• Journal of Gifted/Talented Education
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• v.5 no.2
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• pp.1-15
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• 1995

The latest researchs show that students have their own preconceptions about scientific phenomena or theory before they learn about it in school. The preconceptions exert a great influence on the teaching and learning science. The purpose of this study is to find out the effect of intelligence and attitude to science on elementary school students were sampled from 4th and 6th grade. Data were obtained by IQ test and the questionnaires on scientific conception and attitude toward science. The result was analyzed by t-test, Correlation and ANOVA in the statistical packages SPSS/PC+. The major findings of this study are as follows : 1. The mean score of scientific conception of elementary school students was 12.89. The mean score of attitude to science was 247.29. The mean score of intelligence was 109.93. 2. The correlation coefficient between scientific conception and intelligence (r=.5098)was relatively high(p<.001). The correlation coefficient between attitude to science and scientific conception(r=.2364) was low(p<.001). 3. Significant difference on science conception was found among grade levels(p<.001). Significant difference on science conception was not found between sex (p>.05). 4. The subjects were divided into 4 groups by intelligence and attitude toward science. These 4 groups show the significant difference (p<.01) in the scientific conception. The groups of high of high intelligence showed high scientific conception.

• Journal of the Korea Society of Computer and Information
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• v.7 no.1
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• pp.174-183
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• 2002

In this paper a control chart pattern recognition methodology based on the back propagation algorithm and Multi layer perceptron, a neural computing theory, is presented. This pattern recognition algorithm, suitable for real time statistical process control. evaluates observations routinely collected for control charting to determine whether a Pattern, such as a cycle. trend or shift, which is exists in the data. This approach is promising because of its flexible training and high speed computation with low-end workstation. The artificial neural network methodology is developed utilizing the delta learning rule, sigmoid activation function with two hidden layers. In a computer integrated manufacturing environment, the operator need not routinely monitor the control chart but, rather, can be alerted to patterns by a computer signal generated by the proposed system.

• Journal of the Korea Computer Industry Society
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• v.2 no.12
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• pp.1581-1590
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• 2001

This paper asserted more developmental model of WSD(word sense disambiguation) than J. Hur(2000)'s WSD model. This model suggested an improved statistical homonym disambiguation Model based on Bayes Theory. This paper using semantic information(co-occurrence data) obtained from definitions of part of speech(POS) tagged UMRD-S(Ulsan university Machine Readable Dictionary(Semantic Tagged)). we extracted semantic features in the context as nouns, predicates and adverbs from the definitions in the korean dictionary. In this research, we make an experiment with the accuracy of WSD system about major nine homonym nouns and new seven homonym predicates supplementary. The inner experimental result showed average accuracy of 98.32% with regard to the most Nine homonym nouns and 99.53% for the Seven homonym predicates. An Addition, we save test on Korean Information Base and ETRI's POS tagged corpus. This external experimental result showed average accuracy of 84.42% with regard to the most Nine nouns over unsupervised learning sentences from Korean Information Base and ETRI Corpus, 70.81 ％ accuracy rate for the Seven predicates from Sejong Project phrase part tagging corpus (3.5 million phrases) too.

• Structural Engineering and Mechanics
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• v.84 no.2
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• pp.143-154
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• 2022

