• Journal of Industrial Technology
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• v.24 no.A
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• pp.99-107
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• 2004

This paper considers reinforcement learning control with the self-organizing map. Reinforcement learning uses the observable states of objective system and signals from interaction of the system and the environments as input data. For fast learning in neural network training, it is necessary to reduce learning data. In this paper, we use the self-organizing map to parition the observable states. Partitioning states reduces the number of learning data which is used for training neural networks. And neural dynamic programming design method is used for the controller. For evaluating the designed reinforcement learning controller, an inverted pendulum of the cart system is simulated. The designed controller is composed of serial connection of self-organizing map and two Multi-layer Feed-Forward Neural Networks.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.6-10
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• 1996

This paper presents an overview of research results obtained by the authors in a series of publications. Methods are developed both for time-varying and time-invariant for linear and nonlinear. for time domain and frequency domain . and for discrete-time and continuous-time systems. Among the topics presented are: 1. Learning control based on integral control concepts applied in the repetition domain. 2. New algorithms that give improved transient response of the indirect adaptive control ideas. 4. Direct model reference learning control. 5 . Learning control based frequency domain. 6. Use of neural networks in learning control. 7. Decentralized learning controllers. These learning algorithms apply to robot control. The decentralized learning control laws are important in such applications becaused of the usual robot decentralized controller structured.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.353-360
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• 2004

This paper considers reinforcement learning control with the self-organizing map. Reinforcement learning uses the observable states of objective system and signals from interaction of the system and environment as input data. For fast learning in neural network training, it is necessary to reduce learning data. In this paper, we use the self-organizing map to partition the observable states. Partitioning states reduces the number of learning data which is used for training neural networks. And neural dynamic programming design method is used for the controller. For evaluating the designed reinforcement learning controller, an inverted pendulum on the cart system is simulated. The designed controller is composed of serial connection of self-organizing map and two Multi-layer Feed-Forward Neural Networks.

• Journal of Elementary Mathematics Education in Korea
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• v.10 no.1
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• pp.67-87
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• 2006

This study is to recognize a problem in the practice of performance assessment in elementary school, and to find out some suggestive points for improvement of teaching·learning method in elementary mathematics through assessment by reducing time restriction according to assessment through the practice of self-assessment, peer-assessment and observation, and then by reflecting the results of assessment on teaching learning plan. For that, the questions of study set up are as follows ; 1. How should self-assessment and peer-assessment be applied to in elementary mathematics assessment? 2. How should the time for 'let's play an interesting game' be managed for assessment of elementary mathematics? 3. How should the results of assessment be reflected on the Process of teaching and learning of mathematics? To solve these problems, a researcher of this thesis performed self-assessment, peer-assessment on 40 students of second grade under her charge as a class teacher, and applied observation in the time management process for 'let's play an interesting game' for a semester. self-assessment was made by mathematics journal, self-assessment chart, peer-assessment was by the analysis of conversation record among students in the situations of assessment, and observation was by observation of activity when playing with the results data of play analyzed. the concrete methods of application as follows ; First, mathematics journal was applied $1{\sim}2$ times by each unit with reconstruction into the level of second grade on the basis of the preceding-study models. Second, peer-assessment was applied to the unit-assessment time and the play-activities time by the method of recording·analyzing the contents of conversation among students in the process of assessment. Third, mathematical attitude & dispositions of students making use of the self- assessment table were examined referring to the teaching learning plan. Fourth, the time management for 'let's play an interesting game' was made through the prior recognition of play method and the joyful play-activities by use of the play-plate. Assessment depended on analysis of play-activities results of students making use of an observation form. Fifth, the results of self-assessment, peer-assessment, and observation were analyzed, and then they were made use of as self-observation data, of teacher her/his self, or teaching·learning improvement data. Students' self-assessment datum (mathematics diary, self-assessment sheets, conversation contents in the process of assessment) and observation materials (check lists, Play-activity result materials, conversation contents in the process of play) obtained in the process of application was analyzed as follows ; 1. From the practice of self-assessment in form of mathematics journal, I could obtain not only datum showing how much students was understanding the learning aims by unit time and to any degree they reached but also information about their response to learning datum and favorable type of learning. 2. Assessment by self-assessment chart was useful in planning the mathematics teaching learning process because it helps ascertain mathematical attitude & dispositions of students. 3. Through the application of peer-assessment, students had the opportunity of communicating with other students looking back on his/her explaining process, and teachers could obtain basic materials for assessment of students. 4, In case of time management for 'let's play an interesting game', there was natural extension of play made through time-security by prior looking into the method of play-activity, and then, for a remained time, by making children play a new game. 5, I could easily record the activities of students by use of the observation. form, and make use of it as basic data for descriptive assessment. 6, Each kinds of data obtained from the results of assessment was helpful for securing self-observation materials in the process of teaching learning and for their betterment in mathematics subject. However, because they were in the second grade of elementary school and there was an individual difference, some students could not make use of mathematics diary or self-assessment form properly. In case of these students, assessment data would be obtained through interview or observation. And for effective operation of play, its purpose & method and matters that demand special attention when play-acting should be clearly guided. Also, when applying an effective play in addition to play activities in textbook, to lessons, interesting mathematics lessons could be guided.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.221-228
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• 2006

With the increasing use of the Internet improved Internet technologies as well as web-based applications, the effectiveness assessment of e-Learning has become one of the most practically and theoretically important issues in both Educational Engineering and Information Systems. This study suggests a research model, based on an e-Learning success model, the relationship of the e-learner's self-regulated learning strategy and the quality perception of the e-Learning environment. This research model focuses on the learning environment and on e-learning strategy. The former consists of learning management system, learning content quality and service quality that are provided by e-Loaming. The latter refers to the learners' self-regulated learning strategy. We will show the validity of the model empirically.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.412-419
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• 2022

