• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.579-587
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• 2015

The purpose of this study is to investigate how Korean learners perceive English vowels and further to test SLM which claims that new L2 vowel categories are more easily acquired than similar L2 vowel categories. Twenty Korean learners participated in English-to-Korean mapping test and English vowel identification test with target vowels /i, ɪ, u, ʊ, ɛ, æ/. The result revealed that Korean participants mapped the English pairs /i/-/ɪ/ and /u/-/ʊ/ onto single Korean vowel /i/ and /u/, respectively. in addition, both of English /ɛ/ and /æ/ were simultaneously mapped onto Korean /e/ and /ɛ/. This indicated that the Korean participants seemed to have perceptual difficulty for the pairs /i-ɪ/, /u-ʊ/, and /ɛ-æ/. The result of the forced-choice identification test showed that the accuracy of /ɪ, ʊ, æ/(ɪ: 81.3%, ʊ: 62.5%, æ: 60.0%) was significantly higher than that of /i, u, ɛ/(i: 28,8%, u: 28.8%, ɛ: 32.4%). Thus, the claim of SLM is confirmed given that /ɪ, ʊ, æ/ are new vowel categories whereas /i, u, ɛ/ are similar vowel categories. Further, the conspicuously low accuracy of the similar L2 vowel categories /i, u, ɛ/ was accounted for by over-generalization whereby the Korean participants excessively replaced L2 similar /i, u, ɛ/ with L2 new /ɪ, ʊ, æ/ as the participants were learning the L2 new vowel categories in the process of acquisition. Based on the findings this study, pedagogical suggestions are provided.

• Journal of Korean Elementary Science Education
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• v.33 no.2
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• pp.231-241
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• 2014

This study is subject to compare the STEAM and the STEM education of Korea, the U.K., and the U.S. to find their differences and similarities, as well as the implications in implementing the STEAM education in Korea. In order to accomplish this, the educational objectives, contents and topics, teaching and learning methods, subjects and timing for education, and convergence curriculum were compared; also, after choosing the representative program of each country, a cross-comparative analysis was done for the teaching and learning method distribution ratio, content element distribution ratio, program distribution ratio, STEAM domain ratio, curriculum structure and domain ratio, frequency of inquiry process, basic inquiry, integrated inquiry frequency, hourly basic inquiry, and integrated inquiry process. As a result, it was possible to obtain 77 programs, a total of 656 class hours of Korea, 65 programs and 846 class hours of the U.S., and 75 programs and 774 class hours of the U.K. The results are as follows: Korea's STEAM and the U.K. and the U.S.' STEM all include science, technology, engineering, arts, and mathematics, but in terms of frequency, Korea's STEAM has higher figure in arts. However, the U.K. and the U.S. have higher frequency of debate and discussion, and there were many cases of a student, after receiving feedback from other students, modifying the work.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.23-32
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• 2021

Semantic image segmentation technology in the field of computer vision is a technology that classifies an image by dividing it into pixels. This technique is also rapidly improving performance using a machine learning method, and a high possibility of utilizing information in units of pixels is drawing attention. However, this technology has been raised from the early days until recently for 'lack of detailed segmentation' problem. Since this problem was caused by increasing the size of the label map, it was expected that the label map could be improved by using the edge map of the original image with detailed edge information. Therefore, in this paper, we propose a post-processing algorithm that maintains semantic image segmentation based on learning, but modifies the resulting label map based on the edge map of the original image. After applying the algorithm to the existing method, when comparing similar applications before and after, approximately 1.74% pixels and 1.35% IoU (Intersection of Union) were applied, and when analyzing the results, the precise targeting fine segmentation function was improved.

• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.314-327
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• 2014

This is a quasi-experimental study involving one group design with pretest and posttest for evaluation of an effectiveness of an emergent care management simulation education among senior nursing students according to their learning styles. Participants were 58 senior nursing students. Learning style and educational effectiveness (critical thinking disposition, problem solving process, cooperation, satisfaction with learning, and self-confidence) were measured. Learning styles of senior nursing students were converger 46.6%, assimilator 34.5%, accommodator 15.5%, and diverger 3.4%. Critical thinking disposition, problem solving process, cooperation, and self-confidence were significantly enhanced by an emergent care management simulation education. Otherwise, educational effectiveness according to learning styles were not significantly different. Based on the results, devising stratagem to maximize an educational effectiveness will be needed trough re-evaluation of relationship between learning styles and effectiveness of a simulation education.

