• Journal of The Korean Association For Science Education
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• v.30 no.8
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• pp.1044-1059
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• 2010

In this study, we investigated the influences of the method of using analogy on concept understanding, mapping understanding, and mapping error by analogical reasoning ability level. We also investigated students' perception of a role-playing analogy activity. Seventh graders (N=152) at a middle school were assigned to the comparison and the experimental groups. The students of the experimental group were taught about 'the relation between pressure and volume of gas' with experience-based role-playing analogy, while those of the comparison group were taught with explanation-centered analogy. Analyses of the results revealed that the instruction using roleplaying analogy was more effective in concept understanding and retention of mapping understanding than explanation-centered analogy instruction, regardless of analogical reasoning ability level. It was also found that the students of the experimental group had fewer mapping errors than those of the comparison group. However, there was little difference in t pes of mapping errors by the method of using analogy. The students of the experimental group answered that they did not have difficulties in performing the role-playing analogy activity and they actively engaged in the activity. They perceived that the role-playing analogy activity was interesting. Educational implication of these findings are discussed.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.329-347
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• 2017

Early research into category-based feature inference reported various phenomena in human thinking including typicality, diversity, similarity effects, etc. Later research discovered that participants' prior knowledge has an extensive influence on these sorts of reasoning. The current research tested the effects of causal knowledge on feature inference and conducted modeling on the results. Participants performed feature inference for categories consisted of four features where the features were connected either in common cause or common effect structure. The results showed typicality effects along with violations of causal Markov condition in common cause structure and causal discounting in common effect structure. To model the results, it was assumed that participants perform feature inference based on the difference between the probabilities of an exemplar with the target feature and an exemplar without the target feature (that is, $p(E_{F(X)}{\mid}Cat)-p(E_{F({\sim}X)}{\mid}Cat)$). Exemplar probabilities were computed based on causal model theory (Rehder, 2003) and applied to inference for target features. The results showed that the model predicts not only typicality effects but also violations of causal Markov condition and causal discounting observed in participants' data.

• Communications of Mathematical Education
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• v.23 no.1
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• pp.145-174
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• 2009

Based on the thinking that people can understand more clearly when the problem is related with their prior knowledge, the Purpose of this study was to analysis students' informal knowledge, which is constructed through their mathematical experience in the context of real-world situations. According to this purpose, the following research questions were. 1) What is the characteristics of students' informal knowledge about fraction before formal fraction instruction in school? 2) What is the difference of informal knowledge of fraction according to reasoning ability and grade. To investigate these questions, 18 children of first, second and third grade(6 children per each grade) in C elementary school were selected. Among the various concept of fraction, part-whole fraction, quotient fraction, ratio fraction and measure fraction were selected for the interview. I recorded the interview on digital camera, drew up a protocol about interview contents, and analyzed and discussed them after numbering and comment. The conclusions are as follows: First, students already constructed informal knowledge before they learned formal knowledge about fraction. Among students' informal knowledge they knew correct concepts based on formal knowledge, but they also have ideas that would lead to misconceptions. Second, the informal knowledge constructed by children were different according to grade. This is because the informal knowledge is influenced by various experience on learning and everyday life. And the students having higher reasoning ability represented higher levels of knowledge. Third, because children are using informal knowledge from everyday life to learn formal knowledge, we should use these informal knowledge to instruct more efficiently.

• Journal of the Korean Society of Earth Science Education
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• v.11 no.3
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• pp.224-236
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• 2018

The purpose of this study was to develop a reasoning-based HTE-STEAM program for the development of the cognitive capacity of middle school students and enhancement of their STEAM literacy, and to investigate the effectiveness of this study in the school setting. The subjects of this study were the students of two middle schools located in the central region of Korea. The students participated in the HTE-STEAM program during their free-learning semesters and 202 of them were selected by random sampling method. Main findings were as follows: First, pre- and post-HTE-STEAM program has shown a significant value in statistical verification (p<.05) and the level of logical thinking ability of the research participants improved after the class compared to before the class. Second, the paired samples t-test comparing the difference between the pre and post scores of the STEAM attitude test has shown a significant value in statistical verification (p<.05), and the HTE-STEAM program has turned out to have a positive effect on the STEAM literacy of the research participants. Third, in the HTE-STEAM satisfaction scale test, the mean value of the sub-construct stood at 3.27~4.12, showing a positive overall response. Therefore, the HTE-STEAM program under the topic of earth science of 'Disaster and Safety' developed at the final stage of this study has proven to have a positive influence on the research participants in terms of the development of cognitive capacity by reasoning and collaborative learning, an important quality of communication and consideration necessary for STEAM literacy.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.2
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• pp.21-30
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• 2000

If there exists a model that calculates the proper candidate position whenever the game of Go is in progress, it can be used for setting up the prototype of the candidate generation algorithm without using case-based reasoning. In this paper, we analyze Go through combinatorial game theory and on the basis of probability matrix (PM) showing the difference of the territory of the black and the white. We design and implement a candidate generation system(CGS) to find the candidates at a situation in Go. CGS designed in this paper can compute Influence power, safety, probability value(PV), and PM and then generate candidate positions for a present scene, once a stone is played at a scene. The basic strategy generates five candidates for the Present scene, and then chooses one with the highest PV. CGS generates the candidate which emphasizes more defence tactics than attack ones. In the opening game of computer Go, we can know that CGS which has no pattern is somewhat superior to NEMESIS which has the Joseki pattern.

