• Journal of Korean Elementary Science Education
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• v.30 no.2
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• pp.213-231
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• 2011

The purpose of this study was to investigate knowledge types which the elementary science gifted students would use when solving a science problem, and to examine characteristics and types that were shown in the science problem solving process. For this study, 39 fifth graders and 38 sixth graders from Institute of Education for the Gifted Science Class were sampled in one National University of Education. The results of this study were as follows. First, for science problem solving, the elementary science gifted students used procedural knowledge and declarative knowledge at the same time, and procedural knowledge was more frequently used than declarative knowledge. Second, as for the characteristics in the understanding step of solving science problems, students tend to exactly figure out questions' given conditions and what to seek. In planning and solving stage, most of them used 3~4 different problem solving methods and strategies for solving. In evaluating stage, they mostly re-examined problem solving process for once or twice. Also, they did not correct the answer and had high confidence in their answers. Third, good solvers had used more complete or partially applied procedural knowledge and proper declarative knowledge than poor solvers. In the problem solving process, good solvers had more accurate problem-understanding and successful problem solving strategies. From characteristics shown in the good solvers' problem solving process, it is confirmed that the education program for science gifted students needs both studying on process of acquiring declarative knowledge and studying procedural knowledge for interpreting new situation, solving problem and deducting. In addition, in problem-understanding stage, it is required to develop divided and gradual programs for interpreting and symbolizing the problem, and for increasing the understanding.

• Journal of Korean Elementary Science Education
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• v.38 no.1
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• pp.73-86
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• 2019

The purpose of this study is to investigate the characteristics of problem solving strategies that gifted students use in science inquiry problem. The subjects of the study are the notes and presentation materials that the 15 team of elementary and junior high school students have solved the problem. They are a team consisting of 27 elementary gifted and 29 middle gifted children who voluntarily selected topics related to dimple among the various inquiry themes. The analysis data are the observations of the subjects' inquiry process, the notes recorded in the inquiry process, and the results of the presentations. In this process, the knowledge related to dimple is classified into the declarative knowledge level and the process knowledge level, and the strategies used by the gifted students are divided into general strategy and supplementary strategy. The results of this study are as follows. First, as a result of categorizing gifted students into knowledge level, six types of AA, AB, BA, BB, BC, and CB were found among the 9 types of knowledge level. Therefore, gifted students did not have a high declarative knowledge level (AC type) or very low level of procedural knowledge level (CA type). Second, the general strategy that gifted students used to solve the dimple problem was using deductive reasoning, inductive reasoning, finding the rule, solving the problem in reverse, building similar problems, and guessing & reviewing strategies. The supplementary strategies used to solve the dimple problem was finding clues, recording important information, using tables and graphs, making tools, using pictures, and thinking experiment strategies. Third, the higher the knowledge level of gifted students, the more common type of strategies they use. In the case of supplementary strategy, it was not related to each type according to knowledge level. Knowledge-based learning related to problem situations can be helpful in understanding, interpreting, and representing problems. In a new problem situation, more problem solving strategies can be used to solve problems in various ways.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.43-49
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• 2015

The aim of this study was to model unusual association with declarative knowledge by positive affect using ACT-R cognitive architecture. Existing research related with cognitive modeling tends to pay a lot of attention to strong and negative cognitive moderator. Mild positive affect, however, has far-reaching effects on problem solving and decision making. Typically, subjects with positive affect were more likely to respond to unusual associates in a word association task than subjects with neutral affect. In this study, a cognitive model using ACT-R cognitive architecture was developed to show the effect of positive affect on the cognitive organization related with memory. First, we organized the memory structure of stimulus word 'palm' based on published results in a word association task. Then, we decreased an ACT-R parameter that reflects the amount of weighting given to the dissimilarity between the stimulus word and the associate word to represent reorganized memory structure of the model by positive affect. As a result, no significant associate probability difference between model prediction and existing empirical data was found. The ACT-R cognitive architecture could be used to model the effect of positive affect on the unusual association by decreasing (manipulating) the weight of the dissimilarity. This study is useful in conducting model-based evaluation of the effects of positive affect in complex tasks involving memory, such as creative problem solving.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1434-1445
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• 2000

