• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.781-786
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• 2009

The cloud computing environment is a new trend of web based application parts. It can be IT business model that is able to easily support learning service and allocate resources through the internet to users. U-learning also is a maximal model with efficiency of the internet based learning. Thus, in this research, we proposed a design of u-learning's teaching and learning model that is applying the internet based learning. Proposal method is to fit u-learning and has 7 steps: Preparing, planning, gathering, learning process, analysis and evaluation, and feedback. We make a cloud u-learning server and cloud LMS to process and manage the service. And We also make a mobile devices meta data to aware the model.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.41-52
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• 2018

In Computational thinking is emphasized as a basic learning ability to grow into a key talent in the digital society. There is much interest and discussion on computing education nationally, and the Korean government has also included education in the curriculum. As a result of these changes, the level of computer literacy that preliminary teachers need to be imporved, and the role of computational thinking as a leader in digital society is being emphasized by teachers. Therefore, it is necessary to have a curriculum that can understand computational thinking through various programming learning from preliminary teacher education curriculum. In this study, we designed and taught programming curriculum for non-majored preliminary teachers. Through the developed questionnarie, we analyzed the affect of programming education on the preliminary teacher's development of computational thinking ability.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.621-628
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• 2019

The 2015 revised curriculum offers elementary students an unplugged computing education as a way to learn the concepts and principles of computer science in an easy and fun way and to improve their computational thinking. Yutnori is a traditional board game unique to Korea, which contains various contents such as history, culture, and science of our people, which helps to cultivate cultural identity of learners, and can effectively promote cooperation and communication among members. In this paper, we examined the possibility that Yutnori could be used as an unplugged computing tool in elementary school software education and convergence education. Korean traditional board game Yutnori has elements that can learn the sun and movements of heavenly bodies as well as sequential, selection, and repetitive algorithm elements. Unplugged activities that apply Korean traditional culture Yutnori is expected to help foster creative convergence talents by improving elementary school students' computational thinking, communication and community.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.24-28
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• 2001

교육은 네트워크와 컴퓨팅 파워의 발달로 인한 가장 큰 응용 분야로서 각광을 받고 있으며, 많은 상업적 솔루션의 발표와 연구들이 진행되고 있으나 학습자들의 요구를 충족시키지 못하고 있다. 즉, 학습자들은 개인의 학습 능력에 맞는 개별화된 컨텐츠로 교육받기를 원한다. 이 연구에서는 이러한 학습자들의 개별화원 학습 요구를 만족시키기 위해, 학습자의 인지 정보를 시간의 흐름에 따라 실시간 모델링을 할 수 있는 모델을 제안하였고, 이러한 모델에 기반한 교육 시스템을 설계하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.844-847
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• 2003

모바일 컴퓨팅 기능은 휴대의 편리성과 장소와 시간에 구애 없이 인터넷을 사용할 수 있다는 측면에서 많은 사람들의 관심과 수요자가 계속 증가하고 있다. 이러한 시대적인 요구에 따라 학교 학습 교육도 기존의 유선에 의한 학습 시스템 외에 무선 상태에서 언제 어디서나 학습이 가능한 무선 학습시스템 개발에 많은 관심을 가지고 있다. 본 연구는 시대적 환경을 고려하여 모바일 환경에서 학습능력이 가능한 평가시스템을 설계한다 학습시스템의 기본 설계 내용은 최근 모바일 환경에서 활용 가능한 지문을 이용한 문제풀이 기능, 반복문제 풀이, 연속 다운로드 그리고 사용자 편리성 등이 고려되고 있다. 그리고 이를 디스플레이 할 수 있는 시스템을 설계한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2167-2175
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• 2017

In recent years, an IoT is dramatically developing according to the enhancement of AI, the increase of connected devices, and the high-performance cloud systems. Huge data produced by many devices and sensors is expanding the scope of services, such as an intelligent diagnostics, a recommendation service, as well as a smart monitoring service. The studies of edge computing are limited as a role of small server system with high quality HW resources. However, there are specialized requirements in a smart factory domain needed edge computing. The edges are needed to pre-process containing tiny filtering, pre-formatting, as well as merging of group contexts and manage the regional rules. So, in this paper, we extract the features and requirements in a scope of efficiency and robustness. Our edge offers to decrease a network resource consumption and update rules and learning models. Moreover, we propose architecture of edge computing based on learning factors sharing with a cloud system in a smart factory.

• The Journal of Korean Association of Computer Education
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• v.22 no.2
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• pp.11-20
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• 2019

In Korea, the software education in elementary and middle school is essential to the 2015 revised curriculum, and various software education policies are being implemented. It is necessary to analyze the effects of these changes on computer and information literacy of students. This study investigates and analyzes the present state of computer and information literacy education in 32 middle schools nationwide. For the 640 students, we surveyed the students' status of coding education, confidence in computational thinking based on coding experience, confidence in computational thinking according to the frequency of computer use for learning purposes, and confidence in computational thinking ability according to the frequency of major ICT activities in class. As a result, there was a lack of Computer and Information literacy educational opportunities through school and relatively lack of educational opportunities for students in the rural area. And the more learning experience showed a positive impact on the confidence in computational thinking.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.628-630
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• 2005

유비쿼터스 컴퓨팅 환경의 중요한 이슈 중 하나인 상황인식은 컴퓨팅환경(예를 들어 가용 처리장치, 사용자 입력과 표시를 위한 장치, 네트워크 수용량, 다른 기기와의 접속용이성 및 컴퓨팅비용 등), 사용자 환경(위치, 주위 사람들과의 접촉, 사회적 입장 등) 및 물리적 환경(밝기, 소음, 온도 등)이 지속적으로 변화하는 수행 환경에서 인간으로 하여금 본연의 목적을 달성하는데 집중할 수 있도록 지원하는 인간 친화적인 시스템을 제공하기 위한 필수 기술이다. 이러한 상황인식을 이용하여, 사람이나 장소 및 사물의 입장이나 처지 혹은 관계 등을 특징 지을 수 있는 신원, 위치, 상태(혹은 활동) 및 시간의 4가지 상황정보를 고려한 학습이 이루어지도록 지원함으로써 학습에 있어서의 접근용이성과 적응성을 높이기 위한 컨텐츠 전승제어 시스템을 제안한다.

• Journal of Platform Technology
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• v.11 no.4
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• pp.71-79
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• 2023

In this paper, we analyze the characteristics of machine learning workloads and, based on them, propose a distributed in-memory caching technique to improve the performance of machine learning workloads. The core of machine learning workload is model training, and model training is a computationally intensive task. Performing machine learning workloads in a Kubernetes-based cloud environment in which the computing framework and storage are separated can effectively allocate resources, but delays can occur because IO must be performed through network communication. In this paper, we propose a distributed in-memory caching technique to improve the performance of machine learning workloads performed in such an environment. In particular, we propose a new method of precaching data required for machine learning workloads into the distributed in-memory cache by considering Kubflow pipelines, a Kubernetes-based machine learning pipeline management tool.