• Journal of Information Technology Applications and Management
• /
• v.14 no.2
• /
• pp.27-47
• /
• 2007

In an effort to apply IT to practices of learning, universities are trying to implement e-Learning systems and expanding the extent of their usage. Nowadays, e-Learning systems are not only used for conducting web-based distance learning, but also used for supporting traditional classes education by encouraging communication and information sharing between instructors and learners or among the learners. There is relatively lack of studies on the exploitation of e-Learning systems in the traditional classes, in comparison with a distance education. Specifically, howe-Learning systems could support the traditional class and/or which benefits e-Learning systems could offer in the classes are among the important issues. In this study, we suggest that e-Learning systems would be the rich media to communicate and exchange information among people who participate in a class. We derive key variables like media richness and media experience from Media Richness Theory and from Channel Expansion Theory. Moreover, Media usefulness and Satisfaction of a learner with e-Learning system is drawn from the literature on IS success. We examine the effects of perceived media richness, media usefulness, and media experience on leaner's satisfaction with e-Learning systems. In addition, we also investigate learner's media usefulness perception which is positively related to media richness and media experience. Finally, learner's experience with e-Learning systems affects perceived media richness. Based on the results of an empirical test. we first suggest that perceived media richness with e-Learning systems contributes to increase media usefulness and satisfaction of a learner. Second, media experience is an important predictor of media richness and media usefulness perception. Consequently, the result can support Channel Expansion Theory. Finally, media usefulness perception affects learner's satisfaction with e-Learning systems.

• Database Research
• /
• v.34 no.3
• /
• pp.159-169
• /
• 2018

Discretization of continuous variables intended to improve the performance of various algorithms such as data mining by transforming quantitative variables into qualitative variables. If we use appropriate discretization techniques for data, we can expect not only better performance of classification algorithms, but also accurate and concise interpretation of results and speed improvements. Various discretization techniques have been studied up to now, and however there is still demand of research on discretization studies. In this paper, we propose a new discretization technique to set the cut-point using Wasserstein distance with considering the distribution of continuous variable values with classes of data. We show the superiority of the proposed method through the performance comparison between the proposed method and the existing proven methods.

• Journal of the Korean Society of Earth Science Education
• /
• v.15 no.1
• /
• pp.47-61
• /
• 2022

In this study, We developed VR (Virtual Reality) geological resources based on the Geo Big Data of the Big Data platform that provided by the Korea Institute of Geoscience and Mineral Material (KIGAM). So students selected the theme of lessons by using these resources and we operated Remote classes using the materials that developed as to Virtual Reality. Therefore, the geological theme maps provided by the Geo Big Data Open Platform were reconstructed and produced materials were created for Study about Real Korean geological outcrops grounded in Virtual Reality. And Topographic information data was used to produce class materials for Remote classes. Twenty students were selected by Random sampling, and data were collected by conducting a survey including interviews to confirm the change in students' perception of remote classes in virtual reality geological data development and the effect of the classes, so data were analyzed through inductive categorization. The results of this study are as follows. First, students showed positive responses in terms of interest, utilization, and knowledge utilization as taking remote classes for developing geological data in virtual reality geological data. This is the result of showing the adaptability of diverse and flexible learning getting away from a fixed framework by motivating and encouraging students and inducing cooperation for communication. Second, students recognized distance education in the development of Virtual Reality geological data as 'Realistic hands-on learning process', 'Immersive learning process by motivation', and 'Learning process of acquiring knowledge in the field of earth science'.

• Journal of The Korean Association of Information Education
• /
• v.26 no.3
• /
• pp.219-227
• /
• 2022

Students are always preparing for remote classes while taking face-to-face classes due to COVID-19. However, it is true that the class satisfaction with distance learning is not high for students and teachers. The idea that even if remote classes are conducted at home, it would be nice to have classes together like real ones, the need for a virtual world education program that utilizes augmented reality and virtual reality based on the metaverse has emerged. However, there are very few studies that teachers try to apply them to their classes. In this study, a metaverse application curriculum was presented for elementary science and 'space' domains. To implement the metaverse, ZEPETO and COSPACIS EDU were used. In the analysis of content creation with students and evaluation with schoolmates, this study showed that the concentration of learning was increased and creativity improved in the 'real', 'individual', and 'society' domains.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.1
• /
• pp.118-124
• /
• 2004

