• The Journal of Korean Association of Computer Education
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• v.7 no.5
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• pp.33-43
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• 2004

Fashion design education essentially requires not only a theoretical but also a practical process in which feedback comes through personal interactions between an instructor and a student. But the existing WBI system exemplifies its limitations by applying only a one-way Distance Education methodology that limit interactions based only on the theoretical texts. This study affirms that distance learning system is possible for the applied component of the fashion design curriculum as long as the specific needs of the particular program is taken into consideration and systematically applied. So it designed and applied an original web-based distance educational system specifically incorporating the needs of the fashion design curriculum Thus the results show that the enhanced distance education system is a tool that could be effectively utilized with the same degree of success as the traditional classroom as long as the traditional teaching component of direct interaction necessary to the fashion design program is incorporated.

• The Journal of Korean Association of Computer Education
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• v.12 no.5
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• pp.87-94
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• 2009

This paper presents a Web-based interactive and adaptive learning system that helps students learn the pumping lemma for the family of regular languages. Our system allows the students to proceed with their learning according to their individual differences through Web-Based Instruction and gives them opportunities for the interaction so that they can practice exercise related to the learning and gain feedbacks on the results of the exercises immediately. Especially, the system provides adaptive scaffolding that helps learners understand each step for the proof of the pumping lemma. Unlike existing systems that support learning the pumping lemma, the proposed system defines possible errors in advance and provides appropriate messages for corresponding errors. In addition, the system allows the learners to decompose a string into three parts so that they can understand the pumping lemma precisely.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1500-1506
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• 2020

In this paper, we study a scheduling problem based on reinforcement learning for overlay device-to-device (D2D) communication networks. Even though various technologies for D2D communication networks using Q-learning, which is one of reinforcement learning models, have been studied, Q-learning causes a tremendous complexity as the number of states and actions increases. In order to solve this problem, D2D communication technologies based on Deep Q Network (DQN) have been studied. In this paper, we thus design a DQN model by considering the characteristics of wireless communication systems, and propose a distributed scheduling scheme based on the DQN model that can reduce feedback and signaling overhead. The proposed model trains all parameters in a centralized manner, and transfers the final trained parameters to all mobiles. All mobiles individually determine their actions by using the transferred parameters. We analyze the performance of the proposed scheme by computer simulation and compare it with optimal scheme, opportunistic selection scheme and full transmission scheme.

• Journal of the Korea Institute of Building Construction
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• v.21 no.1
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• pp.71-78
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• 2021

The spread of COVID-19 and the advent of the Fourth Industrial Revolution have significantly affected the nature of college education causing many changes to the way it is conducted. One of these changes is the expansion of online education. The purpose of this study was to analyze the difficulties experienced by learners due to the transition to rapidly expanding online education at domestic universities, and to seek ways to support their learning through this new online platform. Results of a questionnaire showed that learners experienced difficulties in their interactions with professors because of the rapid transition to online education without adequate preparation. It was determined that there were not enough opportunities for communication between learners and professors as a result of non-face-to-face online education, and that learners did not receive Q&A or feedback quickly enough. The study also examined ways to ways to improve the effectiveness of online learning. Students showed a high preference for items such as "appropriate guidance regarding announcements such as lecture schedules," "providing lecture notes as learning materials."

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.353-360
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• 2022

The purpose of this study is to verify the effect of artificial intelligence storytelling education program designed to help learning artificial intelligence based on storytelling, the most important element of human intelligence, on learning flow. To this end, a 16-hour artificial intelligence education program was designed and developed, and applied over 8 weeks to 19 gifted students in 5th and 6th grades of elementary school. Artificial intelligence storytelling education program was developed in the form of teaching and learning course plans for each class and storybooks. Artificial intelligence storytelling education program application results showed significant improvements in average scores in all 9 sub-factors of learning flow, including combination of challenges and abilities, integration of behavior and consciousness, clear goal, concrete feedback, focus on task, sense of control, loss of self-consciousness, Distortion of the sense of time, and self-purpose experience. In other words, it was confirmed that artificial intelligence storytelling education program was effective in improving learning flow.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.13-22
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• 2023

The purpose of this paper is to explore the impact of online problem-based learning (PBL) on learners' 4C competencies and learning experience. The results of the study showed that, first, online PBL had a statistically significant effect on learners' problem-solving skills, communication skills, and pre-service teacher efficacy. Second, learners were very satisfied with the online PBL experience and perceived it to be very beneficial to their learning and to themselves as preservice teachers. Third, learners perceived that the real-time video conferencing system and instant messenger were very helpful for successful online PBL. Fourth, regarding the important factors for successful online PBL, the participants in this study perceived that communication and sincerity are very important, and the role of the leader is also important, but personal intimacy among team members is relatively less important. Fifth, learners perceive that instructor feedback is very important for successful online PBL. Finally, the implications of this study are discussed along with suggestions for future research.

• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.97-106
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• 2001

In this paper, we design and implement complement based speech training system for voice disorder. The system consists of three level of training: precedent training, training for speech apprehension and training for speech enhancement. To analyze speech of voice disorder, we extracted speech features as loudness, amplitude, pitch using digital signal processing technique. Extracted features are converted to graphic interface for visual feedback of speech by the system.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.137-143
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• 2002

This paper presents the In-process compensation to control cutter runout and improve the machined surface quality. Cutter runout compensation system consists of the micro-positioning servo system with piezoelectric actuator which is embeded in the sliding table to manipulate radial depth of cut in real-time. Cutting force feedback control was proposed in the angle domain based upon repetitive learning control strategy to eliminate chip load variation in end milling process. Micro-positioning control due to adaptive actuation force response improves the machined surface quality by compensation runout effect induced cutting force variation. This result will provide lots of information to build-up the preciswion machining technology.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.213-214
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• 2018

빅 데이터 활용의 증가로 인해 효율적으로 데이터를 분류하는 것은 머신러닝의 주요 과제이다. 제한적인 자원을 가지고 이에 맞는 처리능력을 갖기 위해서는 단일 기기의 자원 관리능력을 향상시키는 방향의 연구가 필요하다. 본 논문에서는 머신러닝을 위한 학습 데이터를 최대 엔트로피 이론을 적용시켜 효과적으로 분류하는 방법을 제안한다. 최대 엔트로피에 대한 간단한 설명과 최대 엔트로피 이론을 적용시키기 위한 간단한 사전 작업들의 방향 등에 대한 설명을 토대로 기술하였다. 또한 본 연구를 통해 얻게 된 문제점들과 향후 연구에 필요한 피드백을 갖는다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.269-270
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• 2018

제4차 산업혁명 시대를 살아갈 학생들에게 필요한 핵심 역량으로서 컴퓨팅 사고력의 중요성이 강조되고 있으며, 이와 관련하여 다양한 연구가 진행되고 있다. 그러나 대부분의 연구가 교수 학습 방법을 개발하고 효과성을 검증하는데 치중하는 반면, 학습자의 컴퓨팅 사고력을 어떻게 평가하고 피드백을 줄 것인지에 대한 연구는 부족하다. 따라서 본 연구에서는 컴퓨팅 사고력 평가에 관한 연구 중에서 KCI에 등재된 9편의 연구를 분석하고, 시사점을 도출하였다. 이는 컴퓨팅 사고력 평가에 관한 향후 연구의 방향을 제시해줄 것이라 기대한다.