement the learning consultation contents so that various applications can be done through natural language processing.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.450-454
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• 2018

Because of the rapidly changing environment and high uncertainties, the semiconductor industry is in need of appropriate forecasting technology. In particular, both the cost and time in the test process are increasing because the process becomes complicated and there are more factors to consider. In this paper, we propose a prediction model that predicts a final "good" or "bad" on the basis of preconditioning test data generated in the semiconductor test process. The proposed prediction model solves the classification and regression problems that are often dealt with in the semiconductor process and constructs a reliable prediction model. We also implemented a prediction model through various machine learning algorithms. We compared the performance of the prediction models constructed through each algorithm. Actual data of the semiconductor test process was used for accurate prediction model construction and effective test verification.

• Journal of the Korean Chemical Society
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• v.54 no.5
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• pp.643-649
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• 2010

In this study, the relationships among high school students' epistemological views on theory and data, science process skills, the perceptions of the preferred laboratory learning environment and attitudes toward laboratory work were investigated. The results indicated that science process skills, all subcategories of the perceptions of the preferred laboratory learning environment (student cohesiveness, open-endedness, integration, rule clarity, and material environment) and attitudes toward laboratory work were significantly correlated with epistemological views on theory and data. The results of multiple regression analysis revealed that science process skills, open-endedness and material environment and attitudes toward laboratory work significantly predicted epistemological views on theory and data.