• Communications of Mathematical Education
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• v.33 no.3
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• pp.295-317
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• 2019

Angle concept is widely used in all mathematics curriculums and is a basic concept in geometric domain. Since angle have a multifaceted and affect subsequent learning, it is necessary for students to understand various angle concepts. In this study, Singapore, U.K., Australia, and U.S. are selected as comparable countries to examine the angle-related contents and learning process that appear in the curriculum as a whole, and then look at the perspectives and the size aspects of angle in detail and give implications to the Korean curriculum based on them. According to the analysis, the four countries except Korea, supplement angle, complement angle, angles on a straight line, angles at a point, and finding angle were explicitly covered in the curriculum. And most countries gradually covered angle-related contents over several years, compared to Korea which intensively studied in a particular school year. In common, definition of angle was described as static, measurement of angle was described as dynamic. But in Korean curriculum, dynamic views on angles are described later and less compared to other countries, and range of angle size was narrower than in other countries'. From this comparison, this study suggest to discuss how to place and develop various contents of characteristics of angle in curriculum, address the angle using both static and dynamic perspectives, and introduce the angle size as the amount of rotation to learn the reflex angle, $180^{\circ}$, $360^{\circ}$ angle.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.11
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• pp.1448-1457
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• 2004

Based upon mail survey method, this empirical research aims to compare the CAD education in four countries in terms of education conditions, education methods, and education performance. Results show that Korea is similar to Japan in many ways, while it differ from U.S.A. or Germany in several respects. Putting less importance in CAD course, Korean professors of CAD were found to be relatively young and deficient of teaching experience and/or industrial experience. And CAD course, which is not compulsory but elective one, is taught in a more crowded (junior) class with less satisfactory hardware and software. In the education goal or contents, the CAD courses in Korea lack real world problems or applications, concentrating less on students-based or problem-based learning methods than Germany or U.S.A.. Consequently, Korean CAD education is outperformed by German or U.S. one in educational performance both in skill improvement and in attitude enhancement.

• The Journal of Information Systems
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• v.20 no.4
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• pp.181-204
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• 2011

Recently, the development of ICT(information & communications technology) with the advent of new media paradigm shift in learning has brought a dramatic impact on the competitiveness of universities. The previous studies on the academic performance of e-learning mainly targeted on e-learning users, studying additional synchronization and system quality factors to measure academic performance. This study empirically analyzed the learning flow and academic performance considering both DeLone & McLean model system quality and synchronizing factors based on ARCS model. Relating to quality and synchronization factors, the academic performance of e-learning system was tested, and the difference between learning flow and academic performance was also analyzed based on time-series data, by the test difference(in the beginning, during, and final of the semester). The results of the study are as follows. First, the study shows that both system quality and synchronization directly affected the learning performance. Thus, when designing e-learning system, it is necessary to consider these two factors at the same time. Second, the indirectly mediating effect on the system quality and synchronization factors turned out to be significant in learning flow. Third, the result of regression analysis on the contents of utilizing dummy variable presents that the teacher's explanation has greater influence than multimedia has to the academic performance, and furthermore, the test difference showed no significance. Further research should be undertaken to consider the learner's degree of acceptance which reflects various aspects for building m-learning or u-learning.

• Journal of the Korean Society for Heat Treatment
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• v.36 no.6
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• pp.396-401
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• 2023

Aus-tempering heat treatment is suitable for thin and small-sized in precision parts. However, the heat treatment process relies on the experience and skill of the operator, making it challenging to produce precision parts due to the cold forging process. The aims of this study is to explore suitable machine learning models using data from the aus-tempering heat treatment process and analyze the factors that significantly impact the mechanic properties (e.g. hardness). As a result, the study analyzed, from a machine learning perspective, how hardness prediction varies based on the quenching temperature, carbon (C), and copper (Cu) contents.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.306-319
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• 2010

Recently, crime prevention is away of important criminal justice policy and police activity also pursuit different change compare to the present times. After modern times, as get to know crime control change, eventually on the basis of experience that crime prevention is best way of crime control, what come out with new sight angle for the role of police is community policing. And emphasis points in police activity are variety of police activity, positive entry of community. In relation to this, we are learning crime prevention of the U.S.A and the program of community policing through crime prevention theory books that published in domestic. Then, there are misunderstanding possibilities that the programs which introduced relation books are doing someways all around the U.S.A In this research two cities san mateo county. california, of the U.S.A made a choice, and is going to search main crime present condition of these cities and really done community policing program or crime prevention program operation case.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.143-156
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• 2023

To precisely and reliably analyze the contents of the satellite imagery, recognizing the clouds which are the obstacle to gathering the useful information is essential. In recent times, deep learning yielded satisfactory results in various tasks, so many studies using deep neural networks have been conducted to improve the performance of cloud detection. However, existing methods for cloud detection have the limitation on increasing the performance due to the adopting the network models for semantic image segmentation without modification. To tackle this problem, we introduced the multi-branch neural architecture search to find optimal network structure for cloud detection. Additionally, the proposed method adopts the soft intersection over union (IoU) as loss function to mitigate the disagreement between the loss function and the evaluation metric and uses the various data augmentation methods. The experiments are conducted using the cloud detection dataset acquired by Arirang-3/3A satellite imagery. The experimental results showed that the proposed network which are searched network architecture using cloud dataset is 4% higher than the existing network model which are searched network structure using urban street scenes with regard to the IoU. Also, the experimental results showed that the soft IoU exhibits the best performance on cloud detection among the various loss functions. When comparing the proposed method with the state-of-the-art (SOTA) models in the field of semantic segmentation, the proposed method showed better performance than the SOTA models with regard to the mean IoU and overall accuracy.