Corrosion of steel reinforcement is considered as the main cause of concrete structures deterioration, especially those under humid environmental conditions. Hence, fiber reinforced polymer (FRP) bars are being increasingly used as a replacement for conventional steel owing to their non-corrodible characteristics. However, predicting the shear strength of beams reinforced with FRP bars still challenging due to the lack of robust shear theory. Thus, this paper aims to develop an explicit data driven based model to predict the shear strength of FRP reinforced beams using multi-objective evolutionary polynomial regression analysis (MOGA-EPR) as data driven models learn the behavior from the input data without the need to employee a theory that aid the derivation, and thus they have an enhanced accuracy. This study also evaluates the accuracy of predictive models of shear strength of FRP reinforced concrete beams employed by different design codes by calculating and comparing the values of the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R²), and percentage of prediction within error range of ±20% (a20-index). Experimental database has been developed and employed in the model learning, validation, and accuracy examination. The statistical analysis illustrated the robustness of the developed model with MAE, RMSE, 𝜇, 𝜎, R², and a20-index of 14.6, 20.8, 1.05, 0.27, 0.85, and 0.61, respectively for training data and 10.4, 14.1, 0.98, 0.25, 0.94, and 0.60, respectively for validation data. Furthermore, the developed model achieved much better predictions than the standard predictive models as it scored lower MAE, RMSE, and 𝜎, and higher R² and a20-index. The new model can be used in future with confidence in optimized designs as its accuracy is higher than standard predictive models.

• The Korean Journal of Food And Nutrition
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• v.25 no.4
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• pp.999-1007
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• 2012

This study is to implement a model of CPC-mentoring program based on the mentoring theory and research environment analysis as well as to present the operation case of teaching and learning in colleges. Major research results should use the practical research methods utilizing the statistical program in order to verify the effectiveness of the program of CPC-mentoring program by comparing the before with the after of running the CPC-mentoring program of the research objects, comparison group (61 people) and experiment group (33 people). After running the CPC-mentoring program, whether there was a certification's acquisition or not of the comparison group and the experiment group, a statistically significant difference between the comparison group 34.3% (21) and the experiment group 72.7% (24), (p<0.05) was shown. The goal of the students participating in the CPC-mentoring program was to help one another in order to obtain certification. moreover, by engaging in mutually developing human relationship activities thru various methods, such as adaptation of college life, development of sociality, graduation, etc., good cooperative relationships with one another as well as further development of the relationship was formed. CPC-mentoring program is neither doing only people that want nor being effective for people only that want. A successful matching will naturally lead to all success since mentoring is human relationships is the misunderstanding. The role of a mentoring coordinator(professor) for the operation of a successful CPC-mentoring program and for the application method of detailed CPC-mentoring program was set. In addition, by considering the connectivity with the counseling guidance (shared and individual guidance) of students, which is the characterization direction of technical department of the college, it is expected to make a positive contribution if utilized in a multilateral manner.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.921-929
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• 2011

In Information age, the academic liberal art Computer education course set up goals for promoting computer literacy and for developing the ability to cope actively with in Information Society and for improving productivity and competition among nations. In this paper, we analyze on discovering of decisive property and satisfaction index to have a influence on computer education on university students. As a preprocessing method, the proposed method select optimum property using correlation feature selection of machine learning tool based on Java and then we use multiclass least square support vector machine based on statistical learning theory. After applying that compare with multiclass support vector machine and multiclass least square support vector machine, we can see the fact that the proposed method have a excellent result like multiclass support vector machine in analysis of the academic liberal art computer education satisfaction index data.

• Journal of Korean Clinical Nursing Research
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• v.18 no.1
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• pp.126-135
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• 2012

Purpose: This study was aimed to develop a simulation training program of an advanced cardiac life support (ACLS) based on the mastery learning model (Simulation-MLM), and evaluate the effects of the program on critical care nurses. Methods: As an experimental pre-post test with a non-equivalent control group, the study employed convenience sampling of 38 critical care nurses. The experimental group received the Simulation-MLM including a theoretical lecture, formative evaluation, and simulation training, whereas only a theoretical lecture for the control group. The knowledge, self-efficacy, and performance degrees of respondents were measured to verify the effects of the Simulation-MLM. The statistical processing of the collected data utilized the SPSS WIN 17.0 program. Results: After receiving Simulation-MLM, the participants in the experimental group reported higher marks in the knowledge, self-efficacy and performance of ACLS compared with those in the control group. However, both experimental and control groups demonstrated no significant differences in knowledge, self-efficacy and performance. Conclusion: Despite of the limitation of a small sample size, this study was considered meaningful in a sense that it showed a venue for improving ACLS training efficiency. Future research with more distinct treatment differentiation and better adequate outcome variables was warranted in order to prove the effects of a theory-based simulation education.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.253-263
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• 2021

