• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1471-1476
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• 2013

This research examines how PBL(Problem-based Learning; PBL) system affects to 'Self-directed learning ability', by developing and applying it to the participants of "Science Cyber Conference" - the web based on-line debating learning program - among those students of the Affiliated Institute of Science gifted education of K University, for 16weeks. With this, also the cognizance of learners for the PBL class process are looked into together. After conducting the program applied with the web-based PBL strategy, the participants 'Self-directed learning ability' showed the remarkable change statistically (p<.05). Especially it showed the meaningful changes in six sections (p<.05), among those subdivided seven sections of 'Self-directed learning ability', with the one exception, 'Self-confidence as a Learner'. They also showed the positive response to the class which adopted the web-based PBL strategy.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1158-1165
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• 1999

조건부 분기 명령어(conditional branch instruction)의 잘못된 분기 예측(branch misprediction)은 프로세서의 성능 향상에 심각한 장애 요인이 되고 있다. 특히 시분할(time-sharing) 시스템과 같이 문맥 교환(context switch)이 발생하는 멀티프로그래밍 환경(multiprogramming environment)에서는 더욱 낮은 분기 예측 정확성(branch prediction accuracy)을 보인다. 본 논문에서는 문맥 교환이 발생하는 멀티프로그래밍 환경에서 높은 분기 예측 정확성을 보이는 중첩 분기 예측표 교환(Overlapped Predictor Table Switch, OPTS) 기법을 소개한다. 분기 예측표(predictor table)를 분할하여 각각의 프로세스(process)에 할당하는 OPTS 기법은 문맥 교환의 영향을 최소화함으로써 높은 분기 예측 정확성을 유지하는 분기 예측 방법이다.Abstract There is wide agreement that one of the most important impediments to the performance of current and future pipelined superscalar processors is the presence of conditional branches in the instruction stream. Accurate branch prediction is required to overcome this performance limitation. Many branch predictors have been proposed to help to alleviate this problem, including the two-level adaptive branch predictor, and more recently, hybrid branch predictor. In a less idealized environment, such as a time-sharing system, code of interest involves context switches. Context switches, even at fairly large intervals, can seriously degrade the performance of many of the most accurate branch prediction schemes. In this study, we measure the effect of context switch on the branch prediction accuracy in various situation and show the feasibility of our new mechanism, OPTS(Overlapped Predictor Table Switch), which save and restore branch history table at every context switch.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.4
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• pp.247-258
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• 2009

Distributed file systems running on a cluster of inexpensive commodity hardware are being recognized as an effective solution to support the explosive growth of storage demand in large-scale Internet service companies. This paper presents the design and implementation of BeanFS, a distributed file system for large-scale e-mail services. BeanFS is adapted to e-mail services as follows. First, the volume-based replication scheme alleviates the metadata management overhead of the central metadata server in dealing with a very large number of small files. Second, BeanFS employs a light-weighted consistency maintenance protocol tailored to simple access patterns of e-mail message. Third, transient and permanent failures are treated separately and recovering from transient failures is done quickly and has less overhead.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4167-4173
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• 2010

ICT education guidelines revised in 2005 reinforce computer science elements such as algorithm, data structure, and programming covering all schools. It means that goal of computer education is improving problem-solving abilities not using of commercial software. So this paper suggests problem-solving method of maze escape through robots' cooperation in an effort of learning these elements. Problems robots should solve are first-search and role-exchange. First-search problem is that first robot searches maze and send informations about maze to the second robot in real time. Role-exchange problem is that first robot searches maze, but loses its function at any point. At this time second robot takes a role of first robot and performs first robot's missions to the end. To solve these two problems, it goes through four steps; problem analysis, algorithm description, flowchart and programming. Additional effects of our suggestion are chance of cooperation among students and use of queue in data structure. Further researches are use of more generalized mazes, application to real field and a talented curriculum.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.328-334
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• 2004

Recently, Software DSMs continue to improve its performance and scalability As Software DSMs become attractive on larger clusters, the focus of attention is likely to move toward improving the reliability of a system. A popular approach to tolerate failures is message logging with checkpointing, and so many log-based rollback recovery schemes have been proposed. In this work, we propose a remote logging scheme which uses the volatile memory of a remote node assigned to each node. As our remote logging does not incur frequent disk accesses during failure-free execution, its logging overhead is not significant especially over high-speed communication network. The remote logging tolerates multiple failures if the backup nodes of failed nodes are alive. It makes the reliability of DSMs grow much higher. We have designed and implemented the FT-KDSM(Fault Tolerant KAIST DSM) with the remote logging and showed the logging overhead and the recovery time.

