• Journal of Digital Convergence
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• v.13 no.7
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• pp.47-55
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• 2015

In e-learning industry which represents the convergence of IT and education, the standard of e-learning content development cost has been calculated according to the guideline or standard of existing similar industries without considering the characteristics of the industry until today. The absence of contents development cost standard related to e-learning has been recognized as one of the most difficulties in e-learning industry. The calculation of the content development cost without reflecting the characteristics of e-learning industry has bad effects such as the degradation of content quality and development of e-learning industry, and the growth obstruction of them. This paper suggest a standard of development cost for e-learning content development considering the characteristics of e-learning industry. We analyse current problems and the characteristics in e-learning industry, and define the development cost standard. We propose the methodology for developing e-learning industry and for contributing quality improvement of e-learning content.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.49-56
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• 2023

The purpose of this study is to develop convergence major-based learning (CMBL), which selects performance tasks related to local problems at hand and solves them based on convergence major performance, and builds a suitable teaching and learning model. We developed a CMBL class with a team project-type class that finds and solves practical problems in the region to cultivate overall problem-solving capabilities for convergence major competencies. Additionally, for this class, the instructor played a role as a bridgehead to explore and connect the community's sites, and students visited connected institutions in person to identify problems they need based on understanding and empathy for the subjects through field observation and qualitative interviews, and developed a CMBL class teaching and learning model necessary to directly solve them by using their major capabilities to the fullest. Therefore, we intend to present the future-oriented direction of university convergence education required by the community by forming a group of students with various majors to cultivate the ability to solve realistic problems in the community.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.199-208
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• 2021

In this paper, the effect of artificial intelligence convergence education program that provides STEAM education using machine learning platform on elementary school students' STEAM literacy and learning flow was analyzed. A homogeneous group of 44 elementary school 6th graders was divided into an experimental group and a control group. The control group received 10 lessons of general subject convergence class, and the experimental group received 10 lessons of STEAM-based artificial intelligence convergence education using Machine learning for Kids. To develop the artificial intelligence convergence education program, the goals, achievement standards, and content elements of the 2015 revised curriculum to select subjects and class contents is analyzed. As a result of the STEAM literacy test and the learning flow test, there was a significant difference between the experimental group and the control group. In particular, it can be confirmed that the coding environment in which the artificial intelligence function is expanded has a positive effect on learners' learning flow and STEAM literacy. Among the sub-elements of convergence talent literacy, significant differences were found in the areas of personal competence such as convergence and creativity. Among the sub-elements of learning flow, significant differences were found in the areas such as harmony of challenge and ability, clear goals, focus on tasks, and self-purposed experiences. If further expanded research is conducted in the future, it will be a basic research for more effective education for the future.

• Journal of Digital Convergence
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• v.13 no.7
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• pp.9-21
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• 2015

Nowadays, within the paradigm shift of e-learning, MOOCs service has been expanded among a number of global leading universities and this has affected our domestic universities' e-learning to look for different possibilities and new challenges. In consideration of our domestic educational condition, it is required to contemplate how university e-learning can be changed and developed with focus on MOOCs from the perspective of convergence development. This study suggests plans for convergence development in university e-learning based on MOOCs with conceptual model. We conducted the studies on relevant literature of university e-learning and MOOCs, expert consultation, SWOT analysis, survey for those involved of e-learning centers, etc. Through this process, we developed a final plan which integrates 'open advanced education course service', 'teaching and learning curation service', 'teaching and learning practice service', 'creative teaching and instruction method development and sharing service', and 'cloud based educational platform support service', etc with the perspective of convergence development. Also we designed convergence development plan based on MOOCs. It is assumed that the result of this research provides advanced plans for development of university e-learning and the base for further discussion of introduction and application of MOOCs service in domestic university.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.85-90
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• 2018

The purpose of this study is to analyze the effect of flipped learning strategy, which is an online offline convergence learning strategy becoming a hot issue, on students' learning styles..Ultimately, the goal is to analyze the academic achievements and learning attitudes by applying the flipped learning strategy considering the preferred learning styles of Korean students. By assuming that Korean students are accustomed to traditional lecture class, it is assumed that the students would have difficulty in applying the flipped learning strategy which involves information gathering and problem solving through discussion. In order to analyze whether the application of flipped learning strategy is effective, it is necessary to identify students' preferred learning style and to develop appropriate teaching strategies accordingly.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.249-256
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• 2017

This study was conducted concerning convergence education practice to examine the difference of learning activity participation based on college students' individual traits such as gender, grade and major. To achieve the purpose, the types of learning activity were divided into teacher-directed type, teacher-intervened type, peer-leader type, students' mutual initiative type, and then the difference of types of participation in learning activities based on learners' traits was examined. The results of crosstabs showed that there were differences in the participation of learning activities depending on the students' individual traits. The participation of girl students in gender, first year students in school-year, and students of Health & Social Service in major was significantly high.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.145-156
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• 2022

Nowadays, the complexity of object tracking models among hardware applications has become a more in-demand duty to complete in various indeterminable environment tracking situations with multifunctional algorithm skills. In this paper, we propose a virtual city environment using AirSim (Aerial Informatics and Robotics Simulation - AirSim, CityEnvironment) and use the DQN (Deep Q-Learning) model of deep reinforcement learning model in the virtual environment. The proposed object tracking DQN network observes the environment using a deep reinforcement learning model that receives continuous images taken by a virtual environment simulation system as input to control the operation of a virtual drone. The deep reinforcement learning model is pre-trained using various existing continuous image sets. Since the existing various continuous image sets are image data of real environments and objects, it is implemented in 3D to track virtual environments and moving objects in them.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.247-256
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• 2018

The purpose of this study is to examine effects of pre-learning and role learning using video on self-regulated learning of nursing students in fundamental nursing practice education. A nonequivalent control group was designed to conduct a pre-post test for this study. The participants were assigned to the experimental(n=84) or control group(n=76). Data was collected from March to June, 2016. The experimental group received education based on pre-learning and role learning using video for 13 weeks. On the other hand, the control group only received explanation-based education. Data was analyzed using ${\chi}^2-test$, independent t-test, and ANCOVA. There was a significant increase in rehearsal, metacognition, self-efficacy, and help seeking in the experimental group compared to those in the control group. Results of this study indicate that pre-learning and role learning using video were effective in enhancing students' ability in rehearsal, metacognition, self-efficacy, and help seeking sections.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.175-179
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• 2003

Convergence condition determines performance of iterative learning control (ILC), for example, convergence speed, remaining error, etc. Hence, the performance can be elevated and a feasible set of learning controllers grows if a less conservative condition is obtained. In the frequency domain, the $H_{\infty}$ norm of the transfer function between consecutive errors has been currently used to test convergence of a learning system. However, even if the convergence condition based on the $H_{\infty}$ norm has a clear property about monotonic convergence, it has a few drawbacks, especially in MIMO plants. In this paper, the relation between the condition and the monotonicity of convergence is clarified and a modified convergence condition is found out using a frequency domain Lyapunov equation, which supersedes the conventional one in the frequency domain.