• Journal of the Korean School Mathematics Society
• /
• v.11 no.3
• /
• pp.513-541
• /
• 2008

The purposes of the study were to investigate whether the use of the Geometer's Sketchpad(GSP) is more effective than the use of traditional tools such as ruler and protractor to enhance eighth- grade students' understanding of quadrilaterals and geometric reasoning ability and to examine how the use of the software affects on the development of students' understanding and reasoning ability. According to the results of the posttest, there was a significant difference in student achievement between students using GSP and students using ruler and protractor. Students using GSP significantly outperformed students using ruler and protractor on the posttest. Student interview data showed that the use of the GSP was more effective in developing students' geometric reasoning ability. Students using GSP achieved higher degrees of acquisition for van Hiele level 2 and 3 than students using ruler and protractor. Dynamic visual representations and hands-on experiences provided in GSP learning environment helped students approach quadrilateral concepts more conceptually and realize their pre-existing conceptual errors and re-conceptualize their mathematical ideas.

• Journal of Fisheries and Marine Sciences Education
• /
• v.25 no.1
• /
• pp.233-245
• /
• 2013

The purpose of this study is to analyse the effects on the academic achievement and learning motive in mathematics class by use of Cornell-note method at an elementary school. Thus, Cornell-mathematic note is designed for the experiment in order to recognize the effects how the Cornell-note influences students' mathematics academic achievement and learning motive. This experiment was carried out for 13 weeks and the target was 28 students. The group was consisted of 6rd grade students in elementary school located in Busan. To see the effects of Cornell-note method after experiment, post-test was carried out about mathematics academic achievement and learning motive. The results of this study are as follows: There was meaningful difference before and after test about mathematics academic achievement and learning motive. The academic achievement and learning motive in mathematics were improved after Cornell-note applied. Improvement of learning motive caused progress of academic achievement in mathematics class. The Cornell-note way is not appropriate, however, to reinforce mathematical communication ability and to attract students' interest. Therefore, systematic symbol is necessary and consider about adoption of story-telling way.

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.125-131
• /
• 2021

Detecting fraudulent insurance claims is difficult due to small and unbalanced data. Some research has been carried out to better cope with various types of fraudulent claims. Nowadays, technology for detecting fraudulent insurance claims has been increasingly utilized in insurance and technology fields, thanks to the use of artificial intelligence (AI) methods in addition to traditional statistical detection and rule-based methods. This study obtained meaningful results for a fraudulent insurance claim detection model based on machine learning (ML) and deep learning (DL) technologies, using fraudulent insurance claim data from previous research. In our search for a method to enhance the detection of fraudulent insurance claims, we investigated the reinforcement learning (RL) method. We examined how we could apply the RL method to the detection of fraudulent insurance claims. There are limited previous cases of applying the RL method. Thus, we first had to define the RL essential elements based on previous research on detecting anomalies. We applied the deep Q-network (DQN) and double deep Q-network (DDQN) in the learning fraudulent insurance claim detection model. By doing so, we confirmed that our model demonstrated better performance than previous machine learning models.

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.308-316
• /
• 2021

During the past two years, the education systems in the world witnessed unprecedented turmoil due to the coronavirus (Covid-19) pandemic, as most schools and universities in the world closed their doors to more than 1.5 billion students, or more than 90% of the total learners, according to recent figures issued by the UNESCO Institute for Statistics. Education experts have agreed that post- coronavirus education will not be the same as before, especially with the increasing use of modern technology in education. One of the most important new patterns with a structure digital in education is distance education, this style has been used, in many countries of the world, as an alternative to traditional education, since the beginning of the pandemic. In Saudi Arabia, this type of education has been used in all educational institutions, starting from kindergarten until the postgraduate level, as an alternative to face-to-face education to preserve the health and safety of students and workers in educational institutions. This study aimed to explore the level of satisfaction of preparatory year students on distance learning in their first year of study at Umm Al-Qura University. The findings of this study showed that students in the preparatory year were satisfied with their online learning experience. In addition, the results revealed that there was no effect for gender and location of study on students' level of satisfaction. Saudi universities should continue to work to create a suitable learning environment for students at the e-learning level.

