• School Mathematics
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• v.6 no.1
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• pp.37-57
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• 2004

The purpose of this study is to review, through case study, how the use of web materials has influence on the improvement of self-oriented Learning in mathematics of primary school. This is one of the ways to improve classroom lectures suggested in the 7th National Standard of Curriculum. To accomplish this, the following three studies were conducted. First, a questionnaire concerning the improvement of self-oriented Learning Skill through the use of the materials on the web was designed and analyzed. Second, the activities of the class using the web materials were recorded and the study activities of the children were observed. Third, the process of writing notes about their study using web materials was analyzed though interviews after teaching and learning. Through these studies, it has been shown how web materials contribute to the improvement of self-oriented Learning Skill.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.615-619
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• 2021

This study focuses on memory systems that are optimized to increase performance and energy efficiency in many embedded systems such as IoT, cloud computing, and edge computing, and proposes a performance improvement technique. The proposed technique improves memory system performance based on machine learning algorithms that are widely used in many applications. The machine learning technique can be used for various applications through supervised learning, and can be applied to a data classification task used in improving memory system performance. Data classification based on highly accurate machine learning techniques enables data to be appropriately arranged according to data usage patterns, thereby improving overall system performance.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.306-319
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• 2018

The purpose of this study is to improve a good sense of language through professors' reduced role and university students' cooperative learning with overcoming the limit of existing English teaching materials and learning methods. To analyze the effect of cooperative learning in university general English classes on the improvement of English speaking ability and affective achievement, cooperative learning for English speaking was applied to 50 university students of K university in Seoul for 4 months from March 2 to June 20 in 2018. And then the affective achievement was verified. The results of this study are as follows. Frist, the cooperative learning in university general English classes made a difference in the improvement of English speaking ability (accuracy, fluency, complexity). Second, the cooperative learning in university general English classes made a difference in confidence of learning and interest in learning among the affective achievement but there's no difference in study attitude and learning motivation. Third, the cooperative learning in university general English classes made a difference in the effect of the improvement of English speaking ability (accuracy, fluency, complexity) on the confidence of learning and interest in learning of the affective achievement, but there's no difference in study attitude and learning motivation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.103-113
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• 2018

The purpose of this study supports the establishment of national e-learning policy by analyzing e-learning status and current status of higher education. Enhance the competitiveness of higher education through sharing information between universities. And to improve e-learning quality management. We surveyed the current status of e-learning in 341 universities and questionnaires about e-learning content, e-learning application form, e-learning platform status was surveyed through each school's learning management system. As a result, the infrastructure of e-learning, the rate of platforms secured, and the contents are increasing gradually each year; however, still, not all students can receive the services equally. Dedicated servers and learning management systems were secured by more than 70% of general universities. In the current development status of e-learning content, multimedia, animation, and text forms are gradually decreasing, but video contents are increasing every year. Most of the online contents were used in the e-learning contents by application type, and blended learning, flipped learning, and mooc is not yet actively used since they are still in the beginning stage. Learning analysis techniques should be supported in order to easily use online learning contents such as flipped learning and mooc. We suggest that the effectiveness of e-learning should be measured and the current state of learning analysis for customized learning should be done. This study aims to contribute to the improvement of competitiveness of higher education by sharing information about e-learning among universities as a basis for improvement of e-learning policy. Future tasks are to improve the customized learning environment by adding whether the system environment for learning analysis is provided at the time of the survey.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.203-210
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• 2023

As the environment changes become more complex, learners should establish the learning strategy for the 4th industrial era and the post-COVID-19, also change. This paper focuses on the importance of self-regulated learning. Through this learning strategy, learners will form more positive attitudes and reduce negative attitudes toward the 4th industrial era. This attitude change will lead to an improvement in learners' career decision-making efficacy as a sense of future efficacy. As a result of the study, it was demonstrated that self-regulated learning improves career decision-making efficacy through the mediating effect of positive attitude formation toward the fourth industry. This article emphasizes the necessity of self-regulated learning as a valid learning strategy for the new era. The effect of self-regulated learning is explained as an improvement in attitude toward the future and a sense of efficacy. Through this learning strategy, learners' future performance could be improved.

• The Journal of Information Technology
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• v.12 no.4
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• pp.33-37
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• 2009

This paper analyzed effects Web-Based cooperation Learning have on improvement in Social Adaptability and problematic behavior, using Web-Based cooperation Learning system that is designed for Mental retardation children. Is Made Teaching Design according to students level, based on elementary school Bareunsaenghwal subject. Teaching and Learning program that is going with flash and PPT Embodied is. Designed to bulletin the evaluation data for cooperation studying after studying a part of the lesson. Verification of learning effect went with experimental group and comparison group consisted of groups of 8. Students studied the Internet web data and Teaching material paper and they took pencil test. As a result, point of post-inspection was higher than that of pre-inspection. Web-Based cooperation Learning is confirmed to be effective on Social Adaptability and problematic behavior improvement.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1793-1802
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• 2017

In the recent years, IT and Network Technology has rapidly advanced environment in accordance with the needs of the times, the usage of the smart learning service is increasing. Smart learning is extended from e-learning which is limited concept of space and place. This system can be easily exposed to the various security threats due to characteristic of wireless service system. Therefore, this paper proposes the improvement methods of smart learning system security by use of faults analysis methods such as the FTA(Fault Tree Analysis) and FMECA(Failure Mode Effects and Criticality Analysis) utilizing the consolidated analysis method which maximized advantage and minimized disadvantage of each technique.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.198-207
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• 2023

Responding to changes in artificial intelligence models and the data environment is crucial for increasing data-learning accuracy and inference stability of industrial applications. A learning model that is overfitted to specific training data leads to poor learning performance and a deterioration in flexibility. Therefore, an early stopping technique is used to stop learning at an appropriate time. However, this technique does not consider the homogeneity and independence of the data collected by heterogeneous nodes in a differential network environment, thus resulting in low learning accuracy and degradation of system performance. In this study, the generalization performance of neural networks is maximized, whereas the effect of the homogeneity of datasets is minimized by achieving an accuracy of 99.7%. This corresponds to a decrease in delay time by a factor of 2.33 and improvement in performance by a factor of 2.5 compared with the conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.861-880
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• 2023

Semantic segmentation of road scene is the key technology of autonomous driving, and the improvement of convolutional neural network architecture promotes the improvement of model segmentation performance. The existing convolutional neural network has the simplification of learning knowledge and the complexity of the model. To address this issue, we proposed a road scene semantic segmentation algorithm based on multi-task collaborative learning. Firstly, a depthwise separable convolution atrous spatial pyramid pooling is proposed to reduce model complexity. Secondly, a collaborative learning framework is proposed involved with saliency detection, and the joint loss function is defined using homoscedastic uncertainty to meet the new learning model. Experiments are conducted on the road and nature scenes datasets. The proposed method achieves 70.94% and 64.90% mIoU on Cityscapes and PASCAL VOC 2012 datasets, respectively. Qualitatively, Compared to methods with excellent performance, the method proposed in this paper has significant advantages in the segmentation of fine targets and boundaries.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.457-460
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• 1989

In this paper, an improvement of the EBP(error back propagation) learning speed using an acceleration algorithm is described. Using an acceleration algorithm known as the Partan method in the gradient search algorithm, learning speed is 25% faster than the original EBP algorithm in the simulaion results.