• Journal of the Korean earth science society
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• v.25 no.6
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• pp.409-417
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• 2004

This study investigated the effects and development of instruction module using ICT on earth field at elementary school science. The effects by 5th graders appeared as follows; First. ICT-applied teaching method proved to enhance the science teaming achievement regardless of their grades compared to the ordinary one. Second, Instruction module using ICT devoted to improve 'self-directed learning characteristics' at all grades by comparition of the ordinary teaching method. The 5th graders showed the improvements in the fields of' openness', 'self-conception', 'initiative', 'future inclination', 'creativity', 'self-assessment ability' all of which belong to self-directed teaming characteristics. They did not, however, show meaningful effect on improving 'learning eagerness' and 'responsibility' improvement. Thirdly, ICT-applied teaching method proved that it is more effective for developing 'creativity' than the ordinary one at all sample grades. The effectiveness was presented highly at 'fluency', 'originality' all of which belong to creativity. They did not, however, show meaningful effect on improving 'flexibility'.

• Journal of Korean Elementary Science Education
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• v.21 no.1
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• pp.111-125
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• 2002

The aim of this study is to make it sure how pupils' science inquiry skills and attitude are influenced when they are taught by using the work-sheets for the differentiated learning according to their ability. In order to accomplish this aim, two classes of the fourth grade in the elementary school were distinguished into two groups: one was the experimental class and the other, the comparative class. The experimental class was given 52 hours of science lessons using the above sheets, and the comparative class, the general method of teaching. In order to compare their scientific interest and learning ability of the two groups each other, pupils were tested the standardized achievement in advance. The two groups were also given "ex post facto test" to measure the variation of their inquiry skills and attitude after the lessons. In addition, the experimental class was tested to measure their learning attitude after they are teamed the science with the sheets. The results of this study are as follows: 1. According to the percentile statistics of the science inquiry skills test between the two groups, the work-sheets for the differentiated teaming helped pupils develope their inquiry skills remarkably. 2. The work-sheets did not lead to significant difference between the learning ability of boys and girls. 3. The science lesson using the work-sheets showed positive influences in increasing pupils' scientific attitude. 4. About 77.2 percent of pupils accepted the excellent records of the evaluation in the science lesson using the sheets. It can be, therefore, concluded that the science lesson using the work-sheets for differentiated teaming is one of effective science lessons to increasing pupils' science inquiry skills, compared with the general teaching method.

• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.290-297
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• 2002

The appearance of web technology has accelerated the role of the application of multimedia technology, computer communication technology and multimedia application contents. Recently WBI model which is based on web has been proposed in the part of the new activity model of teaching-teaming. How to learn and evaluate is required to consider individual learner's learning level. And it is recognized that the needs of the efficient and automated education agents in the web-based instruction is increased But many education systems that had been studied recently did not service fluently the courses which learners had been wanting and could not provide the way for the learners to study the learning weakness which is observed in the continuous feedback of the course. In this paper we propose design of multi-module system for course scheduling of learner-oriented using weakness analysis algorithm. First proposed system monitors learner's behaviors constantly, evaluates them, and calculates his accomplishment and weakness. From this weakness the multi-agent prepares the learner a suitable course environment to strengthen his weakness. Then the learner achieves an active and complete teaming from the repeated and suitable course.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.353-363
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• 2008

A multi-agent system has a longer learning period and larger state-spaces than a sin91e agent system. In this paper, we suggest a new method to reduce the learning time of Nash Q-learning in a multi-agent environment. We apply Macro-actions to Nash Q-learning to improve the teaming speed. In the Nash Q-teaming scheme, when agents select actions, rewards are accumulated like Macro-actions. In the experiments, we compare Nash Q-learning using Macro-actions with general Nash Q-learning. First, we observed how many times the agents achieve their goals. The results of this experiment show that agents using Nash Q-learning and 4 Macro-actions have 9.46% better performance than Nash Q-learning using only 4 primitive actions. Second, when agents use Macro-actions, Q-values are accumulated 2.6 times more. Finally, agents using Macro-actions select less actions about 44%. As a result, agents select fewer actions and Macro-actions improve the Q-value's update. It the agents' learning speeds improve.

• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.87-94
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• 2006

Internet makes it possible to access anytime, anywhere learning and so many LMS(Learning Management Systems) serve web based learning. But LMS has not flexible and qualified metadata to offer customired teaming. So we need extensible and flexible techniques which make if possible to define and share advanced teaming metadata. This paper presents an approach for implementing advanced learning metadata in LMS using RDF and the Semantic Web language. So we will first sketch the learning scenario in Semantic Web environment and structure of metadata management. Next we suggest two types of RDF authoring tool and search RDF documents. Advanced metadata management techniques enables the organization of learning materials around small pieces of semantically annotated learning objects. With these metadata learner can customize learning courses, improve retrieval performances.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.53-63
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• 2004

Recurrent-Cascade-Correlation(RCC) is a supervised teaming algorithm that automatically determines the size and topology of the network. RCC adds new hidden neurons one by one and creates a multi-layer structure in which each hidden layer has only one neuron. By second order RCC, new hidden neurons are added to only one hidden layer. These created neurons are not connected to each other. We present a generalization of the RCC Architecture by combining the standard RCC Architecture and the second order RCC Architecture. Whenever a hidden neuron has to be added, the new RCC teaming algorithm automatically determines whether the network topology grows vertically or horizontally. This new algorithm using sigmoid, tanh and new activation functions was tested with the morse-benchmark-problem. Therefore we recognized that the number of hidden neurons was decreased by the experiments of the RCC network generalization which used the activation functions.

• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.804-816
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• 2007

Sample training data for machine learning often contain irrelevant information or redundant concept. It is also the case that the original data may include noise. If the information collected for constructing learning model is not reliable, it is difficult to obtain accurate information. So the system attempts to find relations or regulations between features and categories in the teaming phase. The feature selection is to remove irrelevant or redundant information before constructing teaming model. for improving its performance. Existing feature selection methods assume that the distribution of documents is balanced in terms of the number of documents for each class and the length of each document. In practice, however, it is difficult not only to prepare a set of documents with almost equal length, but also to define a number of classes with fixed number of document elements. In this paper, we propose a new feature selection method that considers the impurities among the words and unbalanced distribution of documents in categories. We could obtain feature candidates using the word impurity and eventually select the features through unbalanced distribution of documents. We demonstrate that our method performs better than other existing methods via some experiments.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.213-217
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• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle) which has been developed by KARI (Korea Aerospace Research Institute). For teaming the NN, a BPN with one hidden, one input and one output layer was used. The input layer had seven neurons of variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer used 6 neurons of degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine. Database for network teaming and test was constructed using a gas turbine performance simulation program. From application results for diagnostics of the PW206C turboshaft engine using the learned networks, it was confirmed that the proposed diagnostics algorithm could detect well the single fault types such as compressor fouling and compressor turbine erosion.

• The Journal of the Acoustical Society of Korea
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• v.19 no.6
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• pp.62-70
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• 2000

In usual language models(LMs), the probability has been estimated by selecting highly frequent words from a large text side database. However, in case of adopting LMs in a specific task, it is unnecessary to using the general method; constructing it from a large size tent, considering the various kinds of cost. In this paper, we propose a construction method of LMs using a small size text database in order to be used in specific tasks. The proposed method is efficient in increasing the low frequent words by applying same sentences iteratively, for it will robust the occurrence probability of words as well. We carried out continuous speech recognition(CSR) experiments on 200 sentences uttered by 3 speakers using LMs by iterative teaming(IL) in a air flight reservation task. The results indicated that the performance of CSR, using an IL applied LMs, shows an 20.4% increased recognition accuracy compared to those without it. This system, using the IL method, also shows an average of 13.4% higher recognition accuracy than the previous one, which uses context-free grammar(CFG), implying the effectiveness of it.

• Journal of the Korea Computer Industry Society
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• v.8 no.4
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• pp.207-220
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• 2007

Recording to development of info-communication, recent educational paradigm asks not for a passive transmitter but an active constructor who can solve the various complicated problems in real situations. Such a change asks for the educational setting which includes sharing ideas and information rather than possessing them by themselves. Learning through presentation has many problems which are few chances of presentation as well as reusing of presentation data. etc. This study suggested the strategy which are promoting interactions through presentation class and using practically. For this, role of the presentation data provider and learner was suggested, also strategies to implement of the presentation learning support system step by step. Through the strategy of this paper could maintain the active communicating relationship between the learners. Without the limitation of the time and space, the real time communication is made while looking at the presentation data of the other party, the teaming effect by the presentation teaming strategy is expected to be high.