• East Asian mathematical journal
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• v.31 no.2
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• pp.145-165
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• 2015

The purpose of this study is to suggest how to go about teaching and learning secondary school algebra by analyzing problem-solving ability and problem-solving process through algebraic reasoning. In doing this, 393 students' data were thoroughly analyzed after setting up the exam questions and analytic standards. As with the test conducted with technical school students, the students scored low achievement in the algebraic reasoning test and even worse the majority tried to answer the questions by substituting arbitrary numbers. The students with high problem-solving abilities tended to utilize conceptual strategies as well as procedural strategies, whereas those with low problem-solving abilities were more keen on utilizing procedural strategies. All the subject groups mentioned above frequently utilized equations in solving the questions, and when that utilization failed they were left with the unanswered questions. When solving algebraic reasoning questions, students need to be guided to utilize both strategies based on the questions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.271-274
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• 1996

Since the primary purpose of information Engineering focuses on transaction or operation processing, various information needs acquired in Information Strategy Planning phase are not properly utilized from the viewpoint of decision support systems development. In this research, we suggest a case-based reasoning application that supports initial Data Warehouse Modeling by expanding the activities in Information Strategy Planning.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.35-38
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• 1996

It's a rather difficult for new product launch strategy establishment to be settled down because we must know the correlation between the quantitative and the qualitative information. Therefore, we introduce you case-based reasoning system that use its correlation and new product launch's experience in the past. Using the real cases, this system evaluates the performance as we compare human expert's new product sales forecasting with system's.

• Journal of The Korean Association For Science Education
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• v.31 no.4
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• pp.587-599
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• 2011

The purpose of this study was to analyze variable-controlling strategy (below vcs) and the ability to infer the effect of variables in Middle school students who experienced 'Thinking Science' activities in a CASE program. For this study, 71 9th grade students experienced in CASE program for 2 years were selected as the experimental group and 72 students were selected as the control group. All students were tested with Science Reasoning TaskVII. The five types of variable-controlling strategy were extracted from students' response. According to the result of this study, the students experienced in CASE program was more successful in the variable-controlling strategy of length, quality, and shape than the control group. The types of reasoning ability of the variable effect intuitively were categorized as possibility of reasoning, impossibility of reasoning, and impossibility of reversible thinking. It has shown that the reasoning ability of the experimental group was higher than that of the control group in the length and thickness variable effect. The results of this study implied that the variable controlling activities in CASE program could be effective for learning variable controlling, and eventually, for the development of reasoning ability of the variable controlling effect. In the ability to infer the effects of variables to get difficult Intuitively, both groups were similar to the rate of cognitive level reached to the formal operation in generalization, and the student of experimental group was 1.5 times faster than the control group.

• Journal of Educational Research in Mathematics
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• v.19 no.1
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• pp.81-98
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• 2009

This study analyzed the types of quantitative reasoning and the characteristics of representation in order to figure out the characteristics of quantitative reasoning of the sixth graders. Three students who used quantitative reasoning in solving problems were interviewed in depth. Results showed that the three students used two types of quantitative reasoning, that is difference reasoning and multiplicative reasoning. They used qualitatively different quantitative reasoning, which had a great impact on their problem-solving strategy. Students used symbolic, linguistic and visual representations. Particularly, they used visual representations to represent quantities and relations between quantities included in the problem situation, and to deduce a new relation between quantities. This result implies that visual representation plays a prominent role in quantitative reasoning. This paper included several implications on quantitative reasoning and quantitative approach related to early algebra education.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.189-196
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• 2001

Fuzzy logic ignores some information in the reasoning process. Neural networks are powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule - inference network. and the traditional propagation rule is modified.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2000.11a
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• pp.375-389
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• 2000

Fuzzy logic ignores some information in the reasoning process. Neural networks are powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule- inference. network. And the traditional propagation rule is modified. For the search strategies to find out the belief value of a conclusion in the fuzzy inference network, we conduct a simulation to evaluate the search costs for searching sequentially and searching by means of search priorities.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.83-90
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• 2004

Strategic games are missing special qualities of genre these days. Game engines neither reason about behaviors of computer objects nor have learning ability that can prepare countermeasure in variously command user's strategy. This paper suggests a strategic game engine that applies non-monotonic reasoning and inductive machine learning. The engine emphasizes three components -“user behavior monitor”to abstract user's objects behavior,“learning engine”to learn user's strategy,“behavior display handler”to reflect abstracted behavior of computer objects on game. Especially, this paper proposes two layered-structure to apply non-monotonic reasoning and inductive learning to make behaviors of computer objects that learns strategy behaviors of user objects exactly, and corresponds in user's objects. The engine decides actions and strategies of computer objects with created information through inductive learning. Main contribution of this paper is that computer objects command excellent strategies and reveal differentiation with behavior of existing computer objects to apply non-monotonic reasoning and inductive machine learning.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1025-1034
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• 1997

Inference process of resolution-based automated reasoning easily consumes the memory of computer without giving any useful result by priducing lots of fruioless information which are not necessary for the conslusion. This paper suggests a control strategy for saving the space of computer memory and reducing the inference time. The strategy uses a restriction that comparatively irrelevant axioms do mot take pare in the resoluition. In order to analyze and determine the priorities of the input axioms of joning the inference process, the system employs the fuzzy relational products.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2050-2060
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• 1998

Weighting strategy is one of the necessary control strategies in automated reasoning to solve problecs within allowable time and computer memory. But, the strategy still consumes too much time since it depends soly on the user's experience and needs much of the user's manual work at each stage. This research suggests a tool which automates the weighting system to generate the weighting thesaurus and merges it to the mechanical theorem prover.