• Journal of Digital Contents Society
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• v.12 no.1
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• pp.123-131
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• 2011

The purpose of this study is to discover if the use of computer technologies in computer-assisted language learning, in the aspect of vocabulary learning, is both effective and useful. The technique of using multimedia lessons, using the computer, offers a variety of language learning tasks in relation to the four basic language learning skills. Korean students have been accustomed to a cramming style of education, and they utilize rote memorization for learning vocabulary. This study consisted of surveys and experiments, using specific multimedia language learning courseware exercises on three different age groups. The study explores the issues and problems that followed, and how teachers could effectively apply or enhance their vocabulary teaching through computer-assisted multimedia which is suited for a variety of levels versus the classroom off-line vocabulary learning application which is suited to one level.

• Journal of Platform Technology
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• v.10 no.3
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• pp.51-59
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• 2022

Machine learning, which has recently innovatively developed, has become an important technology that can solve various optimization problems. In this paper, we introduce the latest research papers that solve the problem of channel sharing in heterogeneous networks using machine learning, analyze the characteristics of mainstream approaches, and present a guide to future research directions. Existing studies have generally adopted Q-learning since it supports fast learning both on online and offline environment. On the contrary, conventional studies have either not considered various coexistence scenarios or lacked consideration for the location of machine learning controllers that can have a significant impact on network performance. One of the powerful ways to overcome these disadvantages is to selectively use a machine learning algorithm according to changes in network environment based on the logical network architecture for machine learning proposed by ITU.

• Journal of Digital Contents Society
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• v.8 no.2
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• pp.121-127
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• 2007

For human beings, language is the most important means of communication. Bloom and Lahey see successful language development as an interaction between form, content, and use. Language knowledge is a social phenomenon produced in a socio-cultural environment through interaction. Teachers have traditionally concentrated on the structure of their student's writing rather than on the message. If writing is to be seen as an interactive social process between humans, it is the content which is responded to. Language acquisition could be a major problem for hearing-impaired children and their acquisition of written language is characteristically problematic. This study is to search the use of microcomputers in written conversational methods, which enable the hearing-impaired student to hear their conversations in a visual form and which usefully extend their written language learning opportunities.

• International Journal of Contents
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• v.17 no.2
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• pp.9-19
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• 2021

The purpose of this survey-based study was to investigate high school students' perceptions of mathematics teachers' implementation of Universal Design for Learning (UDL)-based practices and technology in their mathematics classes in 2017. A total of 303 high school students in South Korea participated in this online survey on teachers' use of technology for instructional practices, the frequency of technology tool use, and the meeting of UDL guidelines in mathematics instruction. According to frequency analysis, high school students generally perceived their teachers' mathematics teaching as somewhat positive in providing multiple means of representation, action and expression, and engagement. However, mathematics teachers' implementation of technology tools in their mathematics classes was generally limited. This study indicated significant and positive relationships between variables regarding the use of technology tools and teachers' efforts to follow the UDL guidelines. Applying the Chi-squared test, we further examined how each survey result differed according to high school students' academic achievements and grade levels.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.159-167
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• 2019

Recently, a learning management system incorporating ICT technology into learning has helped students improve self-directed learning skills. Self-directed learning using LMS promotes and stimulates learners' participation in learning, focusing on the advantages of efficient use of learning resources and the spread of communication. In this study, we study the impact of self-directed learning using the learning management system on elementary school students' motivation and academic performance. We expect learners will be able to achieve effective academic achievement by learning problems that fit their level through the algorithms of the proposed learning management system. For this study, a total of 16 classes were conducted for eight weeks using the proposed learning management system for 21 elementary school students. Research has shown significant improvement in the learning orientation and interest areas of the learners who participated in the experiment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.2 s.302
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• pp.21-30
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• 2005

Development of both multimedia technology and communication network technology has accomplished many changes through the field of learning system. For the construction of a more efficient and clever learning system there is a research being done by the use of the Web and the telephone network. But until now, the case of current implemented teaming system is single system and so it has each merits and demerits. That is to say, when we use the learning system through the Web, the demerit is only possible by the static states using computer. For those who do not use the computer, the demerit is that the user must learn the use of the new system. Also, the case of using telephone network has merits that one can use the system anyplace, anytime by the telephone. But it has the problem of not being able to transmit information very efficiently. From these, this paper proposes the learning system that can be used efficiently and conveniently anyplace, anytime by connecting both telephone network and web. Also, we propose a new algorithm of user ID, password and name registration function using teaming system using VoiceXML and individual learning progress save function using VoiceXML and web.

• The Mathematical Education
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• v.63 no.2
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• pp.335-350
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• 2024

This study explored the factors that influence elementary school teachers' intention to use an artificial intelligence (AI) math learning system and analyzed the interactions and relationships among these factors. Based on the technology acceptance model, perceived usefulness for math learning, perceived ease of use of AI, and attitude toward using AI were analyzed as the main variables. Data collected from a survey of 215 elementary school teachers was used to analyze the relationships between the variables using structural equation modeling. The results of the study showed that perceived usefulness for math learning and perceived ease of use of AI significantly influenced teachers' positive attitudes toward AI math learning systems, and positive attitudes significantly influenced their intention to use AI. These results suggest that it is important to positively change teachers' perceptions of the effectiveness of using AI technology in mathematics instruction and their attitudes toward AI technology in order to effectively adopt and utilize AI-based mathematics education tools in the future.

• The Journal of Korean Association of Computer Education
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• v.21 no.5
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• pp.37-48
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• 2018

The 2015 revised national curriculum includes SW courses to improve computational thinking, and a variety of physical computing tools for learning are on sale for use in education. The purpose of this study is to provide a basis for selecting physical computing tool for learning suitable for learning situations and learning purposes, and to provide a reasonable basis for judging the choice of tools in the field. Delphi survey method was used as a reference method for developing evaluation criteria through 25 expert panels. As a result, the criterion of evaluation of the learning tool composed of 40 essential and 11 selection criteria for 7 domains was presented. In addition, the evaluation results of five kinds of learning tools commercialized through the evaluation criteria of the learning tool were analyzed. The evaluation criteria for the learning tools developed through this study are expected to help teachers select rational learning tools and help learning tool developers develop learning tools.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.952-959
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• 2018

Clustering is one of the most fundamental algorithms in machine learning. The performance of clustering is affected by the distribution of data, and when there are more data or more dimensions, the performance is degraded. For this reason, we use a stacked auto encoder, one of the deep learning algorithms, to reduce the dimension of data which generate a feature vector that best represents the input data. We use k-means, which is a famous algorithm, as a clustering. Sine the feature vector which reduced dimensions are also multi dimensional, we use the Euclidean distance as well as the cosine similarity to increase the performance which calculating the similarity between the center of the cluster and the data as a vector. A deep clustering networks combining a stacked auto encoder and k-means re-trains the networks when the k-means result changes. When re-training the networks, the loss function of the stacked auto encoder and the loss function of the k-means are combined to improve the performance and the stability of the network. Experiments of benchmark image ad document dataset empirically validated the power of the proposed algorithm.

• Journal of Information Science Theory and Practice
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• v.2 no.3
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• pp.29-39
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• 2014

In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.