• Journal of Platform Technology
• /
• v.6 no.4
• /
• pp.34-40
• /
• 2018

Currently, artificial neural networks perform well for a single task, but NN have the problem of forgetting previous learning by learning other kinds of tasks. This is called catastrophic forgetting. To use of artificial neural networks in general purpose this should be solved. There are many efforts to overcome catastrophic forgetting. However, even though there was a lot of effort, it did not completely overcome the catastrophic forgetting. In this paper, we propose sequential iterative learning using core concepts used in elastic weight consolidation (EWC). The experiment was performed to reproduce catastrophic forgetting phenomenon using EMNIST data set which extended MNIST, which is widely used for artificial neural network learning, and overcome it through sequential iterative learning.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.29-36
• /
• 2022

In deep learning classification tasks, most models frequently assume that all labels are available for the training datasets. As such strategies to learn new concepts from unlabeled datasets are scarce. In fingerprint classification tasks, most of the fingerprint datasets are labelled using the subject/individual and fingerprint datasets labelled with finger type classes are scarce. In this paper, authors have developed approaches of classifying fingerprint images using the majorly known fingerprint classes. Our study provides a flexible method to learn new classes of fingerprints. Our classifier model combines both the clustering technique and use of deep learning to cluster and hence label the fingerprint images into appropriate classes. The K means clustering strategy explores the label uncertainty and high-density regions from unlabeled data to be clustered. Using similarity index, five clusters are created. Deep learning is then used to train a model using a publicly known fingerprint dataset with known finger class types. A prediction technique is then employed to predict the classes of the clusters from the trained model. Our proposed model is better and has less computational costs in learning new classes and hence significantly saving on labelling costs of fingerprint images.

• Proceedings of the Korean Statistical Society Conference
• /
• 2004.11a
• /
• pp.307-312
• /
• 2004

In our fast-moving information and knowledge society, skills and know-how rapidly become outdated. Virtual learning environments play a key role in meeting today's growing demand for customized educational and vocational training and lift-long teaming. The scope of multimedia-based and web-supported education is illustrated by means of an interdisciplinary multimedia project 'New Statistics' funded by the German government. The project output contains more than 70 learning modules covering the complete curriculum of an introductory statistics course. All modules are based on a statistical laboratory and on a multitude of Java applets, animations and case studies. The paper focuses on presenting the statistical laboratory and the applets. These components present the main project pillars and are particularly suitable for international use, independently from the original project framework. This article also demonstrates the application of Java applets and other multimedia developments from the educational world to official statistics for interactive presentation of statistical information.

• Journal of the Korean Institute of Educational Facilities
• /
• v.5 no.3
• /
• pp.11-16
• /
• 1998

The size and location of spaces need to be changed for teaching & learning activities in open education. This study is aimed to investigate how school facilities should be rearranged when the open education is implemented in elementary school. Some considerations such as enlargement of classroom, establishment of open space, and provision of various self-learning spaces are proposed for the rearrangement. It is also recommended that (1) a space for research and conference for teachers, (2) a multi-learning space to be utilized by connecting general and special classrooms, and (3) an open space for exclusive use of one grade or two grades be established.

• International journal of advanced smart convergence
• /
• v.8 no.2
• /
• pp.147-154
• /
• 2019

In this paper, we conducted a study that utilizes deep learning to calculate appropriate physical exercise information when basic human factors such as sex, age, height, and weight of users come in. To apply deep learning, a method was applied to calculate the amount of fat needed to calculate the amount of one repetition maximum by utilizing the structure of the basic Deep Neural Network. By applying Accuracy improvement methods such as Relu, Weight initialization, and Dropout to existing deep learning structures, we have improved Accuracy to derive a lean body weight that is closer to actual results. In addition, the results were derived by applying a formula for calculating the one repetition maximum load on upper and lower body movements for use in actual physical exercise. If studies continue, such as the way they are applied in this paper, they will be able to suggest effective physical exercise options for different conditions as well as conditions for users.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.315-321
• /
• 2022

Many students with disabilities and special needs are enrolled in higher education, which substantiated the need for research regarding faculty members' knowledge and willingness to implement supportive strategies in higher education in Saudi Arabia. This study explored Saudi university faculty members' knowledge and willingness to apply UDL (Universal Design for Learning) principles in their teaching practice. Surveys were used for data collection for this descriptive research. The findings indicated faculty members felt that they were knowledgeable regarding UDL and were willing to use UDL principles in teaching their students. Furthermore, there were no statistically significant differences between faculty members' knowledge levels regarding UDL based on their current position and years of experience. The findings indicated there was a significant relationship between gender and knowledge, with males having a significantly higher mean knowledge, although further analyses revealed it was a small effect. Finally, the results suggest more years of experience are related to greater willingness to use UDL principles, and this is particularly true for those in a lecturing position. These findings could be helpful, particularly for the Ministry of Education in Saudi Arabia to shed light on faculty members' UDL knowledge. Further research is needed to substantiate the findings.