• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.

• 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 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.

• Korean Journal of Cognitive Science
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• v.13 no.2
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• pp.47-59
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• 2002

Three experiments were conducted to investigate whether different types (common vs. uncommon) of prior-examples entail different effects in creative problem solving, and whether types/levels (rich or lean. common or uncommon) of background knowledge interact with types of prior-examples. It was found that the example types and the types/levels of background knowledge do interact and have some differential effects on generating novel and useful ideas. In Experiment 1 and 2. uncommon examples had a positive effect - generating many novel and useful ideas. regardless of background knowledge types. while common examples had positive effects, only when the background knowledge was somewhat uncommon In Experiment 3 it was also found that types (irrelevant,. single common. single uncommon, or multiple common + uncommon) of background knowledge seemed to influence differently on the ease of finding solutions: when background knowledge is diverse or not directly related to the task problem, uncommon prior examples produced much greater number of novel ideas than it was with single common or sin91e uncommon background knowledge. Implications of the present study were discussed. in relation to mental sets and fixation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.1
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• pp.16-21
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• 1990

A Knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. Expert system has the potential to solve a wide range of problems which require knowledge about the problem rather than a purely analytical approach. This papaer presents the application of knowledge based expert system to power system fault diagnosis. The contents of expert system develpped in this paper is judgement of fault section from a given alarm sets and production of all possible hypothesis for the single fault. Both relay failures and circuit breaker failures are considered simultaneously. Although many types of relay are used in actual system, experts recognize ones as several typical signals corresponding to the fault types. Therefore relays are classified into several types. The expert system is written in an artificial intelligence language "PROLOG" . Best-first search method is used for problem solving. Both forward chaining and backward chaining schemes are used in reasoning process. The application to a part of actual power system proves the availability of the developed expert system.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.399-412
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• 1996

With respect to the effects of types of knowledge on human diagnostic performance, the results of several experiments claimed that training with procedural knowledge is more effective than training with principle knowledge. However, more useful results would be attained by investigating when and how the principles of system dynamics is valuable for diagnosis. Accordingly, we conducted an experiment to reevaluate the value of principle knowledge in two problem situations. A simulator system, named DLD, to diagnose an electronic device was created. It is a context-free digital logic circuit which includes forty-one gates of three basic types. The experiment investigated the effects of principle knowledge over common procedural knowledge. The experimental results showed that the effects of principle knowledge is dependent on the complexity of diagnostic situations. This adds up on experimental evidence against the presumed ineffectiveness of principle knowledge and forward reasoning in fault diagnosis. The results also suggest the source of the usefulness of principle knowledge.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.387-394
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• 1995

With respect to the effectiveness of types of knowledge on human diagnostic performance, the results of several experiments claimed that training with diagnostic rules (procedural knowledge) is more effective than training that provides theoretical knowledge (principle knowledge). However, we usually have the idea that understanding the principles of system dynamics is necessary for diagnosis in some situations. In this study, we pointed out some problems in the previous experiments that force to reinterpret their experimental conclusions. Accordingly, we conducted an experiment to reinvestigate the value of theoretical knowledge in two problem situations. A simulator system, which is named DLD, that is to diagnose an electronic device was created for this purpose. It is a context-free digital logic circuit which includes forty-one gates of three basic types. Our experiment investigated the marginal effects of theoretical knowledge over common diagnostic rules. The experimental results showed that the effectiveness of the instruction in theoretical knowledge is dependent on the complexity of diagnostic situations. This adds up an experimental evidence against the presumed ineffectiveness of theoretical knowledge and forward reasoning in fault diagnosis. Furthermore, the result suggests the source of the use of theoretical knowledge.

• The Korean Journal of Health Service Management
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• v.7 no.4
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• pp.49-63
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• 2013

This study attempted to examine what effect knowledge management factors have on cooperative organizational culture regarding knowledge sharing depending on workplace types and occupations in order to seek for solution to increase efficiency and effects of knowledge management in the hospital organization. Key findings are as follows: For members of the hospital organization, the higher their recognition was in relation to 'concern and support of chief executive officer for knowledge management', and 'problem solution by specialists or superior in the organization and acquisition on the task knowledge', the more they worked as factors exerting positive effects on 'cooperative organizational culture regarding knowledge sharing'. And influence factors were different depending on workplace types and occupation.

• Journal of Korean Elementary Science Education
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• v.38 no.3
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• pp.395-405
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• 2019

The purpose of this study is to analyze the process of creative science problem solving (CSPS) in elementary school students. To do this, 6 graders (n=9) at a elementary school in Seoul were participated. In this study, fixed eye-tracker with 250 Hz sampling and observation camera were used. The results of this study, the students with higher ability to solve creative science problems had a slower saccade, and had more visual attention on core clues and a greater number of eye changes. Therefore, students with higher ability to solve creative science problems showed more effective eye movement and faster information processing to solve problems. The CSPS types of elementary students were classified as 'declarative knowledge type', 'procedural knowledge type', 'conditional knowledge type', 'knowledge lack type'. Because each type appears to be complementary, CSPS process for elementary students who have integrated the four types was devised. The results of this study can be used as basic data for understanding elementary school students' CSPS and will help to develop and guide creative science teaching and learning programs useful to elementary school students and science gifted students.

• Journal of The Korean Association For Science Education
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• v.24 no.1
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• pp.146-156
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• 2004

The purpose of this study is to look at the use of heuristics when a sixth grader solves a problem. Two research questions have been formulated: The similarities and differences in the use of heuristics when a student solves two problems that are science-knowledge-based and not science-knowledge-based, and the different types of prompts. A male sixth grade student participated in this study. All of the information for the study was collected in three interviews. The interviews began with observing the student's solving problems. The student was asked how and why he solved problem that way. There were some interactions between the researcher and the student during the interview procedures. As results of this study, eight general heuristics were used in both solutions: Check examples for support of an idea: check examples for exceptions to an idea: restate the problem: compare to known examples or patterns: make a hypothesis; check the relevance of other information present; use analogy: and recognize patterns/similarity. There seemed to be more similarities than differences in the type of general heuristic that were used in the two problem solutions. The student was systematic and consistent in his use of the general use of heuristics. Five types of interviewer prompts were detected in the two problem solutions, directional cues, modeling, clarity, problem posing, metacognition and validation.