• Journal of The Korean Association of Information Education
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• v.22 no.6
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• pp.689-699
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• 2018

The purpose of this study was to investigate the prediction of self-regulated learning, GRIT and parents support on computational thinking and learning satisfaction in online software education. The participants were 71 elementary students who attended to an online software education which K university offered in Spring 2018. The 63 of cases were used to analyze by SPSS. The key findings were as follows: First, self-regulated learning and GRIT significantly predicted computational thinking. Second, self-regulated learning and GRIT significantly predicted learning satisfaction. This research suggested the implications for computational thinking and learning satisfaction in online software education.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.167-173
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• 2021

The purpose of this study is to discuss the types of algorithms and data categories in AI education for elementary school students. The study surveyed 11 pre-elementary teachers after providing education and practice on various data, artificial intelligence algorithm, and AI education platform for 15 weeks. The categories of data and algorithms considering the elementary school level, and educational tools were presented, and their suitability was analyzed. Through the questionnaire, it was concluded that it is most suitable for the teacher to select and preprocess data in advance according to the purpose of the class, and the classification and prediction algorithms are suitable for elementary AI education. In addition, it was confirmed that Entry is most suitable as an AI educational tool, and materials that explain mathematical knowledge are needed to educate the concept of learning of AI. This study is meaningful in that it specifically presents the categories of algorithms and data with in AI education for elementary school students, and analyzes the need for related mathematics education and appropriate AI educational tools.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.205-212
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• 2021

The purpose of this study is to analyze elementary school students' interest in virtual reality(VR) technology, usability, and the possibility of learning media. In particular, it is intended to be used for content creation for artificial intelligence(AI) education in the future. The effectiveness of elementary education using virtual reality technology was confirmed through the analysis of overseas research, and the applicability to elementary school students in Korea was analyzed. To proceed with the analysis, various virtual reality contents were provided to 5th grader of elementary school, and then, interest, usability, usefulness, and possibility of use in class and learning were surveyed. As a result of the study, it was confirmed that students' interest in virtual reality contents was very high, and that it could be used sufficiently as a learning medium. It suggests that it can be used in artificial intelligence education and data science education, which have recently been emphasized in importance. In particular, virtual reality can be used to simulate abstract data and artificial intelligence.

• Korean Journal of Cognitive Science
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• v.30 no.3
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• pp.157-174
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• 2019

Motivation of human individuals to perform on intellectual tasks can be hampered by identity threat from intellectual machines. A laboratory experiment examined whether individuals' performance loss on intellectual tasks appears under human identity threat. Additionally, by affirming alternative attributes of human identity, researchers checked whether group-affirmation alleviate the performance loss on intellectual tasks. This research predicted that under high social identity threat, individuals' performance loss on the intellectual tasks would be moderated by valuing alternative attributes of human identity. Experiment shows that when social identity threat is increased, human individuals affirmed alternative human attributes show higher performance on intellectual tasks than individuals non-affirmed. This effect of human-group level affirmation on performance loss did not appear in the condition of low social identity threat. Theoretical and practical implications were discussed.

• The Journal of Korean Association of Computer Education
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• v.18 no.4
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• pp.1-9
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• 2015

Problem solving is essential skill for all students in the $21^{st}$ century. In particular, as the computing system ensures the effectiveness of problem solving in the various disciplines and real life, interest in learning algorithms to design a problem solving process is increasing. In order to improve problem solving skill, students should not only understand algorithm design skills but also apply appropriate skills to solve faced problem. In terms of these the puzzle can be considered a preferred learning tools to improve problem solving skill. Therefore, in this study we designed puzzled based algorithm learning and analyzed the impact of puzzle based algorithm learning on problem solving skills of leaners. As the results of research, we confirmed that the puzzled based algorithm learning took positive effect on enhancing problem solving skills of the learners.