• Journal of Korean Home Economics Education Association
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• v.30 no.3
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• pp.195-213
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• 2018

The purpose of this study is to verify the effect by developing and applying a new program for improvement of creative problem solving ability and collaborative ability. Development of a sewing practice program was performed through the ADDIE model. The subjects of the study were 1^st grade middle school students and the research plan of the study was pretest-posttest control group design. The study method was performed by mixing the quantitative and qualitative analysis methods. Results of this study are as follows. First, the students in the experimental group showed higher creative problem solving ability than the students in the control group, but the difference was not significant at the 5% significance level. Qualitative analysis results indicated that creative problem solving ability is closely related to learning experiences involving the 'generation of diverse ideas', 'rebirth of creative ideas', 'self-directed learning plan', 'active problem solving', 'immediate feedback'. Second, the students in the experimental group showed a significantly higher level of collaborative ability than the students in the control group. This demonstrated that the program developed in this study had an effect on fostering the collaborative ability of middle school students. It was found that collaborative ability is closely related to learning experiences involving 'forming a positive atmosphere', 'continuous interaction', and 'working together'.

• Journal of the International Relations & Interdisciplinary Education
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• v.1 no.1
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• pp.46-60
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• 2021

The main purpose of this study was to examine the satisfaction of online classes of undergraduates who have experienced sudden online classes in college because of COVID-19, and to analyze the differences of the satisfaction of online classes depending on colleges. The participants were 1,380 college students. Descriptive statistics, one-way ANOVA, and Post-hoc Scheffé were performed. Undergraduates were highly satisfied with online classes in cultural subjects and major subjects, whereas they showed low satisfaction with appropriateness of the assignment. There were statistically significant differences in online class satisfaction between colleges. Students at the College of Education were highly satisfied with online classes satisfaction, while engineering students were less satisfied with online classes satisfaction. There were statistically significant differences in students engagements between colleges. Regardless of colleges, students displayed low satisfaction in e-class server and teaching and learning infrastructure. These findings suggest that we need to provide autonomous support and make an effective online learning environment such as server expansion and e-class improvement to enhance undergraduates' self-directed learning. We also should come up with effective online classes guidelines.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.336-345
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• 2019

To extend the potential benefits of error, the current study examined factors that affect students' error perception in classroom. An experimental design was used to measure relations of classroom goal structure, feedback, and social relationships on students' perception of error. A total 316 fourth, fifth, and sixth graders attending elementary schools participated as part of their regular class curriculum. Self-reported questionnaires were administered to measure students' perception of errors and relationships with teacher and peers, then students were manipulated by classroom goal structure and feedback. Results from multiple regression suggest that students' perception of learning from error has affected by relationships with peers at the most, then relationships with teacher and the type of feedback. Students' perception of risk taking for error also affected by relationships with peers and teacher, then the classroom goal structure. However, no classroom goal structure and feedback affect on their perception of thinking about error to improve their learning as well as error strain. These results imply how classroom climate should be structured to improve perception of errors to improve student's learning.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.71-81
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• 2019

To extend the potential benefits of error, the current study examined factors that affect students' error perception in the classroom. An experimental design was used to measure relations of classroom goal structure, feedback, and social relationships on students' perception of error. A total of 316 fourth-, fifth-, and sixth-grade elementary students participated as part of their regular class curriculum. Self-reported questionnaires were administered to measure students' perception of errors and relationships with teacher and peers, and then students were manipulated by classroom goal structure and feedback. Multiple regression analysis results suggested that students' perception of learning from error was affected mostly by relationships with peers, followed by relationships with teacher and the type of feedback. Students' perception of risk taking for error was also affected by relationships with peers and teacher, followed by the classroom goal structure. However, classroom goal structure and feedback did not affect their perception of thinking about error to improve their learning as well as error strain. These results imply how the classroom climate should be structured to improve perception of errors to improve student's learning.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.671-679
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• 2020

