• Archives of design research
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• v.16 no.2
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• pp.271-280
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• 2003

In digital age, multimedia technology has changed the learning method as a learner-directed way. CD-rom and internet that are major two multimedia learning way, has aimed at edutainment which combine education and entertainment. However, existing educational contents can only induce temporary learning motivation, and are in short of entertaining factors enough to induce continuous and ingenuous learning motivation. Therefore, in order to be used by users efficiently, educational software have to adapt characteristics of educational game more actively. In this paper, adoption method of characteristics of educational game in learning contents is sought and the specific example of adoption is demonstrated by a case study of developing vocabulary learning educational game.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.971-973
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• 2017

국제화 시대를 맞이하여 세계 공용어인 영어의 중요성이 부각되고 있다. 특히, 영어 교육의 학습 연령대는 점점 낮아지고 있는 추세이며, 이에 동반하여 저 연령층 영어 교육 콘텐츠가 출시되고 있다. 하지만 현재 저 연령층을 대상으로 출시되는 콘텐츠들은 연령에 맞지 않는 교육 자료를 제시하거나 언어 학습에 필요한 상황적 다양성이 부족한 것이 현실이다. 본 논문에서는 딥러닝을 적용하여 사용자가 원하는 상황을 촬영한 영상에서 대상 연령에 적합한 영어 문장을 생성하고 읽어주는 학습 시스템을 제안한다. 본 시스템을 통하여 저 연령층에 적합한 영어 교육 환경을 제공하고, 저 연령층에게 나타나는 영어 교육의 불균형을 해소하고자 한다.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.161-168
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• 2020

Predicting outcome of the sports enables teams to establish their strategy by analyzing variables that affect overall game flow and wins and losses. Many studies have been conducted on the prediction of the outcome of sports events through statistical techniques and machine learning techniques. Predictive performance is the most important in a game prediction model. However, statistical and machine learning models show different optimal performance depending on the characteristics of the data used for learning. In this paper, we propose a new ensemble model to predict English Premier League soccer games using statistical models and the machine learning models which showed good performance in predicting the results of the soccer games and this model is possible to select a model that performs best when predicting the data even if the data are different. The proposed ensemble model predicts game results by learning the final prediction model with the game prediction results of each single model and the actual game results. Experimental results for the proposed model show higher performance than the single models.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.461-470
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• 2023

While speech animation generation employing deep learning has been actively researched for English, there has been no prior work for Korean. Given the fact, this paper for the very first time employs supervised deep learning to generate Korean speech animation. By doing so, we find out the significant effect of deep learning being able to make speech animation research come down to speech recognition research which is the predominating technique. Also, we study the way to make best use of the effect for Korean speech animation generation. The effect can contribute to efficiently and efficaciously revitalizing the recently inactive Korean speech animation research, by clarifying the top priority research target. This paper performs this process: (i) it chooses blendshape animation technique, (ii) implements the deep-learning model in the master-servant pipeline of the automatic speech recognition (ASR) module and the facial action coding (FAC) module, (iii) makes Korean speech facial motion capture dataset, (iv) prepares two comparison deep learning models (one model adopts the English ASR module, the other model adopts the Korean ASR module, however both models adopt the same basic structure for their FAC modules), and (v) train the FAC modules of both models dependently on their ASR modules. The user study demonstrates that the model which adopts the Korean ASR module and dependently trains its FAC module (getting 4.2/5.0 points) generates decisively much more natural Korean speech animations than the model which adopts the English ASR module and dependently trains its FAC module (getting 2.7/5.0 points). The result confirms the aforementioned effect showing that the quality of the Korean speech animation comes down to the accuracy of Korean ASR.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.61-67
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• 2021

The purpose of this study is to demonstrate how EFL learners can overcome the limitations of traditional classes and practice communication through the learning activity model. As a research method, it was conducted from March to June 2019 to develop and derive strategies and guidelines through model development, validation, and application. After two validity tests, the model was applied to the experimental group, resulting in an increase of self-direction, engagement, problem-solving, and participation. Moreover the post results showed significant results in all fields, the usefulness of this model was confirmed. However, continuous follow-up research is needed, including the development of software that can easily apply AI related to English learning to classes, and the presentation of convergence activities with more systematic maker education in learning activities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2049-2068
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• 2021

