• Journal of Elementary Mathematics Education in Korea
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• v.19 no.4
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• pp.457-484
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• 2015

This study aims to investigate an approach to teach proportional reasoning in elementary mathematics class by analyzing the proportional strategies the students use to solve the proportional reasoning tasks and their percentages of correct answers. For this research 174 sixth graders are examined. The instrument test consists of various questions types in reference to the previous study; the proportional reasoning tasks are divided into algebraic-geometric, quantitative-qualitative and missing value-comparisons tasks. Comparing the percentages of correct answers according to the task types, the algebraic tasks are higher than the geometric tasks, quantitative tasks are higher than the qualitative tasks, and missing value tasks are higher than the comparisons tasks. As to the strategies that students employed, the percentage of using the informal strategy such as factor strategy and unit rate strategy is relatively higher than that of using the formal strategy, even after learning the cross product strategy. As an insightful approach for teaching proportional reasoning, based on the study results, it is suggested to teach the informal strategy explicitly instead of the informal strategy, reinforce the qualitative reasoning while combining the qualitative with the quantitative reasoning, and balance the various task types in the mathematics classroom.

• Journal of Science Education
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• v.41 no.1
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• pp.152-165
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• 2017

The magnetic field due to a current is one of the core concepts in electromagnetism which has been taught in secondary science education. In addition, it is a representative example of using visual representations to explain the relation between invisible physical quantities; current and magnetic field. In this study we investigated middle school students' representational competence into three components; interpretation, construction, and application of visual representations. According to the analysis, more than 75 % of the respondents interpreted the meaning of the arrows for current and magnetic field correctly. However, half of them confused the movement of electric charges with the direction of magnetic field. Over 60 % of the students constructed the magnetic field representation as circular closed curves, but many of them could not express the density of field lines properly. In application of visual representations, more than half failed to draw the direction of compass needle correctly. The scores were in order of interpretation, construction and application. There were also significant correlations among three components of representational competence. More attention and research on students' representational competence and effective use of visual representations is needed to better support science learning and teaching.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.209-228
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• 2011

Web search behavior has evolved. People now search using many diverse information devices in various situations. To monitor these scattered and shifting search patterns, an improved way of learning and analysis are needed. Traditional web search studies relied on the server transaction logs and single query instance analysis. Since people use multiple smart devices and their searching occurs intermittently through a day, a bundled query research could look at the whole context as well as penetrating search needs. To observe and analyze bundled queries, we developed a proprietary research software set including a log catcher, query bundling tool, and bundle monitoring tool. In this system, users' daily search logs are sent to our analytic server, every night the users need to log on our bundling tool to package his/her queries, a built in web survey collects additional data, and our researcher performs deep interviews on a weekly basis. Out of 90 participants in the study, it was found that a normal user generates on average 4.75 query bundles a day, and each bundle contains 2.75 queries. Query bundles were categorized by; Query refinement vs. Topic refinement and 9 different sub-categories.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.681-691
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• 2016

In this study, we investigated pre-service secondary chemistry teachers' use of teacher's guide in planning lessons. Eleven pre-service teachers at a college of education in Seoul participated in this study. Textbooks and teacher's guide books including various teaching materials were provided. Pre-service teachers used teacher's guide while they planned two lessons, which were a lecture and an instruction using science teaching model. A semi-structured interview was conducted. All of the teaching-learning materials and interviews were analyzed. The analyses of the results revealed that most pre-service teachers followed each lesson presented in teacher's guide, but they did not consider the structure of the whole unit and science curriculum. There were some cases that the exemplary lesson planning in teacher's guide helped them to select science teaching model. They modified the questions of textbook activity in planning their lecture. On the other hand, they modified the activity to fit each stage of the model in planning their instruction using science teaching models. Most pre-service teachers constructed their own worksheets by applying the materials of the teacher's guide. They recognized the components of assessment by considering exemplary lesson planning from the teacher's guide, and created questions by modifying the content of textbooks and teacher's guide books including various teaching materials. However, the questions which they made were limited in context of knowledge. They evaluated that introductory questions were not of interest to students, and modified or added new materials. Educational implications of these findings are discussed.

• Journal of Korean Library and Information Science Society
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• v.51 no.3
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• pp.325-350
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• 2020

For University students, reading is one of the important way of character education and career education that can give students the power to recognize and adapt to changes in society. The university supports the reading activities of university students in various ways, such as opening liberal arts courses related to reading or setting up required credits. In addition, it supports activities such as selecting the recommended book list for university students and providing the list. The purpose of this study is to analyze the problems of the current university's recommended book list and methods of using reading, and to propose improvement plans. To this end, using D University as an example, the current status of the recommended book list and reading discussion program were identified, and problems were investigated. In the current recommended book list, the subject area and list did not properly reflect the times, and the information on the provided list was very simple. Also, it was found that there was no suggestion on how to use the recommended book list. Through this, the recommended book list with the addition of bibliographic information and composition of the subject area was proposed. In addition, the reading discussion method was structured using Havruta.

• Korean Journal of Childcare and Education
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• v.10 no.2
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• pp.319-335
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• 2014

The purpose of this study was to examine the effects of variables of interest on mothers' choices of infant care. The variables of interest in this study were categorized into the following three areas: 1) demographic characteristics of mothers and infants, 2) structural and procedual dimensions of infant care facilities, and 3) maternal beliefs on child-rearing. The subjects of this study were mothers whose infants were currently cared by at infant care facilities(n=185) and those who were on the waiting list to use non-maternal infant care(n=53). The main results of this study were as follows. First, mothers of this study preferred to select a type of center-based subsidized infant care over other types of care(family day care) due to quality of the program. Second, the mothers who were not using infant care and cared for their infants at homes reported that there were limitations in their choices of types of infant care due to accessibility and availability of public subsidized infant care facilities, and their child rearing goals were more likely to emphasize learning achievement and maturity than character education or personality. The mothers were more likely to choose a family home care over center-based public subsidized care when they were employed, had younger infants, had longer period of time on waiting lists, and emphasized structural dimensions of infant care than center-based care users. Implications for research and practices were discussed along with the main results of this study.

• Journal of The Korean Association For Science Education
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• v.30 no.1
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• pp.170-180
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• 2010

Among the various fields of Earth Science, especially in Astronomy, we often deal with the change of space-time in an abstract way. Thus, making use of 'Concept Sketches'-simplified sketches that represent the main features, principles, processes and interrelationships of the learning content by using some concise explanations, signs and terms could help the students efficiently learn the phenomena of Astronomy. This study's aim was to check its effects and analyze the results of the lessons that included concept sketches and a discussion about the field of Earth Science in high school. The control group took traditional lessons, while the experimental group did a small-group discussion that used the concept sketches. After the lesson, some students were chosen to answer a questionnaire and go through an in-depth interview. The result of the data shows that the small-group discussion lesson that used the concept sketches helped both the high-ranking and low-ranking students to build concepts and was able to attract students' attention. Moreover, the students produced long-term memories of the content learned through the class discussion, which allowed them to exchange their own thoughts and opinions with other students. Most of all, drawing pictures, a familiar activity, appealed to the students, so they took part in the class eagerly.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.197-205
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• 2020

Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.