In order to increase the food self-sufficiency rate, monitoring and analysis of crop conditions in the cultivated area is important, and the existing measurement methods in which agricultural personnel perform measurement and sampling analysis in the field are time-consuming and labor-intensive for this reason inefficient. In order to overcome this limitation, it is necessary to develop an efficient method for monitoring crop information in a small area where many exist. In this study, RGB images acquired from unmanned aerial vehicles and vegetation index calculated using RGB image were applied as deep learning input data to classify complex upland crops in small farmland. As a result of each input data classification, the classification using RGB images showed an overall accuracy of 80.23% and a Kappa coefficient of 0.65, In the case of using the RGB image and vegetation index, the additional data of 3 vegetation indices (ExG, ExR, VDVI) were total accuracy 89.51%, Kappa coefficient was 0.80, and 6 vegetation indices (ExG, ExR, VDVI, RGRI, NRGDI, ExGR) showed 90.35% and Kappa coefficient of 0.82. As a result, the accuracy of the data to which the vegetation index was added was relatively high compared to the method using only RGB images, and the data to which the vegetation index was added showed a significant improvement in accuracy in classifying complex crops.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.227-233
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• 2021

To obtain a fruitful outcome in intellectual property (IP) education in colleges, it is essential to identify the affecting factors. The relationships between the factors were to be analyzed as a structural equation model. The IP education achievement was measured by the IP total score. The students' characteristics (input factor) were measured by defining the characteristics, parents' expectations, and IP interest. The characteristics after highschool (process factor) were observed as college satisfaction and learning attitude. Students with excellent defining characteristics have not only high college satisfaction but also an excellent learning attitude, so they have a high IP total score. Using indirect effects analysis, the path through which the defining characteristics indirectly affects the IP total score through college satisfaction and learning attitude was identified. This is consistent with the prediction that self-directed students will have high participation in IP classes and achieve excellent results. The IP interest was found to have no significant effect on the IP total score. This contradicts the belief that students with high IP interest will actively participate in IP classes and earn high scores, which is because it overlooks the possibility that participation in IP activities in high school is semi-forced.

• (The) Korean Journal of Educational Psychology
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• v.31 no.3
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• pp.563-587
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• 2017

The purpose of this study was to understand the ways to enhance academic help-seeking by analyzing the structural relations among individual(achievement goal orientation) and contextural (teacher behaviors and classroom climate) factors known to affect help-seeking, one of the effective self-regulated learning strategies, for upper elementary students. More specifically, it explored the mediational roles of general classroom climate and student achievement goal orientation in the relation between supportive teacher behaviors and student academic help-seeking. A survey was administered to 315 fifth- or sixth-grade students in three elementary schools and the data from the survey was analyzed. Main results are as follows. First, supportive and learning-oriented teacher behaviors with high expectation related to more cohesive and positive classroom climate and more adaptive achievement goal such as mastery goal. Positive classroom climate played an important role in improving student mastery goal, and only mastery goal among different types of achievement goal orientation had a positive prediction of student help-seeking. Second, teacher behaviors significantly predicted student help-seeking through a double mediation of classroom climate and student mastery goal, which showed that classroom contextual factors and student individual factors interacted for help-seeking. These results suggest that the role of teachers as well as the mastery goal of students are important for enhancing students' help-seeking behavior as an adaptive learning strategy.

• (The) Korean Journal of Educational Psychology
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• v.22 no.2
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• pp.461-478
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• 2008

This study attempted to test whether or not students' collaborative argumentation and explanation activity while using concept mapping did improve understanding on texts. Total of 52 college students participated in this study. They were randomly assigned to one of four experimental conditions. The experiment lasted for two or three weeks and students were tested on comprehension level of a text material that they have studied over the period. As a result, with two independent factors of explanation and collaboration, there was a significant interaction effect without main effects. That is, individual did better when they did have to explain what they were doing. However, this is not the case when students collaborate. Students in the paired condition, they did better when they do not have to explain what they were doing with concept maps. This study showed efficiency with using computerized software does not always guarantee higher understanding on text materials. Instructional contexts and variables, collaboration and explanation, needs to be considered. Collaborating with others and explaining their own learning processes should be carefully designed when they are combined with concept mapping contexts. How to minimize learning obstacles from discussing ideas with others are a critical issue for future research.