This paper proposes an approach to deriving a fuzzy classifier based on evolutionary supervised clustering, which identifies the optimal clusters necessary to classify classes. The clusters are formed by multi-dimensional weighted Euclidean distance, which allows clusters of varying shapes and sizes. A cluster induces a Gaussian fuzzy antecedent set with unique variance in each dimension, which reflects the tightness of the cluster. The fuzzy classifier is com-posed of as many classification rules as classes. The clusters identified for each class constitute fuzzy sets, which are joined by an "and" connective in the antecedent part of the corresponding rule. The approach is evaluated using six data sets. The comparative results with different classifiers are given.are given.

• Journal of Korean Institute of Industrial Engineers
• /
• v.39 no.2
• /
• pp.82-89
• /
• 2013

Novelty detection (ND) is an effective technique that can be used to determine whether a future observation is normal or not. In the present study we propose a novelty detection algorithm that can handle a situation where the distributions of target (normal) observations are inhomogeneous. A simulation study and a real case with the TFT-LCD process demonstrated the effectiveness and usefulness of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.4
• /
• pp.460-465
• /
• 2006

This paper presents a new fuzzy learning rule which considers the Euclidean distances between the input vector and the prototypes of classes. The new fuzzy learning rule is integrated into the supervised IAFC neural network 4. This neural network is stable and plastic. We used iris data to compare the performance of the supervised IAFC neural network 4 with the performances of back propagation neural network and LVQ algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.3 no.2
• /
• pp.134-146
• /
• 2009

Traffic classification seeks to assign packet flows to an appropriate quality of service(QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.

• International Journal of Computer Science & Network Security
• /
• v.24 no.3
• /
• pp.160-172
• /
• 2024

The characteristic aspects of learning a foreign language require special resources and tools for online learning. Criteria for choosing educational platforms depend on key elements of an academic subject area. Microsoft Teams (hereafter, MT) educational platform is competitive one because it meets most of the needs that arise during the formation of a secondary linguistic persona. Due to the large number of corporate programs, there are a successful acquisition of language skills and the implementation of all types of oral activities of students. A significant MT advantage is the constant analysis and monitoring of the platform of participants' needs in the educational process by developers. The article highlights MT advantages and disadvantages. The attention is drawn to individual programs, which, in the authors' opinion, are the most successful to learn writing, reading, speaking, listening, as well as organize classes that meet needs of modern foreign students.

• Journal of the Korean School Mathematics Society
• /
• v.3 no.1
• /
• pp.189-200
• /
• 2000

The purpose of this thesis is that the students understand the sentence stated math problems closely related to the real life and adapted the right solving strategies try to find the solution to a problem. The following research problem were proposed. 1. How repeated thinking lessons develop the understanding of problems and influence the usage of correct problem solving strategies and extensions of problem solving. 2. There are how much differences of achievement for each type of sentence stated problems by using comparative analysis of upper class, intermediate class, and lower class for each level between the experimental and comparative classes. In order to conduct this research the classes were divided into three different level - upper class, intermediate class and lower class. Each level include an experimental class and a comparative class. The two classes (experimental class and comparative class) of the same level were tested on the basis of class division record with the experimental class repeated learning papers for two weeks were used to guide the fixed thinking algorism for each sentence stated math problems. Eight common problems were chosen from a variety of textbooks : number calculation problems, velocity-distance-time problems, the density of a mixture, benefit problems, distribution problems, problems about working, ratio problems, the length of a figure problems. After conducting this research experiment The differences in achievement level between the experimental class and comparative class, were compared and analyzed through achievement tests made from the achievement test papers with seven problems, which were worth seventy points (total score). The conclusions of this thesis are as follows: Firstly, leaning activities through the usage of repeated learning papers for each level class produce an even development of achievement level especially in the case of the upper class learners, they have particular differences (between experimental class and comparative class) compared to the intermediate level and lower classes. Secondly, according to the analysis about achievement development each problems, learners easily accept the strategies of solution through the formula setting up to the problem of velocity -distance-time, and to the density of the mixture they adapted the picture drawing strategies interestingly, However each situation requires a variety of appropriate solution strategies. Teachers will have to employ other interesting solution strategies which relate to real life.