• Journal of the Korean Chemical Society
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• v.55 no.3
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• pp.519-528
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• 2011

The main purpose of this study was to develop a teaching program, especially designed to improve the skills of control variables. The secondary purpose was to investigate the effect of the program on enhancing students' scientific reasoning and understanding. The program was designed based on the 3-step learning model: i.e. students recognize the necessity of controlling the variables (step 1), perform their own experiments (step 2), and reflect on their variables control process (step 3). The program included 9 topics of increasing difficulty. In results, Lawson's SRT scores increased in both experimental and control groups after application of the program, but the difference was not statistically significant. After the application, there was an increase in type A and type B which implied that students' skills of control variables was improved. In addition, responses of students in the experimental group to the open-ended items showed that it was challenging for them to think scientifically and critically when controling variables, but they ended up feeling proud of their achievement after the program.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.644-653
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• 1998

In resistance spot weld, the assurance of weld quality has been a long-standing problem. Since the weld nuggets if resustance spot welding form between the workpieces, visual detection of defects in usually impossible. Welding quality of resistance spot welding can be verified by non destructive and destructive inspections such as X-Ray inspection and testing of weld strength. But these tests, in addition to being time-consuming and costly, can entail risks due to sampling basis. The purpose of this study is the development of the monitoring system based on fuzzy inference, aimed at diagonosis of quality in resistance spot welding. The fuzzy inference system consists of fuzzy input variables, fuzzy membership functions and fuzzy rules. For inferring the welding quality(strength), the experimental data of the spot welding were acquired in various welding conditions with the monitoring system designed. Some fuzzy input variables-maximum, slop and difference values of electrode movement signals-were extracted from the experimental data. It was confirmed that the fuzzy inference values of strength have a .${\pm}$5% error in comparison with actual values for the selected welding conditions(9-10.5KA, 10-14 cycle, 250-300 $kg_f$). This monitoring system can be useful in improving the quality assurance and reliability of the resistance spot welding process.

• Journal of The Korean Association For Science Education
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• v.22 no.1
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• pp.1-11
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• 2002

This study was analyzing what studying factors are affecting on the development of science process skills of the 5th graders in the elementary school. For this research, 2 hundreds of elementary students were chosen and questioned on 3 factors like teacher, school environment, and learning strategy which are supposed to affect the development of science process skills. According to the result, there were differences in the categories according to the region. Especially, science process skills were significantly different in level of school category(p<.05)). Science process skills were significantly correlated with teachers and school category, and learning environment in 5th grade. Based on these results, it is expected to perform analysis about the influences that studying variables have on science achievement and attitude as well as scientific reasoning ability. Also, further study is needed about the influence that these small difference have on middle and high school students, though studying variables are not statistically significant on this research.

• The Mathematical Education
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• v.56 no.3
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• pp.281-300
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• 2017

This study analyzed the difficulties of middle school students in computer simulation of the law of large numbers through eye movement analysis. Some students did not attend to the simulation results and could not make meaningful inferences. It is observed that students keep the existing concept even though they observe the simulation results which are inconsistent with the misconceptions they have. Since probabilistic intuition influence student's thinking very strongly, it is necessary to design a task that allows students to clearly recognize the difference between their erroneous intuitions and simulation results. In addition, we could confirm through eye movements analysis that students could not make meaningful observations and inferences if too much reasoning was needed even though the simulation included a rich context. It is necessary to use visual representations such as graphs to provide immediate feedback to students, to encourage students to attend to the results in a certain intentional way to discover the underlying mathematical structure rather than simply presenting experimental data. Some students focused their attention on the visually salient feature of the experimental results and have made incorrect conclusion. The simulation should be designed so that the patterns of the experimental results that the student must discover are not visually distorted and allow the students to perform a sufficient number of simulations. Based on the results of this study, we suggested that cumulative relative frequency graph showing multiple results at the same time, and the term 'generally tends to get closer' should be used in learning of the law of large numbers. In addition, it was confirmed that eye-tracking method is a useful tool for analyzing interaction in technology-based probabilistic learning.