• Journal of Digital Contents Society
• /
• v.16 no.5
• /
• pp.707-715
• /
• 2015

With the development of computer technology, the multimedia mediums that allow for animated videos, conversational illustrations are increasingly receiving attention for materials for educational purposes. Accordingly, there is a need to research whether multimedia resources and material is more effective compared to traditional educational material and resources. This study aims to compare traditional English reading and writing learning methods with learning methods using educational multimedia mediums such as illustrations or animation. Students were divided into a experimental group and a control group, and during 6 months the groups were exposed to different educational resources and on the basis of student evaluation feedback and grades, a new approach to English education is offered.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.5
• /
• pp.2099-2106
• /
• 2018

This study presents a novel approach of discriminative feature vectors based on manifold learning using nonlinear dimension reduction (DR) technique to improve loss function, and combine with the Adversarial examples to regularize the object function for image classification. The traditional convolutional neural networks (CNN) with many new regularization approach has been successfully used for image classification tasks, and it achieved good results, hence it costs a lot of Calculated spacing and timing. Significantly, distrinct from traditional CNN, we discriminate the feature vectors for objects without empirically-tuned parameter, these Discriminative features intend to remain the lower-dimensional relationship corresponding high-dimension manifold after projecting the image feature vectors from high-dimension to lower-dimension, and we optimize the constrains of the preserving local features based on manifold, which narrow the mapped feature information from the same class and push different class away. Using Adversarial examples, improved loss function with additional regularization term intends to boost the Robustness and generalization of neural network. experimental results indicate that the approach based on discriminative feature of manifold learning is not only valid, but also more efficient in image classification tasks. Furthermore, the proposed approach achieves competitive classification performances for three benchmark datasets : MNIST, CIFAR-10, SVHN.

• Journal of the Korean Institute of Educational Facilities
• /
• v.26 no.3
• /
• pp.33-41
• /
• 2019

As the information age matures, the learning style of youth is changing rapidly. Students study at a variety of places such as cafe or lobbies utilizing various digital learning devices. Along with the place changes, learning methods are also changing. Student-centered learning methods such as smart learning, collaborative learning, and activity-based learning are increasingly being utilized instead of the traditional instructor-centered learning in which knowledge is unilaterally delivered. Accordingly, many universities are remodeling central libraries, and they are also transforming lobby spaces of the college buildings into simple but useful learning spaces. In this study, we analyze the characteristics of learning spaces in universities from the standpoint of the students. According to the analysis, overall satisfaction is high in terms of comfortable physical learning environments such as Wi-Fi, furniture, lighting, etc. But the spaces are still optimized for individual and intensive learning. There seems to be a lack of effort to support collaborative learning or activity-based learning. This observation is confirmed by the characteristics of the central library, and it is considered that the reason why the college buildings are preferred by students is that college buildings are more suitable for collaborative or activity-based learning than libraries.

• Journal of the Korean Society of School Health
• /
• v.35 no.3
• /
• pp.113-122
• /
• 2022

Purpose: The purpose of this study was to identify the effects of applying jigsaw cooperative learning to basic nursing practicums on self-directed learning ability, self-efficacy, and learning outcomes. Methods: This study was based on a non-equivalent control group design, and the subjects were nursing students. The study allocated 30 people in the experimental group and 30 people in the control group, and jigsaw cooperative learning was applied to the experimental group for 2 hours every week for a total of 8 weeks. The traditional educational method was applied to the control group. The collected data were analyzed using SPSS v26.0. Results: The experimental group to which jigsaw cooperative learning was applied showed statistically significant differences in self-directed learning ability (F=4.49, p=.038), self-efficacy (F=6.15, p=.016), and learning outcomes (F=19.48, p<.001) compared to the control group. Conclusion: By applying jigsaw cooperative learning to basic nursing practicums, this study confirmed its effect not only on the effective domain such as self-directed learning ability and self-efficacy, but also on learning outcomes in the practical domain. We propose future studies apply jigsaw cooperative learning to various practice classes to achieve learning outcomes that focus on cultivating students' practical capabilities.

• 대한공업교육학회지
• /
• v.32 no.1
• /
• pp.1-32
• /
• 2007

The purpose of this study was to verify that the practical skill instruction of the heat treatment and the tensile strength test using the problem-based learning is more effective than the traditional skill instruction in improving the key competencies. For the study, various literature researches were reviewed intensively about problem solving process, problem -based learning, and learning principals. The process of the practical skill instruction using the problem-based learning was composed with planning, executing, testing and evaluating. Based upon the conclusion of this study, the practical skill instruction using the problem-based learning was more effective than the traditional practical skill instruction of the heat treatment and the tensile strength test in improving the key competencies.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38B no.12
• /
• pp.954-961
• /
• 2013

In this paper, we propose a new learning method using a variable learning to improve pattern recognition in the FCSR(Fast Commit Slow Recode) learning method of the Fuzzy ART. Traditional learning methods have used a fixed learning rate in updating weight vector(representative pattern). In the traditional method, the weight vector will be updated with a fixed learning rate regardless of the degree of similarity of the input pattern and the representative pattern in the category. In this case, the updated weight vector is greatly influenced from the input pattern where it is on the boundary of the category. Thus, in noisy environments, this method has a problem in increasing unnecessary categories and reducing pattern recognition capacity. In the proposed method, the lower similarity between the representative pattern and input pattern is, the lower input pattern contributes for updating weight vector. As a result, this results in suppressing the unnecessary category proliferation and improving pattern recognition capacity of the Fuzzy ART in noisy environments.

• The Journal of the Korea Contents Association
• /
• v.5 no.2
• /
• pp.53-60
• /
• 2005

e-learning which is beyond time and space restrictions as a new education tool, has been practically used in many fields in order to support instrument or displacement for traditional education. This research shows that the survey on the significance and the effect of e-learning to teachers who have experience in e-learning through the internet compared with effect of tradition education. Furthermore, we investigate variable factors affecting on effect of e-learning, the correlation of factors and coefficient of correlation between factors associated with effects of e-learning based on the results of our survey.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1994.04a
• /
• pp.611-616
• /
• 1994

Developing the safety training program has been a major research topic in CBT as well as in traditional teaching and learning. With regard to determining learning control in CBT, it is important to consider not only the characteristics of learning tasks but also student's individual difference. In this regard, the purposes of this study are to develop the CBT program as well as animation program in order to increase the student's performance.

• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.6
• /
• pp.366-371
• /
• 2014

This paper reports a machine learning approach for image object detection. Object detection and localization in a wild image, such as a STL-10 image dataset, is very difficult to implement using the traditional computer vision method. A convolutional neural network is a good approach for such wild image object detection. This paper presents an object detection application using a convolutional neural network with pretrained feature vector. This is a very simple and well organized hierarchical object abstraction model.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.5
• /
• pp.187-197
• /
• 2020

Recently, various methods of text embedding using deep learning algorithms have been proposed. Especially, the way of using pre-trained language model which uses tremendous amount of text data in training is mainly applied for embedding new text data. However, traditional pre-trained language model has some limitations that it is hard to understand unique context of new text data when the text has too many tokens. In this paper, we propose self-supervised learning-based fine tuning method for pre-trained language model to infer vectors of long-text. Also, we applied our method to news articles and classified them into categories and compared classification accuracy with traditional models. As a result, it was confirmed that the vector generated by the proposed model more accurately expresses the inherent characteristics of the document than the vectors generated by the traditional models.