This study aims to present effective teaching and learning methods for improving class satisfaction and improving the quality of university education by empirically analyzing changes in class satisfaction according to teaching methods such as face-to-face(FTF) classes, non-face-to-face(NFTF) classes, and blended classes of theories and practical subjects before and after COVID-19, targeting beauty major students who have a relatively higher proportion of practical classes than theoretical classes. For data analysis, SPSS 18.0 statistical package was used, and in the analysis of the difference in satisfaction with teaching methods for theoretical subjects before and after COVID-19, 10 items out of 20 items showed statistically significant differences, and 8 items out of 20 items in the practical subjects showed statistically significant differences. It is expected that the quality of university education will be improved by applying efficient and practical teaching methods considering the items affecting the class satisfaction according to the teaching and learning methods of these theories and practical subjects.

• Korean Journal of Mathematics
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• v.32 no.1
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• pp.43-57
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• 2024

Given a domain X and a collection H of functions h : X → {0, 1}, the Vapnik-Chervonenkis (VC) dimension of H measures its complexity in an appropriate sense. In particular, the fundamental theorem of statistical learning says that a hypothesis class with finite VC-dimension is PAC learnable. Recent work by Fitzpatrick, Wyman, the fourth and seventh named authors studied the VC-dimension of a natural family of functions ℋ'²_t(E) : 𝔽²_q → {0, 1}, corresponding to indicator functions of circles centered at points in a subset E ⊆ 𝔽²_q. They showed that when |E| is large enough, the VC-dimension of ℋ'²_t(E) is the same as in the case that E = 𝔽²_q. We study a related hypothesis class, ℋ^d_t(E), corresponding to intersections of spheres in 𝔽^d_q, and ask how large E ⊆ 𝔽^d_q needs to be to ensure the maximum possible VC-dimension. We resolve this problem in all dimensions, proving that whenever |E| ≥ C_dq^d-1/(d-1) for d ≥ 3, the VC-dimension of ℋ^d_t(E) is as large as possible. We get a slightly stronger result if d = 3: this result holds as long as |E| ≥ C_3q^7/3. Furthermore, when d = 2 the result holds when |E| ≥ C_2q^7/4.

• Journal of The Korean Association For Science Education
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• v.34 no.7
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• pp.693-701
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• 2014

Based on social cognitive theory, self-efficacy in the context of learning has been steadily emphasized as an indicator of students' motivation and performance. The premise for developing such an instrument was that a specific measure of Physics self-efficacy was deemed to be an important predictor of the change processes necessary to improve students' physics understanding. In this study we described the process of developing and validating an instrument to measure students' beliefs in their abilities to perform essential tasks in physics and then investigated high school students' self-efficacy about physics learning and performance. Validity and reliability of PSEI were tested using various statistical techniques including the Cronbach alpha coefficient, exploratory factor analysis. The result of factor analysis supported the contention that the Physics Self-Efficacy Inventory (PSEI) was a multidimensional construct consisting of at least four dimensions: understanding and application of Physics concepts, achievement motivation, confidence for physics laboratory, confidence for Mathematics. The result showed that Kroean high schools students have low Physics self-efficacy for the all four dimensions. Therefore, researchers should focus on development of students' Physics self-efficacy. In addition, the instrument may lead to further understanding of student behavior, which in turn can facilitate the development of strategies that may increase students' aspiration to understand and study Physics. More specifically, by using the PSEI as a pre- and post-test indicator, instructors can gain insight into whether students' confidence levels increase as they engage in learning Physics, and, in addition, what type of teaching strategies are most effective in building deeper understanding of Physics concepts.where they freely exchanged opinions and feedback for constructing better collective ideas.