AI combined with NLP techniques has promoted the use of Virtual Assistants and have made people rely on them for many diverse uses. Conversational Agents are the most promising technique that assists computer users through their operation. An important challenge in developing Conversational Agents globally is transferring the groundbreaking expertise obtained in English to other languages. AI is making it possible to transfer this learning. There is a dire need to develop systems that understand secular languages. One such difficult language is Hindi, which is the fourth most spoken language in the world. Semantic similarity is an important part of Natural Language Processing, which involves applications such as ontology learning and information extraction, for developing conversational agents. Most of the research is concentrated on English and other European languages. This paper presents a Corpus-based word semantic similarity measure for Hindi. An experiment involving the translation of the English benchmark dataset to Hindi is performed, investigating the incorporation of the corpus, with human and machine similarity ratings. A significant correlation to the human intuition and the algorithm ratings has been calculated for analyzing the accuracy of the proposed similarity measures. The method can be adapted in various applications of word semantic similarity or module for any other language.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.197-206
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• 2021

This study is a case of convergence education using the AI model of entry in elementary schools. The subject is English, and the class was conducted based on the image learning model among the convergence activities with the art department drawing and the AI model of the entry. In order to effectively achieve the learning goals of speaking and writing in English education. The class was designed by combining art and SW. Students experienced communication using AI, improved confidence, and were able to improve creativity and communication skills by expressing not only listening and speaking but also expressing through various media such as pictures and photos. In addition, in order to find out the effectiveness of the class, a survey was conducted on students and the results were analyzed. As a result of the analysis, it was found that it had a positive effect on students' participation rate, degree of understanding AI after class, interest in AI, satisfaction with AI classes.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.329-331
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• 2020

Edutech is a compound word of education and technology, and is an educational paradigm in the era of the 4th industrial revolution. This refers to next-generation education using information and communication technology (ICT) such as big data, artificial intelligence (AI), robots, and virtual reality (VR) of the 4th industrial revolution. e-Learning is being used as an online lecture for education in ICT, but edutech is attracting attention along with e-learning as the feeding of non-face-to-face education has rapidly increased due to COVID-19. Therefore, this paper summarizes the reviewed papers on the blockchain-based badge service platform, simulation-based collaborative e-Learning system, video English dictionary, and blockchain-based access control audit system.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.319-327
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• 2006

Higher grade elementary school students who have superior cognitive abilities need education of basic principles of computer or programming rather than computer in education. In this study, all the errors occurring while elementary school students wrote and executed programs were collected. in the method of predicting and dealing with possible-to-occur problems on programming education of the higher grades (4th, 5th and 6th grades) during their optional special activities or during talent aptitude activities after school, classified by type and analyzed. If the errors analyzed are put to practical use, optimal programming curriculums could be written and such curriculums could be a great contribution to induction of learning effect and interest on teaching learning. It was found by analyzing the errors collected for this study that the most of elementary school students during programming felt difficulties in simple errors by poor use of software and in simple coding by poor use of reserved words in English. In the next, students occurred errors by difficulties in understanding grammar. It was exposed that these error types were the opposite phenomena to those analyzed by commercial software developing companies, however, it is predicted that if teaching learning is setting improved, the same phenomena could be found desirably.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.129-136
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• 2010

In this paper, we present an Example-based Dialogue System for English conversation tutoring. It aims to provide intelligent one-to-one English conversation tutoring instead of old fashioned language education with static multimedia materials. This system can understand poor expressions of students and it enables green hands to engage in a dialogue in spite of their poor linguistic ability, which gives students interesting motivation to learn a foreign language. And this system also has educational functionalities to improve the linguistic ability. To achieve these goals, we have developed a statistical natural language understanding module for understanding poor expressions and an example-based dialogue manager with high domain scalability and several effective tutoring methods.