• Journal of Digital Convergence
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• v.12 no.6
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• pp.69-77
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• 2014

System Dynamics(SD) is one of the complexity theories that has attracted attention as a computer-aided simulation methodology to analyze a dynamic problem and to develop a policy(strategy) in social science. Though there are properly unproven cases in research models which were developed in various fields by SD methodology during the last five decades, they are utilized as models to represent SD sub-theories. For this reason, this study targeted the population dynamics model which was frequently utilized to explain SD fundamentals and it proved errors of reasoning a structure of the existing causal and dominant feedback loop. Consequently, we presented a strategy to strengthen the coherence between CLD(causal loop diagram) and SFD(stocks-and-flows diagram) for improving validity of the existing model. The findings of this study contribute to the advancement of the existing SD and to the reinforcement of validation for policy research models of SD.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.39-48
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• 2014

Good and bad luck is an important factor that frequently affects human information processing. However, in spite of its significance, few studies have been done to examine how good and bad luck influences information processing and reasoning. The current research was performed to explore the effect of good and bad luck on reasoning and, for this, two experiments were conducted. In experiment 1, participants were primed with good or bad luck and were asked to make an inference for a given murder case and include as many as clues for it, while in experiment 2, participants were asked to exclude as many as clues for the same murder case. Results show that, in experiment 1, participants who were primed with good luck included more clues than those who were primed with bad luck. However, in Experiment 2, it was found that participants who were primed with bad luck excluded more clues than those who were primed with good luck. Findings from this study indicate that priming good luck enhances holistic thinking which leads to including more and excluding less clues whereas priming bad luck increases analytic thinking which leads to including less and excluding more clues. Implications of this study for inference and decision making, consumer behavior, and addict psychology are discussed.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.16 no.4
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• pp.459-471
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• 2009

Introduction: Critical thinking involves identifying problem(s), assessing resources, and generating possible solutions and allows clinical nurses to decide which solution is the most reasonable under the given circumstances, taking into consideration the "hat ifs" and how they will affect the end result. This research was conducted to further understanding and identification of subjective factors in critical thinking in clinical nurses. Methods: The research design was a Q-Methodological Approach. Q-population was formulated from a non-structured questionnaire and interviews from 17 experienced clinical nurses. Thirty selected Q-statements were sorted by 30 experienced clinical nurses. Results: Four factors for critical thinking were identified: (1) Deductive reasoning based on causal relation, (2) Construction of an effective model based on patients' responses, (3) Formulating categories based on priorities for effective interventions, and (4) Judging validity of the situational significance on clinical performances. Conclusion: Critical thinking is an attitude and reasoning process. From this study, the frame of reference for clinical nurses in formulating critical thinking within the context of clinical settings is identified and indicates the way nurses utilize thinking skills when they care for patients and areas that need further exploration as nurses and faculty develop education systems to advance clinical performance competency.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.29-40
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• 2000

Process planning (selection and ordering of processes) and material selection for product manufacturing are two key things determined before taking full-scale manufacturing. Knowledge on product design. material characteristics, processes, time and cost all-together are mutually related and should be considered concurrently. Due to the complexity of problem, human experts have got only one of the feasilbe solutions with their field knowledge and experiences. We propose a hierarchical expert system framework of knowledge representation and reasoning in order to overcome the complexity. Manufacturing processes have inherently hierarchical relationships, from top level processes to bottom level operation processes. Process plan of one level is posted in process blackboard and used for lower level process planning. Process information on blackboard is also used to adjust the process plan in order to resolve the dead-end or inconsistency situation during reasoning. Decision variables for process, material, tool, time and cost are represented as object frames, and their relationships are represented as constraints and rules. Constraints are for relationship among variables such as compatibility, numerical inequality etc. Rules are for causal relationships among variables to reflect human expert\`s knowledge such as process precedence. CRSP(Constraint and Rule Satisfaction Problem) approach is adopted in order to obtain solution to satisfy both constraints and rules. The trade-off procedure gives user chances to see the impact of change of important variables such as material, cost, time and helps to determine the preferred solution. We developed the prototype system using visual C++ MFC, UNIK, and UNlK-CRSP on PC.

