• The Journal of Korean Association of Computer Education
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• v.13 no.4
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• pp.51-59
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• 2010

Many of learners in cyber universities have experienced the difficulties of learning and participation because they have never participated courses of cyber universities before. One of main reasons why they have experienced the difficulties was that they might have not received systematic guidances of university system as well as learning supports, depending on their readiness of e-learning. Otherwise, they may have lack of supports frequently and finally, fail to graduate. However, few studies were conducted to investigate the e-learning readiness of freshmen and enrollees in cyber universities. The purpose of the study was to analyze the e-learning readiness and learning activities of freshmen and enrollees of A cyber university and to support them more systematically and get them to succeed in studying. In the results, there were no differences between the freshmen and enrollees in basic competencies of cyber learning as well as interaction, task performance, and learning methods.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.969-975
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• 2011

The purpose of this study is to investigate the effects of learners' self-motivational attitudes, use of instructional function, and understanding of successful learning on achievement in college e-learning classes. The study analyzed 297 college students' questionnaire about their internet learning attitudes based on how they understand e-learning and use various internet functions for their learning achievement. After factor analyses, the results found that there were three major factors such as self-motivational attitude, use of instructional function, and understanding of successful learning out of 15 survey items. Multiple regression showed that the self-motivational factor affects the learning achievement with overall three factors analyses. This result indicates that college e-learning classes should focus on the analysis of learners' self-motivational issues in college e-learning classes. This study suggest that the relationship between learners' e-learning experience and learning achievement should be examined in the near future to show how it affects on learners e-learning class management and their achievement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.81-90
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• 2016

The objective of this study was to investigate the effect of an education method applying the flipped learning technique for college students. Both self-directed learning readiness and educational performance before and after applying the flipped learning were examined. After applying the flipped learning technique, teacher-student interaction, learning satisfaction, and learning motivation were identified. The correlation of each variable was examined after applying the flipped learning technique to investigate its influence on learning motivation. A total of 68 second-year nursing students enrolled in E University were analyzed. A difference between before and after applying the flipped learning was analyzed by the paired t-test; a correlation between the variables was analyzed via Pearson's correlation coefficient; and an influence on the dependent variable learning motivation was analyzed using the stepwise multiple regression analysis. The results showed that self-directed learning readiness increased before and after applying the flipped learning technique with statistical significance, and the difference of educational performance was not significant. After an education session applying the flipped learning technique, a learning motivation demonstrated a significantly positive correlation with self-directed learning readiness (r=0.33, p=.006), college student educational performance (r=0.51, p<.001), teacher-student interaction (r=0.72, p<.001), and learning satisfaction (r=0.79, p<.001). A significantly positive correlation was also observed between the other variables. Factors influencing learning motivation were learning satisfaction and teacher-student interaction. The explanatory power for learning motivation in the regression model considering these two variables was 71.3% (F=80.66, p<.001). Therefore, to enhance learning motivation in applying the flipped learning technique, it is necessary to increase learning satisfaction and to establish a strategy that further vitalizes the teacher-student interaction.

• Smart Media Journal
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• v.12 no.7
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• pp.9-17
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• 2023

Plant diseases and pests affect the growth of various plants, so it is very important to identify pests at an early stage. Although many machine learning (ML) models have already been used for the inspection and classification of plant pests, advances in deep learning (DL), a subset of machine learning, have led to many advances in this field of research. In this study, disease and pest inspection of abnormal crops and maturity classification were performed for normal crops using YOLOX detector and MobileNet classifier. Through this method, various plant pest features can be effectively extracted. For the experiment, image datasets of various resolutions related to strawberries, peppers, and tomatoes were prepared and used for plant pest classification. According to the experimental results, it was confirmed that the average test accuracy was 84% and the maturity classification accuracy was 83.91% in images with complex background conditions. This model was able to effectively detect 6 diseases of 3 plants and classify the maturity of each plant in natural conditions.

• Journal of Korean Public Health Nursing
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• v.34 no.3
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• pp.405-415
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• 2020

Purpose: This study was undertaken to identify the mediating effect of family strengths in the relationship between e-learning readiness and learning management system-based online education learning outcomes. Our results provide basic data for proposing strategies to increase online education learning outcomes of nursing students. Methods: A self-report questionnaire was surveyed by 133 nursing students who took online education using a learning management system at three nursing colleges in Daejeon, Jeonbuk, and Gyeongbuk. The mediating effect of family strengths in the relationship between the e-learning readiness of the subject and online education learning outcomes, were analyzed by hierarchical multiple regression. Sobel test was performed to verify effectiveness of the pathway. Results: In the relationship between e-learning readiness and online education learning outcomes of nursing students, family strengths were determined to exert absolute mediating effect. Conclusions: Our results indicate that in order to improve e-learning readiness, the basic curriculum for nursing students should include web-based communication, cooperation, and the use of information technology, including interaction for online education. Improvements in family strengths can be achieved through home study activities, such as frequent conversations with members, monitoring achievements of the students, and sharing family leisure activities.

