• Journal of Fisheries and Marine Sciences Education
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• v.28 no.5
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• pp.1478-1491
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• 2016

This study has designed to find out the effects of a project-based flipped learning model at universities on the self-directed learning ability, the self-leadership, and the learning competency. For the study, two procedures were performed. First, a flipped learning model for a project-based learning was developed on the basis of the literature reviews. The flipped learning model has three different steps: the pre-class, the in-class, and the post-class. In the pre-class, instructors provide mini-core courses using various technologies for learners outside the class. The in-class is the step to check whether learners prepare their learning or not. Also, in this step, the in-death learning and the teaching-learning process by interaction between instructors and learners would be performed. In the post-class, learners would be able to sustain the extended learning to develop the learning tasks and activities after flipped learning class. Through this step, the learners could be experienced integrated thinking and application, documentation and management, as well as sharing and spread of their learning. Second, the effectiveness of the developed flipped learning model on the self-direction, the self-leadership, and the learning competency was examined. The quantitative research method and the qualitative research method were used for this study. The results indicated that the flipped learning model showed improvement on the self-direction, the self-leadership, and the learning competency.

• Journal of the Korea Society of Computer and Information
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• v.23 no.6
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• pp.15-21
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• 2018

The purpose of this study is to design a Content-based Korean Class model using Flipped learning for foreign students. The class model that presents on this paper will lead the language learning through content learning, also it will be enable the student more active and to have an initiative in the class. Prior to designing a Content-based Korean Class model using Flipped learning, the concepts and educational significance and characteristics of flip learning were reviewed through previous studies. Then, It emphasizes the necessity of teaching method adapting Flipped learning to Content-based teaching method in Korean language education. It also suggests standards and principles of composition in Contents-based teaching method using Flipped learning. After designing the instructional model based on the suggested standards and principles, it presents a course of instruction about how learning methods, contents and activities should be done step by step. The Content-based Korean class model using the Flipped learning will be an alternative approach to overcome the limitations of teacher-centered teaching methods and lecture-teaching methods which are the dominant of present classroom environment.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.104-110
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• 2020

In the 4th Industrial Revolution, the competitiveness of the software industry is important, and as a solution to fundamentally secure the competitiveness of the software industry, education classes should be provided to educate high quality software personnel in educational institutions. Despite this social situation, software-related classes in universities are largely composed of competitive or individual learning structures. Cooperative learning is a learning model that can complement the problems of competitive and individual learning. Cooperative learning is more effective in improving academic achievement than individual or competitive learning. In addition, most learners have the advantage of having a more desirable self-image by having a successful experience. In this paper, we apply a pair check model, which is a type of cooperative learning, in operating system classes. In addition, the class procedure and instruction plan are designed to apply the pair check model. We analyze the test results to analyze the performance of the cooperative learning model.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.411-418
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• 2016

Learning analytic has been utilized to helps us to successfully complete the course by using the interaction of the teacher and the learner data generated from the teaching and learning support system. In other words, Learning analytic is a method in order to understand the activities of learners. In the learning analytic, the data model is needed in order to utilize the more useful for teaching and learning activities data. Therefore, in this study, we propose a user centric data model of learning styles and learning objects. This model is expressed by aggregating of user learning style, learning objects, and learning activities. The proposed model is significant that laid the foundation for analyzing the activities of the learners in course units.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.221-228
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• 2006

With the increasing use of the Internet improved Internet technologies as well as web-based applications, the effectiveness assessment of e-Learning has become one of the most practically and theoretically important issues in both Educational Engineering and Information Systems. This study suggests a research model, based on an e-Learning success model, the relationship of the e-learner's self-regulated learning strategy and the quality perception of the e-Learning environment. This research model focuses on the learning environment and on e-learning strategy. The former consists of learning management system, learning content quality and service quality that are provided by e-Loaming. The latter refers to the learners' self-regulated learning strategy. We will show the validity of the model empirically.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.159-168
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• 2021

Detecting cyber-attacks using machine learning or deep learning is being studied and applied widely in network intrusion detection systems. We noticed that the application of deep learning algorithms yielded many good results. However, because each deep learning model has different architecture and characteristics with certain advantages and disadvantages, so those deep learning models are only suitable for specific datasets or features. In this paper, in order to optimize the process of detecting cyber-attacks, we propose the idea of building a new deep learning network model based on the association and combination of individual deep learning models. In particular, based on the architecture of 2 deep learning models: Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM), we combine them into a combined deep learning network for detecting cyber-attacks based on network traffic. The experimental results in Section IV.D have demonstrated that our proposal using the CNN-LSTM deep learning model for detecting cyber-attacks based on network traffic is completely correct because the results of this model are much better than some individual deep learning models on all measures.

• Korean System Dynamics Review
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• v.9 no.1
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• pp.57-71
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• 2008

This research paper describes a complex and vague settings in which organization makes a decision and explains a role of decision maker's learning process. The original paper, written by Cohen, March, Olsen in 1972, said that all members of organization depended on the technology taken through trials and errors, which is the 'learning' process literally. But they intended to exclude the learning process in their simulation model because their PORTRAN model couldn't replicate the learning concept. As a result, they couldn't explain how all agents of garbage can simulation model resolve the problem dynamically. To overcome this original paper's limitations, we try to rebuild a learning process simulation model using by system dynamics approach that can capture the linkage between organization leanings and agents-based decision-makings. Our learning simulation results reveal two points. First, decision maker's leanings process improves the efficiency of decision making in complex situation. Second, group learning shows a superior efficiency to an individual learning because group members share organizational memory and energy.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.278-283
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• 2010

In this paper, we designed and proposed framework of extended user model to support student tailored learning in ubiquitous environment. For the purpose, existents model that is domain model, user model, adaptation model and interaction model connected to LMS(Learning Management System) and LCMS(Learning Contents Management System). Students information management process that is extended user model is in between LMS and adaptive learning system. And the process connected u-LMS to use u-learning. u-LMS and u-LCMS could support the learning contents through exchange the contents according to connect and request from the students.

• Journal of Korean Ophthalmic Optics Society
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• v.12 no.1
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• pp.75-84
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• 2007

In this study, I developed a teaching-learning model using project learning model which makes the most of PIM(Peer & Instructor Mentoring), Presentation contest, and unification of courses on the field ophthalmic optics. There were several conclusion as followings;. The teaching-learning model considering the unification and organic connections among subjects was efficient to the students' academic achievement. Peer & instructor mentoring system was helpful for students to accomplish their own learning projects. Project learning model with collaboration was useful for the development of students' self-controled learning ability and communicative ability. Project learning model gave its driving force to the better motivation and to the goal achievement. Project learning model was instructive for building up the related theories and concepts on the students' major. In conclusion, project learning model mixed subjects with festival, can be a alternative teaching-learning model.

• 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.