• Journal of The Korean Association For Science Education
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• v.26 no.3
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• pp.356-366
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• 2006

The purpose of this study was to investigate the effects of offering similar experiences for hypothesis-generation based on abduction. Two hundred and seventy eight students in Seoul(8th and 10th grades) were requested to propose causal questions and generate hypotheses after observing an unfamiliar situation. Then, after having been presented numerous similar experimental situations to initial situation, the students were asked to regenerate a hypothesis. When the $X^2$ analysis was done to determine differences in hypothesis generation before and after offering the similar experimental situations, a meaningful difference appeared(p<.001). This study proposes that offering similar experimental situations ease hypothesis-generation based on abductive reasoning. Additionally, the second meaningful difference was discovered when the $X^2$ analysis was carried out to find differences in causal question proposal and hypothesis generation among students who had varied cognitive levels(p<.05) Considering the findings of the study, a progressive stage offering similar scenarios may further abductive reasoning while implementing lessons related to hypothesis generation in middle and high school.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.1-9
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• 2008

Fuzzy Cognitive Map, one of ways to model, describe and infer reasoning relations, is widely used in the field of reasoning knowledge engineering. Despite of the natural and easy understanding of decision and smooth explanation of relation between front and rear, reasoning relation is organized with mathematical haziness and complex algorithm and rarely has an interactive user interface. This paper suggests an interactive Fuzzy Cognitive Map(FCM) construction support system. It builds a FCM increasingly concerning multiple experts' knowledge. Futhermore, it supports user-supportive environment by dynamically displaying the structure of Fuzzy Cognitive Map which is constructed by the interaction between experts and the system.

• Journal of The Korean Association For Science Education
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• v.23 no.5
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• pp.458-469
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• 2003

Hypothesis is defined as a proposition intended as a possible explanation for an observed phenomenon. The purpose of this study was to generate a grounded theory on the process of undergraduate students' generating hypothesis-knowledge about scientific episodes. Three hypothesis-generating tasks were administered to four college students majored in science education. The present study showed that college students represented five types of intermediate knowledge in the process of hypothesis generation, such as question situation, hypothetical explicans, experienced situation, causal explicans, and final hypothetical knowledge. Furthermore, students used six types of thinking methods, such as searching knowledges, comparing a question situation and an experienced situation, borrowing explicans, combining explicans, selecting an explican, and confirming explicans. In addition, hypothesis-generating process involves inductive and deductive reasoning as well as abductive reasoning. This study also discusses the implications of these findings for teaching and evaluating in science education.

• Journal of The Korean Association For Science Education
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• v.26 no.4
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• pp.546-558
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• 2006

The purpose of this study was to identify heuristically how abduction was used in a context of solving an earth-environmental problem. Thirty two groups of participants with different institutional backgrounds, i,e., inservice earth science teachers, preservice science teachers, and high school students, solved an open-ended earth-environmental problem and produced group texts in which their ways of solving the problem were written, The inferential processes in the texts were rearranged according to the syllogistic form of abduction and then analyzed iteratively so as to find thinking strategies used in the abductive reasoning. The result showed that abduction was employed in the process of solving the earth-environmental problem and that several thinking strategies were used for inferring rules from which abductive conclusions were drawn. The strategies found included data reconstruction, chained abduction, adapting novel information, model construction and manipulation, causal combination, elimination, case-based analogy, and existential strategy. It was suggested that abductive problems could be used to enhance students' thinking abilities and their understanding of the nature of earth science and earth-environmental problems.

• Journal of The Korean Association For Science Education
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• v.25 no.2
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• pp.111-121
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• 2005

The purpose of this study was to analyze characteristics of experimental design and evidence choice of the elementary school students in problem solving process related to controlling variable. For this study, 96 6th grade students were selected and tested with Science Reasoning Task. This study revealed that the types of experimental design were categorized as variance of control variable, controlling of causal variable, perfect controlling variable, imperfect controlling variable, variance of all variable. Prior belief had a strong influence on student's experimental design. The types of evidence choice were categorized as perfect controlling variable, controlling causal variable, variance of causal variable. The degree of controlling variable in evidence choice process was much lower than that in experimental design. Most students tended to choose evidence according to prior belief without controlling variable. The results of this study implied that student's prior belief and characteristic of science process skills should be considered to develop program for promoting controlling variable ability.

• Journal of KIISE:Software and Applications
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• v.27 no.2
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• pp.120-133
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• 2000

Major obstruction of using formal methods for hybrid real-time systems in industry is the difficulty that engineers have in understanding and applying the quantitative methods in an abstract requirements phase. While formal methods technology in safety-critical systems can help increase confidence of software, difficulty and complexity in using them can cause another hazard. In order to overcome this obstruction, we propose a framework for qualitative requirements engineering of the hybrid real-time systems. It consists of a qualitative method for requirements specification, called QFM (Qualitative Formal Method), and a safety analysis method for the requirements based on a causality information, called CRSA (Causal Requirements Safety Analysis). QFM emphasizes the idea of a causal and qualitative reasoning in formal methods to reduce the cognitive burden of designers when specifying and validating the software requirements of hybrid safety systems. CRSA can evaluate the logical contribution of the software elements to the physical hazard of systems by utilizing the causality information that is kept during specification by QFM. Using the Shutdown System 2 of Wolsong nuclear power plants as a realistic example, we demonstrate the effectiveness of our approach.