• Education of Primary School Mathematics
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• v.24 no.4
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• pp.217-231
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• 2021

The purpose of this study was to investigate the effects of flipped learning through EBSmath on Students' 'rate and ratio' learning. By increasing demands for change in education, an innovative teaching and learning paradigm, 'Flipped Learning', has been presented and drawing attentions. In South Korea, Flipped Learning is also highly recognized for its effectiveness by many scholars and various media. However, this innovative learning model has limitations in application and expansion due to the excessive burden of class preparation of teachers. As remote learning becomes more active, it would be possible to overcome the limitations of Filliped learning by using the platform provided by the Korea Educational Broadcasting System (EBS). EBSmath is an online learning module that is designed to assist students' self-directed learning. Thus, EBSmath would reduce teachers' burden to prepare mathematics classes for the application of Flipped Learning; and led to students' better understanding of mathematical concepts and problem solving. In this study, the effect of Flipped Learning through EBSmath on learning 'rate and ratio' was investigated. In order to scrutinize the effects of flipped learning, students' achievement and mathematical disposition were examined and analyzed. Students' achievement, specifically, was divided into two subcategories: concept understanding and problem solving. As a result, Flipped learning through EBSmath had a positive effect on students' 'rate and ratio' problem solving. In addition, a statistically significant change was identified in the 'willingness', which is subdomain of students' mathematical disposition.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.42-42
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• 2022

지금까지도 유역에서의 녹조 모니터링은 현장채수를 통한 점 단위 모니터링에 크게 의존하고 있어 기후, 유속, 수온조건 등에 따라 수체에 광범위하게 발생하는 녹조를 효율적으로 모니터링하고 대응하기에는 어려운 점들이 있어왔다. 또한, 그동안 제한된 관측 데이터로 인해 현장 측정된 실측 데이터 보다는 녹조와 관련이 높은 NDVI, FGAI, SEI 등의 파생적인 지수를 산정하여 원격탐사자료와 매핑하는 방식의 분석연구 등이 선행되었다. 본 연구는 녹조의 모니터링시 정확도와 효율성을 향상을 목표로 하여, 우선은 녹조 측정장비를 활용, 7000개 이상의 녹조 관측 데이터를 확보하였으며, 이를 바탕으로 동기간의 고해상도 위성 자료와 실측자료를 매핑하기 위해 다양한Machine Learning기법을 적용함으로써 그 효과성을 검토하고자 하였다. 연구대상지는 낙동강 내성천 상류에 위치한 영주댐 유역으로서 데이터 수집단계에서는 면단위 현장(in-situ) 관측을 위해 2020년 2~9월까지 4회에 걸쳐 7291개의 녹조를 측정하고, 동일 시간 및 공간의 Sentinel-2자료 중 Band 1~12까지 총 13개(Band 8은 8과 8A로 2개)의 분광특성자료를 추출하였다. 다음으로 Machine Learning 분석기법의 적용을 위해 algae_monitoring Python library를 구축하였다. 개발된 library는 1) Training Set과 Test Set의 구분을 위한 Data 준비단계, 2) Random Forest, Gradient Boosting Regression, XGBoosting 알고리즘 중 선택하여 적용할 수 있는 모델적용단계, 3) 모델적용결과를 확인하는 Performance test단계(R², MSE, MAE, RMSE, NSE, KGE 등), 4) 모델결과의 Visualization단계, 5) 선정된 모델을 활용 위성자료를 녹조값으로 변환하는 적용단계로 구분하여 영주댐뿐만 아니라 다양한 유역에 범용적으로 적용할 수 있도록 구성하였다. 본 연구의 사례에서는 Sentinel-2위성의 12개 밴드, 기상자료(대기온도, 구름비율) 총 14개자료를 활용하여 Machine Learning기법 중 Random Forest를 적용하였을 경우에, 전반적으로 가장 높은 적합도를 나타내었으며, 적용결과 Test Set을 기준으로 NSE(Nash Sutcliffe Efficiency)가 0.96(Training Set의 경우에는 0.99) 수준의 성능을 나타내어, 광역적인 위성자료와 충분히 확보된 현장실측 자료간의 데이터 학습을 통해서 조류 모니터링 분석의 효율성이 획기적으로 증대될 수 있음을 확인하였다.