• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.779-785
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• 2022

Study analyzes whether the 3D CAD class using the flipped learning-based PBL is effective in acquiring professional knowledge and nurturing talent. A Flipped Learning-based PBL class was implemented for 3rd grade students of Robot and Automation Engineering Major, Dong-Eui University, and a survey was conducted on satisfaction and effectiveness. The students seemed to be generally satisfied with the class, and the flipped learning-based PBL appeared to be effective in improving the competency required by companies. In particular, it is hoped that it will contribute to the use of video education in practical subjects in the future by proving that practical classes can be operated effectively even in non-face-to-face learning. Moreover, this study is an important indicator for future research and will be used as a quantitative indicator for class improvement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.174-176
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• 2022

In this paper, we present a mobile application for 'personalized customized learning' for children with articulation disorders using an artificial intelligence (AI) algorithm. A dataset (Data Set) to analyze, judge, and predict the learner's articulation situation and degree. In particular, we designed a prototype model by looking at how AI can be improved and advanced compared to existing applications from the UX/UI (GUI) aspect. So far, the focus has been on visual experience, but now it is an important time to process data and provide a UX/UI (GUI) experience to users. The UX/UI (GUI) of the proposed mobile application was to be provided according to the learner's articulation level and situation by using CRNN (Convolution Recurrent Neural Network) of DeepLearning and Auto Encoder GPT-3 (Generative Pretrained Transformer). The use of artificial intelligence algorithms will provide a learning environment with a high degree of perfection to children with articulation disorders, thereby enhancing the learning effect. I hope that you do not have any fear or discomfort in conversation by improving the perfection of articulation with 'personalized and customized learning'.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.75-81
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• 2022

Autonomous vehicles, which can dramatically solve the lack of parking spaces, are making great progress through deep reinforcement learning. Activation functions are used for deep reinforcement learning, and various activation functions have been proposed, but their performance deviations were large depending on the application environment. Therefore, finding the optimal activation function depending on the environment is important for effective learning. This paper analyzes 12 functions mainly used in reinforcement learning to compare and evaluate which activation function is most effective when autonomous vehicles use deep reinforcement learning to learn parking. To this end, a performance evaluation environment was established, and the average reward of each activation function was compared with the success rate, episode length, and vehicle speed. As a result, the highest reward was the case of using GELU, and the ELU was the lowest. The reward difference between the two activation functions was 35.2%.

• Smart Media Journal
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• v.13 no.5
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• pp.45-51
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• 2024

Recently, realistic contents such as virtual reality(VR) and augmented reality (AR) are widely used for education to provide beneficial learning environments with thee-dimensional(3D) information and interactive technology. Specially, AR technology will be helpful to intuitively understand by adding virtual objects registered in the real learning environment with effective ways. In this paper, we developed an AR learning system using 3D spatial information in the 2D based textbook for studying math related to geometry. In order to increase spatial learning effect, we applied to solid shapes such as prisms and pyramids in mathematics education process. Also, it allows participants to use various shapes and expression methods (e.g., wireframe mode) with interaction. We conducted the experiment with our AR system, evaluated achievement and interest. Our experimental study showed positive results, our results are expected to provide effective learning methods in various classes through realistic visualization and interaction methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• Journal of Korean Home Economics Education Association
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• v.33 no.2
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• pp.115-133
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• 2021

The purpose of this study is to develop a teaching-learning plans for middle school Home Economics that practices clothing life in response to climate change. Four steps of analysis, design, development, and evaluation were used for the research. 'Phenomenon and cause, impact (environmental, economic and social) and response (relaxation and adaptation)' were selected as educational content elements for climate change through reviewing the literature related to climate change. Six types of middle school Technology and Home Economics textbooks under the 2015 revised curriculum were analyzed using the selected content elements for climate change as the basis for analysis according to the data type(reading data, picture data, activity data) and clothing use cycle (production, purchase, use, and disposal). Based on the content elements of climate change in the clothing life area extracted through textbook analysis, a total of 12 teaching-learning plans in response to climate change were developed by utilizing various teaching and learning methods, data and media. The teaching-learning plans were designed based on an integrated understanding of the phenomena, causes, effects, and responses of climate change for the students to realize the seriousness of climate change and to exercise positive influence on families and society.

• The Journal of Korean Association of Computer Education
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• v.5 no.3
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• pp.45-58
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• 2002

In this paper, we propose the new approach with which user is able to retrieve the massive volume of learning contents in the multimedia learning system. In order to secure the compatibility of learning contents. we apply the SMIL on the basis of XML, so that the integration and the synchronization of multimedia components can be available to realize in the mode of standardization. We also implement the multimedia learning contents represented by the RDF on the IEEE LOM. We present the two step-retrieval method to get precise results. In the first step, user can find with high speed and ease whatever contents user wants to take a look through metadata in the system. The second step is followed that by using the time information of SMIL, user can retrieve the interest synchronous parts in the result of the first step. This innovative retrieval approach applied in the multimedia learning system is highly expected to make a meaningful contribution to implement the principles of self-directed learning in the learning environments, where user can use and revise the retrieval results for their own learning purpose and make further the active knowledge-reconstruction.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.171-182
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• 2006

Science education in elementary school is mostly based on solving investigative tasks conducted by small groups on the basis of the inquiry activities such as experiments, observations, etc. Students should be able to draw conclusions from experiments and observations through their collaborative interactions by exchanging ideas. If learners use the advantages of Blended-Learning as a new pedagogical method comprehending merits of both off-line and on-line learning to complement off-line activities throughout the entire process, the interactions among them may be reinforced, and they would take part in the inquiry learning more actively. Accordingly, the proposed system can help children foster science inquiry learning effectively by using on-line communication facilities to arrange learners' diverse opinions and thoughts coming from off-line inquiry activity process. The result shows that the system enhanced learners' interest about science inquiry learning and improved their learning achievements by exchanging diverse opinions via the Web communication facilities.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.77-86
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• 2005

In this paper, we designed a learning algorithm of LVQ that extracts classification errors and learns ones and improves classification performance. The proposed LVQ learning algorithm is the learning Networks which is use SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of LVQ. To extract pattern vectors which cause classification errors, we proposed the error-cause condition, which uses that condition and constructed the pattern vector space which consists of the input pattern vectors that cause the classification errors and learned these pattern vectors , and improved performance of the pattern classification. To prove the performance of the proposed learning algorithm, the simulation is performed by using training vectors and test vectors that are Fisher' Iris data and EMG data, and classification performance of the proposed learning method is compared with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional classification.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.37-45
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• 2018

The purpose of this study was to understand language learning strategies use, language learning beliefs, and listening achievement of Korean EFL learners. The participants was sixty-nine university students who enrolled in blended learning classes for English listening. Data was collected and analyzed to see if there were any differences in strategies and beliefs between students who improved their listening test score and those who did not. The results showed that students showing improvement at the post-test used more language learning strategies and had a high level of motivation. Statistically significant correlation was found between motivation and strategies such as cognitive and meta-cognitive strategies.