• East Asian mathematical journal
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• v.35 no.4
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• pp.407-427
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• 2019

The six core competencies included in the mathematics curriculum revised in 2015 are problem solving, reasoning, communication, attitude and practice, creativity and convergence, information processing. In particular, the problem solving is very important for students' enhancing much higher mathematical thinking. Based on this competency, this study selected the four elements of the problem solving such as problem solving process, cooperative problem solving, mathematical modeling, problem posing. And also this study selected the domain of function which is comprised of the content of the coordinate plane, the graph, proportionality in the seventh grade mathematics textbook. By the subject of the ten kinds of textbook, this study examined how the four elements of the problem solving competency were shown in each textbook.

• Korean Institute of Interior Design Journal
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• v.16 no.2 s.61
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• pp.63-70
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• 2007

Analogy in problem solving is similarity-based reasoning facilitated by verbal and visual operation. This similarity-based reasoning generally supports initial phase of idea search. Therefore, this study intends to infer the types of problem solving by tracing the analogy use of verbal and visual representation through a experimental research. According to the result of this research, the types of problem solving by analogy are classified into 'evolving', 'divergent', and 'poor conversion' type. Firstly, 'evolving type' is distinguished between 'combination type' associated different contents to develope a new design and 'transformation type' associated similar words and sketches to be continuously revised and developed. In these types usually structural analogy rather than surface analogy is used. Secondly, in 'divergent type' associated words or sketches are individually represented, and among them one design solution is selected. In this type usually surface analogy is used. Thirdly, in 'poor conversion type' interaction between verbal representation and visual representation does not go on smoothly, and the generation of idea is poor. In here surface analogy is mostly used. These findings could form the basis of skill development of idea generation and conversion in design education.

• Journal of The Korean Association For Science Education
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• v.17 no.1
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• pp.75-83
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• 1997

The purpose of this study was to determine the strategies that middle school students used in solving problems concerning density and solubility. These were compared in the aspects of problem contexts for 42 students of varying logical reasoning ability, spatial ability, and learning approach. A coding scheme used consists of five categories: reading & organization, production, errors, evaluation, and strategy. Students' protocols were analyzed after intercoder agreement had been established to be .95. The results were as follows: 1. Students had more difficulties in reading and organizing the problems in everyday contexts than in scientific contexts. Students at the concrete-operational stage and / or surface approach were more likely to have difficulties in reading and organizing the problems than those at the formal-operational stage and / or deep approach. 2. Students tended to split up the solubility problems into sub-problems and to solve the density problem in everyday contexts in random manner. These were significantly correlated with the test scores concerning logical reasoning ability, spatial ability, and learning approach at the .1 level of significance. 3. Major errors in solving the density problems were to disregard the given information or generated and to use inappropriate information. Many errors in solving the solubility problems were found to be executive errors. The strategy to use the information given appropriately was positively related to students' logical reasoning ability, spatial ability, and learning approach. 4. More evaluation strategies were found in everyday contexts. Their strategies to grasp the meaning of answers and to check the math were significantly related to students' logical reasoning ability. 5. Students used the random trial-and-error strategy more than the systematic strategy and the systematic trial-and-error strategy, especially in everyday contexts. The strategies used by the students were significantly related to students' logical reasoning ability, spatial ability, and learning approach.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.201-204
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• 2003

A hybrid artificial intelligence approach based on combining case based reasoning and neural networks is presented. The approach is designed to allow for solving blowing control of BOF(basic oxygen furnace), example of which lie at the core of steelmaking process control systems application in the steel industry. According to this hybrid approach, the system, when faced with a new problem, first retrieves similar cases and neural network is used to solve the problem. Experimental Results indicate that combining case based reasoning and neural network offers an efficient approach to solving control and prediction problem

• Journal of Elementary Mathematics Education in Korea
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• v.18 no.2
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• pp.189-209
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• 2014

This study designed and developed a model of ill-structured problem solving and ill-structured problems for the 4th, 5th, and 6th graders. In addition, two sets of ill-structured problems has been explored to 23 4th graders, 33 5th graders, and 23 6th graders in elementary schools in order to investigate their problem solving, creative personality, and mathematical reasoning. The model of ill-structured problem solving was suggested ABCDE (Analyze-Browse-Create-DecisionMaking-Evaluate) model and analyzed participants' problem solving procedure. As results, participants showed improvement between pretest and posttest in problem solving and the high graders showed the greater creative personality.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.569-590
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• 2023

The purpose of this case study is to compare and analyze the covariational reasoning levels of two middle school students revealed in the process of solving and generalizing algebra word problems. A class was conducted with two middle school students who had not learned quadratic equations in school mathematics. During the retrospective analysis after the class was over, a noticeable difference between the two students was revealed in solving algebra word problems, including situations where speed changes. Accordingly, this study compared and analyzed the level of covariational reasoning revealed in the process of solving or generalizing algebra word problems including situations where speed is constant or changing, based on the theoretical framework proposed by Thompson & Carlson(2017). As a result, this study confirmed that students' covariational reasoning levels may be different even if the problem-solving methods and results of algebra word problems are similar, and the similarity of problem-solving revealed in the process of solving and generalizing algebra word problems was analyzed from a covariation perspective. This study suggests that in the teaching and learning algebra word problems, rather than focusing on finding solutions by quickly converting problem situations into equations, activities of finding changing quantities and representing the relationships between them in various ways.

• The Mathematical Education
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• v.48 no.2
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• pp.141-148
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• 2009

The article discusses roles of analysis in problem solving, especially the problem posing. The author shows the procedure of analysis like the presentation of the hypothesis, the reasoning for the necessary conditions and the sufficient condition. Finally the author suggests that the analysis should be reviewed in the school mathematics.

• Journal of Educational Research in Mathematics
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• v.22 no.3
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• pp.331-352
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• 2012

The purpose of the study is to verify what cognitive variables have significant effect on proportional problem solving. For this aim, the study classified proportional problem into well-structured, moderately-structured, ill-structured problem by the level of structuredness, then classified the cognitive variables as well into factual algorithm knowledge, conceptual knowledge, knowledge of problem type, quantity change recognition and meta-cognition(meta-regulation and meta-knowledge). Then, it verified what cognitive variables have significant effects on 6th graders' proportional problem solving abilities through multiple regression analysis technique. As a result of the analysis, different cognitive variables effect on solving proportional problem classified by the level of structuredness. Through the results, the study suggest how to teach and assess proportional reasoning and problem solving in elementary mathematics class.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.97-112
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• 2000

The basic idea of case-based reasoning is to solve a new problem using the previous problem-solving experiences. In this research we develop a case-based reasoning system for equipment malfunction diagnosis. We first divide the case base into clusters using the case-based clustering technique. Then we develop an appropriate case-based diagnostic system for each cluster. In other words for individual cluster a different case-based diagnostic system which uses different weights for attributes is developed. As a result multiple case-based reasoning system are operating to solve a diagnostic problem. In comparison to the performance of the single case-based reasoning system our system reduces the computation time by 50% and increases the accuracy by 5% point.