The amount of digital text data is growing exponentially, and many machine learning solutions are being used to monitor and manage this data. Artificial intelligence and machine learning are used in many areas of our daily lives, but the underlying processes and concepts are not easy for most people to understand. At a time when many experts are needed to run a machine learning solution, no-code machine learning tools are a good solution. No-code machine learning tools is a platform that enables machine learning functions to be performed without engineers or developers. The latest No-Code machine learning tools run in your browser, so you don't need to install any additional software, and the simple GUI interface makes them easy to use. Using these platforms can save you a lot of money and time because there is less skill and less code to write. No-Code machine learning tools make it easy to understand artificial intelligence and machine learning. In this paper, we examine No-Code machine learning tools and compare their features.

• The Journal of Korean Academic Society of Nursing Education
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• v.17 no.3
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• pp.355-364
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• 2011

Purpose: This study was designed to explore the influencing factors on self-directed learning ability of nursing students and to investigate the relationship between learning style, learning attitude, and self-directed learning ability. Methods: The study sample was composed of 263 nursing students. Data were collected from March 8th to April 7th, 2011 using a questionnaire which included Kolb's learning style inventory, learning attitude inventory, and self-directed learning ability inventory. Results: Learning styles of the subjects were assimilator 33.8%, converger 31.9%, accommodator 24.7%, and diverger 9.5%. There was no significant difference in learning styles among grades. However, the total mean score of learning attitude (F=8.30, p<.001) and self-directed learning ability (F=2.85, p=.038) significantly differed among grades. Learning attitude positively correlated to self-directed learning ability (r=.62, p<.001). Learning attitude was the most significant predictor and accounted for 36.5% of the variance in self-directed leaning ability in nursing students. Conclusion: It is important for students to use all four learning styles rather than to rely solely on one style. There should be more emphasis placed on the development of positive learning attitude and self-directed learning ability of nursing students.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.647-654
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• 2023

Deep Learning is a useful method for classifying and recognizing complex data such as images and text, and the accuracy of the deep learning method is the basis for making artificial intelligence-based services on the Internet useful. However, the vast amount of user da vita used for training in deep learning has led to privacy violation problems, and it is worried that companies that have collected personal and sensitive data of users, such as photographs and voices, own the data indefinitely. Users cannot delete their data and cannot limit the purpose of use. For example, data owners such as medical institutions that want to apply deep learning technology to patients' medical records cannot share patient data because of privacy and confidentiality issues, making it difficult to benefit from deep learning technology. In this paper, we have designed a privacy preservation technique-applied deep learning technique that allows multiple workers to use a neural network model jointly, without sharing input datasets, in multi-party system. We proposed a method that can selectively share small subsets using an optimization algorithm based on modified stochastic gradient descent, confirming that it could facilitate training with increased learning accuracy while protecting private information.

• Journal of The Korean Association of Information Education
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• v.5 no.3
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• pp.415-431
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• 2001

Recently, the biggest interest in education, education using ICT(Information and Communication Technology) is being emphasized excessively and only the practical side is being embossed on the research about it, so it is causing worry that it is inclined to technical use. In this study, we tried to prepare the strategy for efficient use of ICT in search of theoretical level on use of ICT as an alternative plan for these problems. First, we defined the concept of efficient use of ICT and fixed high thinking of human as basic authority cited for deduction of strategy and analyzed Integrated Thinking Model of Iowa State Dept. of Education. We categorized synthetic thinking for efficient use of ICT through these works. In addition, we classified ICT for efficient use into software area, hardware area, and use skill area, and observed each concepts and interrelationship. And we argued 'Decision Authority of Relation between Thinking Area and ICT Area' to examine relation between synthetic thinking category and each area of ICT, and we established concretization of that, 'Analysis Matrix for Deduction of ICE-EUS'. We tried to guarantee the propriety of deduction process and the clearness of deduction result through this works. Through this process we finally deduct the ICT-EUS(Efficient-Use Strategy of ICT) about learning resources, learning tools, tutee, searching, communication, production and presentation of ICT area. ICT-EUS is expected to provide possibility of being able to enhance the efficiency and effectiveness of achievement of learning goals through cognitive analysis about learning resources, tools and use skills beyond simple use of ICT.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.263-285
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• 2022

This study presented the factor analysis on constructing the new factors affecting the middle school students' online learning behaviors from the questionnaires employed among middle school students. A total of 204 students participated and the data were collected in South Korea. The sample of middle school ninth-grade students was selected and used through purposive sampling. Findings from the factor analysis provided evidence for the eight-factor solution for the 35-items accounting for 66.15% of the shared variance. A wide range of factors has been considered to identify students' online learning behaviors. The appropriate experience and use of e-learning in the middle school period is also important as it will be a critical stepstone for future education. This research provides information that has been taken into account for advancing online learning to enhance the quality of e-learning systems for middle school students. The study results provided eight new factors affecting the middle school students' online learning behaviors; that is 1) communication using social media as a learning tool, 2) intention to share information using ICT, 3) addiction of technology, 4) adoption of technology, 5) seeking information using ICT, 6) use of social media learning, 7) information search using ICT, and 8) immersion of technology. This study confirmed that middle school students prefer communication using social media as a learning tool, and value intention to share information using ICT for the most part. The data obtained based on factor analysis can highlight the online learning behaviors towards a mixture of social media learning and ICT to ensure a new educational platform for the future of e-learning. This research expects to be useful for both middle schools of online learning to better understand students' online learning behaviors and design online learning environments and information professionals to better assist students who particularly need digital literacy.