• The Journal of Korean Association of Computer Education
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• v.11 no.6
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• pp.77-84
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• 2008

The Teaching & Learning Center plays an important role in increasing the expertise of instructors and for directing the diffusion of innovation not only in primary & secondary education but also in education at the university level. In this study, the Performance Evaluation Model is devised and developed for improving the competency of the Teaching & Learning Center. It consists of three domains - (a) the planning domain, (b) the process domain, and (c) the performance domain - and 11 external indices and 8 internal indices. The Performance Evaluation Index and Guidelines are proposed based on this model.

• The Journal of Korean Association of Computer Education
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• v.11 no.2
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• pp.55-64
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• 2008

Even though studies on improvement of programming language teaching and learning have been made continuously and many education courseware for programming languages have been developed, computer programming learners' performance is relatively poor. Thus, in this paper, we designed and realized a web- based visual programming learning system by applying cognitive apprenticeship model to improve effect of computer programming education and then put this system into practice in class. As a result, we suggested that it can have positive influence upon learners' performance and their attitude.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.773-793
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• 2022

The moving picture experts group (MPEG) immersive video (MIV) coding standard has been established to support six degrees of freedom (6DoF) in virtual reality (VR) by transmitting high-quality multiple immersive videos. The MIV exploits two approaches considering tradeoff between bandwidth and computational complexity: 1) eliminating correlation between multi-view videos or 2) selecting representative videos. This paper presents performance analysis on intermediate synthesized views on source view positions and synthesized pose traces using high-efficiency video coding (HEVC) and versatile video coding (VVC) for above-mentioned two approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.608-611
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• 2003

Performance assessment was introduced to improvement of self-directed learning and method of assessment for differenced learning as the seventh educational curriculum is enforced. Performance assessment is overcoming limitation about problem solving ability and higher thinking abilities assessment that is problem of a written examination and get into the spotlight by way for quality of class and school normalization. But performance assessment has problems about possibilities of assessment fault by appraisal, fairness, reliability, and validity of grading, ambiguity of grading standard, difficulty about objectivity security etc. This study proposes fuzzy performance assessment system to solve problem of the conventional performance assessment. This paper presented an objective and reliable performance assessment method through fuzzy reasoning, design fuzzy membership function and define fuzzy rule analyzing factor that influence in each sacred ground of performance assessment to account principle subject. Also, performance assessment item divides by formation estimation and subject estimation and designed membership function in proposed performance assessment method. Performance assessment result that is worked through fuzzy performance assessment system can pare down burden about appraisal's fault and provide fair and reliable assessment result through grading that have correct standard and consistency to students.

• Korean Medical Education Review
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• v.22 no.3
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• pp.198-206
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• 2020

This study aimed to identify needed improvements to current evaluation methods in medical school computer-based test (CBT) programs and test environments. To that end, an analysis of the importance and satisfaction was conducted through a survey of 3rd and 4th year medical students who had sufficient experience with CBT programs. Importance performance analysis methodology using the correlation coefficient was applied to assess average satisfaction and importance. The first quadrant (keep up the good work) was a factor of review and time management and test facilities among the conveniences of the CBT program. The second quadrant (concentrate here) was a factor of the convenience of the CBT program and computer monitor and chair factor within the test facilities. The third quadrant (low priority) was a factor of cheating and computer failure. The fourth quadrant (possible overkill) was the location, spacing, and temperature factors of the test facilities. Improvements are needed to reduce 'eye fatigue' and help students focus and understand the questions in the CBT programs. It is necessary to improve computer monitors, desks and chairs, and consider the subject's body type and manager in order to cope with computer breakdown and peripheral failures. Spare computers are needed. These findings are meaningful in that they have been able to identify factors that require improvement in the CBT program and test environment resulting from changes in assessment tools.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.209-213
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• 2021

Data mining is the application of specific algorithms for extracting patterns from data and KDD is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories or data streams. Data mining can be used for decision making in educational system. But educational institution does not use any knowledge discovery process approach on these data; this knowledge can be used to increase the quality of education. The problem was happening in the educational management system, but to make education system more flexible and discover knowledge from it huge data, we will use data mining techniques to solve problem.

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.41-48
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• 2008

Current performance evaluation of the natural science section mainly focuses on teacher evaluation, which causes slow feedback on the evaluation result and little evaluation on colleagues due to limits of time and space. In addition, report performance evaluation, which is a main target of the evaluation in the natural science section, is conducted mostly based on records of experiments and observation without any systematic forms. Such performance evaluation cannot meet expectation on the evaluation for a self-adjustment through instant feedback on the evaluation result and improvement of motivation through sharing common performance standard. Therefore, the study here completes an experiment/research report through information sharing and discussion among colleague learners based on the web and uses it for colleague or teacher evaluation. In addition, it is intended to recognize needs of learners and develop a performance evaluation system that can provide learners with appropriate feedback through the result.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.175-182
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• 2019

The study was conducted to verify the effect of basic life support training on the skill ability of police officers. The subjects of this study were 10 experimental group and 10 comparative group with voluntary consent after explaining the theory and significance of the training experiment at the police station located in K. The education program used in this study consists of theoretical education and practical training, and the theoretical education is 60 minutes and the practical training is 30 minutes. The measurement tool for basic resuscitation performance was measured based on the 'CPR and ECG Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care' presented by the American Heart Association. The results are as follows. The experimental group showed higher performance skills than the traditional control group in field confirmation performance skills, primary evaluation performance skills (A, B, C, medical evaluation), and BLS performance skills (heart compression, artificial respiration, medical evaluation) which are the basic resuscitation performance skills. In conclusion, this study confirmed that the theory and practice education program is more effective in improving the clinical performance of police officers than the traditional lectures and practice education, so it is possible to apply this simulation education program to the cardiac arrest patient emergency treatment.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.77-82
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• 2019

Collaborative filtering is a popular technique for recommender systems and used in many practical commercial systems. Its basic principle is select similar neighbors of a current user and from their past preference information on items the system makes recommendations for the current user. One of the major problems inherent in this type of system is data sparsity of ratings. This is mainly caused from the underlying similarity measures which produce neighbors based on the ratings records. This paper handles this problem and suggests a new similarity measure. The proposed method takes users rating patterns into account for computing similarity, without just relying on the commonly rated items as in previous measures. Performance experiments of various existing measures are conducted and their performance is compared in terms of major performance metrics. As a result, the proposed measure reveals better or comparable achievements in all the metrics considered.