• Journal of The Korean Association For Science Education
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• v.40 no.4
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• pp.415-427
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• 2020

This study aims to understand science education conducted in North Korea by analyzing the PCK components shown in two science teacher's guidebooks: (1) Guidebook for 1^st grade elementary school and (2) Guidebook for 1^st grade middle school. These were published after 2013, when "the first 12-year Universal Compulsory Curriculum" was implemented in North Korea. The analysis shows that both elementary and middle school guidebooks had the highest percentage of content in "Knowledge of Subject Matter", followed by "Knowledge of Instructional Strategies in Science" and "Knowledge of Science Curriculum". On the other hand, "Knowledge of Assessment in Science" and "Knowledge of Students" were significantly low in content. Within the "Knowledge of Subject Matter", both elementary and middle schools had the highest proportion of content in "Concepts and Theories", along with "Experiments and Inquiries" that was also significantly higher than other PCK components. Science teacher's guidebooks in North Korea advocates constructivist teaching style by using "discussions" as the main activity when conveying scientific concepts and theories to students or conducting scientific inquiry classes. Furthermore, "Knowledge of Instructional Strategies in Science" was mainly focused on guiding the "Instruction sequence and method" from the "Topic-specific Strategies", while only a small part of the "Subject-specific Strategies" was being presented. Also, Science teacher's guide books in North Korea included only a few theoretical elements of science education in both the general outline and the particular sections of guidebooks. "Knowledge of Science Curriculum" was mainly composed of "Lesson Objectives" with some inclusion of "Vertical Articulation" and "Horizontal Articulation". "Knowledge of Assessment in Science" and "Knowledge of Students" accounted for a small portion compared to the science teacher's guidebooks in South Korea.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.1
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• pp.397-416
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• 2006

This study is focusing on the establishment of knowledge management framework of library, supposed that library becomes an integrated knowledge system offering various types of knowledge. Knowledge management of library based on knowledge ecology justifies the logical and physical roles of library, as the sustainer of the knowledge ecosystem in which all the types of social factors consisting of knowledge ecosystem are Interacting to continuously circulate knowledge. The library as the center of knowledge ecosystem should make sure the systemized environment in which knowledge producer is supported to timely distribute knowledge to knowledge consumer through information professional accomplishing the role of knowledge facilitator.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.309-324
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• 2015

In this paper we introduce how to analyze survival data via a SRC-Stat statistical package. This provides classical survival analysis (e.g. Cox's proportional hazards models for univariate survival data) as well as advanced survival analysis such as shared and nested frailty models for multivariate survival data. We illustrate the use of our package with practical data sets.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.343-351
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• 2015

We introduce how to fit random effects models via a SRC-Stat statistical package. This package has been developed to fit double hierarchical generalized linear models where mean and dispersion parameters for the variance of random effects and residual variance (overdispersion) can be modeled as random-effect models. The estimates of fixed effects, random effects and variances are calculated by a hierarchical likelihood method. We illustrate the use of our package with practical data-sets.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes the hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.288-291
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• 2003

For the purpose of building the more efficient knowledge learning system, it is very important to make a good structure of the knowledge system first of all. The well designed knowledge system can make the stored knowledge to be easily accessed for knowledge acquisition and extraction. Expert knowledge can also play a good role for controlling. Accordingly, in this paper we propose the Hierarchical modular system with expert knowledge gating mechanism. This system consists of the mechanisms for knowledge acquisition, constructing the associative memory, knowledge inference and extraction according to the expert knowledge gating mechanism. We applied this system to the medical diagnostic area for classifying Virus(coxackie virus, echovirus, cold), Rhinitis(Nonallergic, allergic) and tested with symptom data

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• Korean Management Science Review
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• v.32 no.4
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• pp.81-96
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• 2015

This paper models knowledge diffusion on an inter-organizational network. Based on literatures related to knowledge diffusion, the model considers critical factors that affect diffusion behavior including nodal property, relational property, and environmental property. We examine the relationships among network structure, knowledge search, and diffusion performance. Through a massive simulation runs based on the agent-based model, we find that the average path length of a network decreases a firm's cumulative knowledge stock, whereas the clustering coefficient of a firm has no significant relationship with the firm's knowledge. We also find that there is an interaction effect of network structure and the range of knowledge search on knowledge diffusion. Specifically, in a network of a larger average path length (APL) the marginal effect of search conduct is significantly greater than in that of a smaller APL.

• Journal of the Korean Society of Food Science and Nutrition
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• v.24 no.1
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• pp.10-18
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• 1995

Nutrition knowledge of mothers who had middle-school studients was investigated using questionnaire about nutrition knowledge and food habit. The results were summerized as follows ; The mean score of nutrition knowledge was 25.3 (out of possible-80-80points), which score was slightly lower than those of other studies. the percentage of perceived knowledge and accuracy of the knowledge were 77.7% and 79.6%, respectively. these scores were influenced by general characteristics such as age, education, occupation, income, food expense. With decreasing age and increasing education level, family income, nutritional knowledge score, the percentage of perceived knowledge and accuracy were significantly getting higher. The levels of both perceived knowledge and accuracy on the necessi쇼 of vitamins and minerals were above 90%. However, the accuracy on protein quality and dietary fiber was below 40%. The better food habit a subject had, the higher was the nutrition knowledge score.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.145-156
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• 1996

Although knowledge discovery is increasingly important in databases, the discovered knowledge sets may not be effectively used for application domains. It is partly because knowledge discovery does not take user's interests into account, and too many knowledge sets are discovered to handle efficiently. We believe that user's interests are conveyed by a query and if a nested query is concerned it may include a user's thought process. This paper describes a novel concept for discovering knowledge sets based on query processing. Knowledge discovery process is performed by: extracting features from databases, spanning features to generate range features, and constituting a knowledge set. The contributions of this paper include the following: (1) not only simple queries but also nested queries are considered to discover knowledge sets regarding user's interests and user's thought process, (2) not only positive examples (answer to a query) but also negative examples are considered to discover knowledge sets regarding database abstraction and database exceptions, and (3) finally, the discovered knowledge sets are quantified.