An expert system executes the inference, based on the knowledge of specific domain. the reliability on the results of inference depends upon both the consistency and accuracy of knowledge. This is the reason why expert system requires the facilities which can practice an access to the various kinds of knowledge and maintain the consistency and accuracy of knowledge an maintain the consistency and accuracy of knowledge. This paper is to implement an expert system permitting an access of declarative and procedural knowledge in the knowledge base and in the data base. This paper is also to implement a knowledge acquisition system which adds the knowledge a only if its accuracy and consistency are maintained, after verifying the potential errors such as contradiction, redundancy, circulation, non-reachable rule and non-lined rule. In consequence, the expert system realizes a good access to the various sorts of knowledge and increases the reliability on the results of inference. The knowledge acquisition system contributes tro strengthening man-machine interface that enables users to add the knowledge easily to the knowledge base.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.777-784
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• 1994

A design expert system for the ship structural design is developed to support inexperienced designers. To establish the knowledge-base, an expert system development shell, Nexpert, is used. Knowledge is extracted from the rules of a classification society of ships, and also from an existing ship structural program that is being used by ship designers. This knowledge is systematized using the objectoriented concept. The design support system is constructed by adding additional functions which are required for the conventional engineering design work. Added functions are; calculation of longitudinal strength, database of existing ship designs, graphical user interface, and visualization of design results. It is observed that visualizing the relationships among the rules, which are activated to draw a certain design decision, is helpful. The system can easily be updated according to changes of the rule books of ship classification societies.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.157-185
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• 1998

One of the essential issues in model systems is how to represent and manipulate mathematical modeling knowledge. As the bases of integrated modeling environments, current modeling frameworks have limitations: lack of facility to coordinate different users perpectives and lack of mechanism to reuse modeling knowledge. In this paper, multi-facetted modeling approach is proposed as a basis for the development of integrated modeling environment which provides facilities for (1) independent management of modeling knowledge from individual models； (2) object-oriented conceptual blackboard concept； (3) multi-facetted modeling； and (4) declarative representation of mathematical knowledge. The proposed multi-facetted approach is illustrated using multicommodity transportation models.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.49-63
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• 2003

This paper proposes and implements a tool for the development of efficient and reliable expert system. In the expert system the inference is executed, based on the knowledges stored in the knowledge base of specific domain. To acquire the reliable results of inference, the expert system requires the facilities which can access the various kinds of knowledge and maintain the consistency and accuracy of knowledge. In this context this paper implemented the knowledge management system which maintains the consistency and accuracy of knowledge, adding selectively the knowledges without error to the knowledge base by verifying their error before the knowledges are added to the knowledge base. At the same time this paper made the expert system call and use the procedural knowledge and the declarative knowledge in the data base so that it might use the various kinds of knowledge in the process of inference.

• Language and Information
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• v.11 no.1
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• pp.25-38
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• 2007

So-called multiple nominative constructions (MNCs) in Korean are quite theoretically as well as computationally puzzling. This paper shows that a grammar allowing the interaction of declarative constraints on types of signs - in particular, constructions (phrases and clauses)-can provide a robust and efficient way of encoding generalizations for two different MNCs. The feasibility of the grammar developed has been checked with its implementation into the LKB (Linguistic Knowledge Building) system.

• Journal of the Korean earth science society
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• v.23 no.2
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• pp.180-187
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• 2002

The aim of this study was to investigate the factors affecting earth science problem-solving performances of elementary school pre-service teachers. The participants of the study were 81 students attending an elementary school teacher education university. The instruments of the study were paper-and-pencil tests, questionnaires, and interviews. The tests mainly measured the participants' problem solving abilities in the motions of the moon and the planets. Correlation and multiple regression techniques were used for data analysis. The results demonstrated that the pre-service teachers' problem solving abilities were low. Problem-solving performances were affected by the procedural knowledge, the participants' perception of the past earth science performance, self-efficacy, and the prerequisite declarative knowledge. Contrary to our expectation, the spatial visualization ability was not found to be related to the problem-solving performances. Implications of the study are drawn, and suggestions are made for further research.

• Journal of The Korean Association For Science Education
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• v.23 no.3
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• pp.215-228
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• 2003

The present study is to analyze the arguments about the generation of declarative scientific-knowledge in the philosophy of science and invent a structured model of the process of scientific-knowledge generation with the types of the generated scientific-knowledge. The invented model shows that scientific-knowledge generation is a distinctive process with the processes of inductive, abductive, and deductive thinking. Furthermore, inductive process is included with observation, which is consisted of simple observation and operative observation, and rule-discovery which is involved with the processes of commonness discovery, classification, pattern discovery, and hierarchical relationship. Also, abductive process has two components. One component generates question and second component generates hypothesis in which the process consists of representing question situation, identifying experienced situation, identifying causal explicans, and generating hypothetical explicans. Finally, deductive process is involved with logical inventing test method and evaluation criteria, concrete inventing test method and evaluation criteria, evaluating hypothesis, and making conclusion.