• Journal of The Korean Association For Science Education
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• v.36 no.6
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• pp.895-910
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• 2016

The purpose of this study is to explore secondary students' progression in group norms and argumentation competency through collaborative reflection about small group argumentation. The progression is identified as the development of group norms and an epistemic understanding of argumentation with the enhancement of group argumentation competency during collaborative reflection and argumentation lessons. Participants were four first grade middle school students who have different academic achievements and learning approaches. They participated in ten argumentation lessons related to photosynthesis and in seven collaborative reflections. As a result, the students' group norms related to participation were developed, and the students' epistemic understanding of argumentation was enhanced. Furthermore, the students' group argumentation competencies, identified as argumentation product and argumentation process, were advanced. As the collaborative reflection and argumentation lessons progressed, statements related to rebuttal increased and different students suggested a range of evidence with which to justify their claims or to rebut others' arguments. These findings will give a better idea of how to present an apt application of argumentation to science teachers and science education researchers.

• Journal of The Korean Association of Information Education
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• v.9 no.4
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• pp.635-648
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• 2005

It meets 21 century and the society is quickly changing with advancement of Information and Communication Technology(ICT), the use of the Internet which increases geometrical progression is changing the paradigm of the instruction and learning. The school education site which uses a consequently new ICT and change of instructional method became to be inevitable. Uses the most up-to-date medium in the students who in the knowledge information society of 21 century will live with the leading actor and it will be able to accommodate information which increases explosively effectively in order, description below hazard only information knowledge education which stands the bay knows application education, compared to further information anger early rising education for the whole life studying social realization more earnestly what than is necessary. In this study, It examined the actual state and a problem point of ICT application ability and ICT application education of the elementary school teachers. It will reach to lead, the reporter to grope the improvement program of ICT application education it did.

• Journal of Science Education
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• v.46 no.1
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• pp.1-16
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• 2022

The purpose of this study is to explore learning progressions for global warming at middle school level. For this purpose, we conducted a construct modeling approach that specifies constructs, item designs, outcome spaces, and measurement model steps from April to October, 2021. In order to develop student assessment items, we analyzed the 2015 revised curriculum and textbooks of middle school and categorized a concept hierarchy for each construct to create a construct map. The assessment items were developed into multiple-choice, short answer, and essay questions according to the selected constructs to strengthen the linkage between the constructs and the items. Based on the three-step grading criteria for each item, an online assessment of 21 minor items developed for middle school students show that many students met 'high' level, but none met 'low' level. In this manner, the initial set lower anchor was reset to level 0, the original set upper anchor was lowered from level 4 to level 3, and the hypothetical learning progression for global warming was presented in the following order: phenomenal, conceptual, and mechanical understandings. The results of the research have raised implications for reorganizing the next science curriculum and improving the assessment system.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1172-1180
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• 2004

Recently, the gene expression data, product of high-throughput technology, appeared in earnest and the studies related with it (so-called bioinformatics) occupied an important position in the field of biological and medical research. The microarray is a revolutionary technology which enables us to monitor several thousands of genes simultaneously and thus to gain an insight into the phenomena in the human body (e.g. the mechanism of cancer progression) at the molecular level. To obtain useful information from such gene expression measurements, it is essential to analyze the data with appropriate techniques. However the high-dimensionality of the data can bring about some problems such as curse of dimensionality and singularity problem of matrix computation, and hence makes it difficult to apply conventional data analysis methods. Therefore, the development of method which can effectively treat the data becomes a challenging issue in the field of computational biology. This research focuses on the gene selection and classification for cancer subtype discrimination based on gene expression (microarray) data.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.591-600
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• 1993

Considerable controversy exists about the trend of animal traction effects on crop production in dryland farming systems in sub-Saharan Africa (SSA). This problem arises on account of the failure of the few available empirical studies to recognise the important of technological experience of the individual adopting farmers. This study hence addresses this issue by examining the effects of experience in animal traction technology (ATT) on farm size, cropping emphasis, total crop output and farm productivity. It is based on farm management survey data on 42 small holder farm households fro Ghana. Thirty of these households used animal traction technology (ATT) fro crop cultivation and the rest, mainly hand-hoe. The animal traction sub-sample is classified into three groups according to farmers' years of experience with the technology , thus , those with 1-2, 3-10, and more than 10. Evidence from the study shows that the progression of years of experience with ATT leads to inten ification of labour and land use systems, enhancement of degree of motivation to enter into the market economy, increases in total crop output and farm productivity resulting for decreases in cultivated acreages. The implication of the findings is that institutioal and technical support that do accompany the introduction of such technologies should be structured to last for a relatively longer period to accomodate the learning process.

• Journal of The Korean Association of Information Education
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• v.21 no.3
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• pp.343-350
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• 2017

This current study employs multi-year design-based research to design and implement a course in teacher education in Korea. Specifically this paper reports our first attempt to work with 3 primary in-service teachers majoring in computer education. We have incorporated design thinking (DT) into the course design and investigated how primary teachers appreciate the role of DT and recognize the connection between teaching computational thinking and DT. This qualitative study reports the course design, its progression, reflections, and learning outcomes.

• Clinical and Experimental Pediatrics
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• v.64 no.10
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• pp.497-503
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• 2021

Reading disability (dyslexia) refers to an unexpected difficulty with reading for an individual who has the intelligence to be a much better reader. Dyslexia is most commonly caused by a difficulty in phonological processing (the appreciation of the individual sounds of spoken language), which affects the ability of an individual to speak, read, and spell. In this paper, I describe reading disabilities by focusing on their underlying neurobiological mechanisms. Neurobiological studies using functional brain imaging have uncovered the reading pathways, brain regions involved in reading, and neurobiological abnormalities of dyslexia. The reading pathway is in the order of visual analysis, letter recognition, word recognition, meaning (semantics), phonological processing, and speech production. According to functional neuroimaging studies, the important areas of the brain related to reading include the inferior frontal cortex (Broca's area), the midtemporal lobe region, the inferior parieto-temporal area, and the left occipitotemporal region (visual word form area). Interventions for dyslexia can affect reading ability by causing changes in brain function and structure. An accurate diagnosis and timely specialized intervention are important in children with dyslexia. In cases in which national infant development screening tests have been conducted, as in Korea, if language developmental delay and early predictors of dyslexia are detected, careful observation of the progression to dyslexia and early intervention should be made.

• Journal of Korea Game Society
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• v.21 no.3
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• pp.3-12
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• 2021

This study is a design study to develop the reading application for English learning courses with fun elements of Gamification incorporating user's immersion. The system is focusing on the story progression of Aesop's fable "Rabbit and Tortoise", which is consisted of chapters in digital technology. We intended to apply the four elements of fun factors by grafting Gamification into the game engine system. The purpose and significance of the study is to present the guideline through evaluation of usability from prototypes by surveying the educator group.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.425-427
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• 2022

The grade of glioma is important information related to survival and thus is important to classify the grade of glioma before treatment to evaluate tumor progression and treatment planning. Glioma grading is mostly divided into high-grade glioma (HGG) and low-grade glioma (LGG). In this study, image preprocessing techniques are applied to analyze magnetic resonance imaging (MRI) using the deep neural network model. Classification performance of the deep neural network model is evaluated. The highest-performance EfficientNet-B6 model shows results of accuracy 0.9046, sensitivity 0.9570, specificity 0.7976, AUC 0.8702, and F1-Score 0.8152 in 5-fold cross-validation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.