• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1363-1372
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• 2021

Red tide, defined as the major reproduction of harmful birds, has the characteristics of being generated and diffused in a wide area. This has limitations in detection only with the existing investigation method. Therefore, in this study, red tide was detected using a remote sensing technique. In addition, it was intended to increase the accuracy of detection by using optical characteristics, not just the concentration of chlorophyll. Red tide mainly occurs on the southern coast where sea signals are complex, and the main red tide control species on the southern coast is Cochlodinium polykirkoides. Therefore, it was intended to secure objectivity by reflecting features that could not be found depending on the researcher's observation and experience, not limited to visual judgment using machine learning techniques. In this study, support background machines and random forest were used among machine learning models, and as a result of calculating accuracy as performance evaluation indicators of the two models, the accuracy was 85.7% and 80.2%, respectively.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.153-165
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• 2022

This study is about the Novel Engineering(NE) education program : a class model that combines reading and engineering. By including the process of directly designing and programming a virtual reality using CospacesEdu (a VR authoring tool for the NE class), the effects of the educational program on learners' STEAM literacy and Learning immersion are demonstrated. Moreover, the subject of this education is Dokdo in South Korea. As a result, the average of STEAM literacy is increased, and a significant change is confirmed statistically in Convergence. Learning immersion shows significant improvement in Challenges-skills balance. On the other hand, some students experience difficulties due to the long research stages, from reading a book to researching for information to designing VR and rewriting a story with the collected information. In conclusion, this study will help generalise other education using NE, and this developed program will be a reference that would suggest a new way of teaching.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.811-816
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• 2023

With the emergence of a climate crisis, climate disasters have recently been clearly felt in Korea. In particular, the typhoon 'Hinnamno' in the summer of 2022 made many people feel a sense of crisis with its formidable power. In this situation, children are likely to suffer great damage even in small crises due to their lack of experience and ability to cope with disaster situations. In this paper, we introduce a disaster response learning application that supports children's disaster response training. Designed based on research results on situational learning theory and child disaster safety education, this system produces various episodes and trains them to encounter disaster situations. Children can participate in the episode by choosing options during the episode, which is reflected in the picture diary after the episode is completed. By providing information naturally in the picture diary, children can access how to cope with disaster situations. Through this system, children are expected to develop their judgment in disaster situations that they can encounter and have the ability to secure basic safety outside of adult help.

• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.241-252
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• 2020

The purpose of this research is to study the effect of soldiers' self-development during military service on returning university students' self-directed learning and job preparation Behavior. The object of this study are 323 students among second, third and fourth graders of about 15 universities' nationalwide by online stratified clusterrandom sampling. SPSS 25.0 program was used for data analysis and factor analysis, frequency analysis, independent t-test, one way ANOVA, multiple regression analysis were done. The rusult are as follows :First, self-directed learning and job preparation behavior according to personal characters have meaningful differences in university location, grade, degree of self-development during military service, degree of self-development during military service, self-development during military service, e-learning study during military service, gaining credits during military service, gaining national licence during military service and receiving money for self-development during military service. Second, The experience of self-development during military service has meanigful difference in returnig university students' self-directed learning and job preparation behavior.

• School Mathematics
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• v.17 no.1
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• pp.135-156
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• 2015

There is a difference in quality between transition from elementary school to junior high school and the simple change of grades. This time is also a critical time that many students would be to abandon the mathematics. According to experience in conjunction with mathematics, this timing can be either bright or dark outlook with relation to mathematical development. Thus, at this turning point, it is necessary to analyze what changes the students are experiencing in teaching and learning mathematics, what such changes effect the students, whether or not there is room for improving such changes etc. Therefore, in this study, by comparing and analyzing math lessons of 6th grade in elementary school and 1st grade in junior high school, we investigate the difficulties of teaching and learning mathematics experienced by students who have been placed in the turning point and suggest implications to help them to land softly into junior high school.

• The Journal of Korean Association of Computer Education
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• v.11 no.4
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• pp.37-46
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• 2008

Using robots in the programming classes may help to induce learners' interest and motivation. However, simple introduction of new media, such as robots, may cause to increase learners' interest level temporarily, but also may give cognitive overload and offense against learning motivation. We developed a robot programming course to induce intrinsic motivation and to reduce cognitive load for learners in the programming education. And then, we implemented the developed course in college programming classes and analysed the educational effects of robot programming learning on novice learners' flow level. We found that robot programming course was helpful in enhancing novice learners' flow level. Especially, the element of 'autotelic experience', which explains an intrinsic motivation, was higher than conventional programming course group. It means that the developed strategies for robot programming course provides positive effects on learners' intrinsic motivation.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.

• School Mathematics
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• v.10 no.4
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• pp.583-601
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• 2008

The creative productivity is regarded as an essential factor to perform the gifted education. While it is very important to cultivate and to expand a creative productivity through mathematically problem solving in gifted education, we have difficulties in actual education of the (mathematically) gifted, even are there few researches/studies which deal with teaching and guiding the creative problem solving in mathematically gifted education, it is hard to find a guideline that provides proper ways (or directions) of learning-instruction and evaluation of the mathematically gifted. Therefore in this study, the researcher would provide a learning-instruction model to expand a creative productivity. The learning-instruction model which makes the creative productivity expanded in mathematically gifted education is developed and named MG-CPS(Mathematically Gifted-Creative Problem Solving). Since it reflected characteristics of academic- mathematical creativity and higher thinking level of the mathematically gifted, this model is distinguished from general CPS. So this model is proper to provide a learning experience and instruction to the mathematically gifted.

• The Journal of Bigdata
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• v.6 no.1
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• pp.197-206
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• 2021

GPR data is used for underground exploration. The data gathered are interpreted by experts based on experience as the underground facilities often reflect GPR. In addition, GPR data are different in the noise and characteristics of the data depending on the equipment, environment, etc. This often results in insufficient data with accurate labels. Generally, a large amount of training data have to be obtained to apply CNN models that exhibit high performance in image classification problems. However, due to the characteristics of GPR data, it makes difficult to obtain sufficient data. Finally, this makes neural networks unable to learn based on general supervised learning methods. This paper proposes an image classification method considering data characteristics to ensure that the accuracy of each label is similar. The proposed method is based on semi-supervised learning, and the image is classified using clustering techniques after extracting the feature values of the image from the neural network. This method can be utilized not only when the amount of the labeled data is insufficient, but also when labels that depend on the data are not highly reliable.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.187-196
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• 2021

This study was conducted as a study on the SW career education of students from underprivileged areas, which is a necessary condition for SW education to become a universal education or where research has not been conducted. Therefore, this study conducted a SW career selection model using structural equations for 2,231 students in grades 3 to 6 in 6 schools located in the marginalized areas of eup/myeon. As a result of the study, it was analyzed that the intrinsic SW learning motive of students from underprivileged areas did not affect their SW career choice, whereas the external SW learning motive was analyzed to affect their SW career choice. This is inferred that the intrinsic SW learning motive does not affect the SW career choice due to the lack of SW experience of students in underprivileged areas. The correlation between internal and external SW learning motivation was analyzed to be significant. In the future, as students from the underprivileged class have more SW education experiences, research should be conducted on how internal SW learning motives affect SW career choice and how external SW learning motives support internal SW learning motives.