• School Mathematics
• /
• v.15 no.4
• /
• pp.785-799
• /
• 2013

The researchers developed the teaching-learning materials for 9th grade mathematically gifted students in terms of the hypothesis that the students would have opportunity for problem solving and develop various mathematical thinking through the mathematical modeling lessons. The researchers analyzed what mathematical thinking abilities were shown on each stage of modeling process through the application of the materials. Organization of information ability appears in the real-world exploratory stage. Intuition insight ability, spatialization/visualization ability, mathematical reasoning ability and reflective thinking ability appears in the pre-mathematical model development stage. Mathematical abstraction ability, spatialization/visualization ability, mathematical reasoning ability and reflective thinking ability appears in the mathematical model development stage. Generalization and application ability and reflective thinking ability appears in the model application stage. The developed modeling assignments have provided the opportunities for mathematically-gifted students' mathematical thinking ability to develop and expand.

• Journal of Gifted/Talented Education
• /
• v.8 no.2
• /
• pp.69-89
• /
• 1998

The purpose of this study is to develop a test which can be used in identification of the gifted students in the area of mathematics. This study was carried out for two years from 1996. Mathematical giftedness is, in this study, regarded as a result of interaction of mathematical thinking ability, mathematical creativity, mathematical task committment, background knowledge. This study presumed that mathematical thinking ability is composed of seven thinking abilities: intuitive insights, ability for information organization, ability for visualization, ability for mathematical abstraction, inferential thinking ability(both inductive and deductive thinking abilities), generalization and application ability, and reflective thinking. This study also presupposed that mathematical creativity is composed of 3 characteristics: fluency, flexibility, originality. The test for mathematical creative problem solving ability was developed for primary, middle, and high school students. The test is composed of two parts: the first part is concentrated more on divergent thinking, while the second part is more on convergent thinking. The major targets of the test were the students whose achievement level in mathematics belong to top 15~20% in each school. The goodness of the test was examined in the aspects of reliability, validity, difficulty, and discrimination power. Cronbach $\alpha$ was in the range of .60~.75, suggesting that the test is fairly reliable. The validity of the test was examined through the correlation among the test results for mathematical creative problem solving ability, I. Q., and academic achievement scores in mathematics and through the correlation between the scores in the first part and the scores in the second part of the test for mathematical creative problem solving ability. The test was found to be very difficult for the subjects. However, the discrimination power of the test was at the acceptable level.

• Journal of Educational Research in Mathematics
• /
• v.17 no.2
• /
• pp.163-177
• /
• 2007

Studies on mathematically gifted students have been conducted following Krutetskii. There still exists a necessity for a more detailed research on how these students' mathematical competence is actually displayed during the problem solving process. In this study, it was attempted to analyse the algebraic thinking process in the problem solving a peg puzzle in which 4 mathematically gifted students, who belong to the upper 0.01% group in their grade of elementary school in Korea. They solved and generalized the straight line peg puzzle. Mathematically gifted elementary school students had the tendency to find a general structure using generic examples rather than find inductive rules. They did not have difficulty in expressing their thoughts in letter expressions and in expressing their answers in written language; and though they could estimate general patterns while performing generalization of two factors, it was revealed that not all of them can solve the general formula of two factors. In addition, in the process of discovering a general pattern, it was confirmed that they prefer using diagrams to manipulating concrete objects or using tables. But as to whether or not they verify their generalization results using generalized concrete cases, individual difference was found. From this fact it was confirmed that repeated experiments, on the relationship between a child's generalization ability and his/her behavioral pattern that verifies his/her generalization result through application to a concrete case, are necessary.

• Research in Mathematical Education
• /
• v.10 no.1 s.25
• /
• pp.55-70
• /
• 2006

The purpose of this study was to develop math creative problem solving test in order to identify the mathematically gifted on the basis of their math creative problem solving ability and evaluate the goodness of the test in terms of its reliability and validity of measuring creativity in math problem solving on the basis of fluency in producing valid solutions. Ten open math problems were developed requiring math thinking abilities such as intuitive insight, organization of information, inductive and deductive reasoning, generalization and application, and reflective thinking. The 10 open math test items were administered to 2,029 Grade 5 students who were recommended by their teachers as candidates for gifted education programs. Fluency, the number of valid solutions, in each problem was scored by math teachers. Their responses were analyzed by BIGSTEPTS based on Rasch's 1-parameter item-response model. The item analyses revealed that the problems were good in reliability, validity, difficulty, and discrimination power even when creativity was scored with the single criteria of fluency. This also confirmed that the open problems which are less-defined, less-structured and non-entrenched were good in measuring math creativity of the candidates for math gifted education programs. In addition, it discriminated applicants for two different gifted educational institutions and between male and female students as well.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.10a
• /
• pp.323-335
• /
• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.11a
• /
• pp.401-406
• /
• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine(SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel(KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2006.11a
• /
• pp.46-53
• /
• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine (SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel (KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.

• Phonetics and Speech Sciences
• /
• v.13 no.2
• /
• pp.77-90
• /
• 2021

This study is to develop a Korean version of nonword intervention by modifying and supplementing a Rapid syllable transition treatment (ReST) and to determine its effect by applying it to children with CAS. Ultimately, the purpose of this study is to investigate whether nonword interventions are effective for nonword production ability and generalization of real words. Single-subject research using the ABA design was performed for a child aged five years and six months with diagnostic features of CAS. The nonwords used in the interventions were made suitable for the individual child. The intervention was provided in one-hour sessions, twice a week for six weeks. In all cases, performance of the treated three-syllable nonwords improved, and untreated three-syllable words, four-syllable words, and nonwords showed a generalization effect. However, the generalization of treatment effects to words was smaller than for nonwords. The nonword intervention was effective in improving the subject's speech motor programming skills. As a result, transition errors due to impaired speech motor programming were greatly reduced, and the ability to produce untreated nonwords was greatly increased. However, there was a limit to the full improvement of strongly habitable word errors, which would be expected if a more intensive and repetitive intervention schedule was provided.

• Communications of Mathematical Education
• /
• v.25 no.1
• /
• pp.245-259
• /
• 2011

In this study, the instrument of mathematical creative problem solving ability test were considered the differences between Korean and American sixth grade students in mathematical creativity ability and mathematical thinking ability. The instrument consists of 9 items. The participants for the study were 212 Korean and 148 American students. SPSS were carried out to verify the validities and reliability. Reliabilities(Cronbach ${\alpha}$) in mathematical creativity ability is 0.9047 and in mathematical thinking ability is 0.9299 which were satisfied internal validity evaluation on the test items. Internal validity were analyzed by BIGSTEPS based on Rasch's 1-parameter item response model. The results of this study can serve as a foundation for understanding the Korean and American students differences in mathematical creativity ability and mathematical thinking ability. Especially we get the some informations on mathematical creativity ability for American's fifth grade to seventh grade students.

• The KSFM Journal of Fluid Machinery
• /
• v.3 no.3 s.8
• /
• pp.19-24
• /
• 2000

It is well known that the finite element analysis often has an inaccuracy when it is in conflict with test results. Model updating is concerned with the correction of analytical model by processing records of response from test results. The famous one of the model updating methods is FRF sensitivity method. However, it has demerit that the solution is not unique. So, the neural network is recommended when an unique and exact solution is desired. The generalization ability of radial basis function neural network is used in model updating. As an application model, a cantilever and a rotor system are used. Specially the machined clearance($C_p$) of a journal bearing is updated.