• The Journal of Korean Association of Computer Education
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• v.15 no.1
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• pp.43-53
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• 2012

The spread of smartphones, many educational applications have been developed. However, the existing educational applications, learning the simple and uniform, due to the way the needs of learners are given feedback after learning did not reflect the present problem is how. In this paper vocabulary learning applications to implement the existing application using the learners' needs, survey analysis, and analysis results to reflect the learner's motivation to continue the learners to self-built learning objectives according to the stages of learning tailored to the training schedule set up and made a systematic feedback learning vocabulary was designed and implemented applications.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1464-1468
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• 2004

This paper presents a learning controller for repetitive gait control of biped walking robot. We propose the iterative learning control algorithm which can learn periodic nonlinear load change ocuured according to the walking period through the iterative learning, not calculating the complex dynamics of walking robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of learning control to biped robotic motion is shown via dynamic simulation with 12-DOF biped walking robot.

• The Journal of Korean Association of Computer Education
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• v.4 no.1
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• pp.87-97
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• 2001

With coming information society and universal use of internet, we have been concerned about the educational utilization of the internet. Recognizing the growing need for the use of the internet in education, there are many research of WBI According to behaviorism learning theory, learning effects are extremely improved when immediate feedback is offered to learner. In this paper, we designed and implemented feedback BBS that offers immediately reponses to learner. The feedback BBS was implemented using PHP and MySQL. And we evaluated implemented feedback BBS by questionnaire.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.61-67
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• 2000

Generally, relevance, feedback reflecting user's intention has been used to refine the refine the query conditions in image retrieval. However, in this paper, the usage of the relevance feedback is extended to the image database categorization so as to be accommodated to the user independent image retrieval. In our approach, to guarantee a desirable user-satisfactory performance descriptors and the elements of the descriptors corresponding unique features associatiated with of each image are weighted using the relevance feedback where experts can more lead rather than beginners do. In this paper, we propose a proper image description scheme consisting of global information, local information, descriptor weights and element weights based on color and texture descriptors. In addition, we also introduce an appropriate learning method based on the reliability scheme preventing wrong learning from abusive feedback.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2567-2576
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• 1994

In this paper we propose a new method to determine the learning rates of fuzzy learning algorithm(FLA) in nonlinear MIMO system. The state feedback gains are used from the linearized system of the nonlinear MIMO system. Through this method, it is easy to determine the learing rates. And it is quarauteed the good convergence and confirmed the performance of FLA is better than that of linear controller(LC) through the simulation. Acrobatic robot system is selected as an example(one-input two-output system), and FLA is implemented through the experiment.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.171-179
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• 2008

This paper addresses the synthesis of an iterative learning controller for a class of linear systems with norm-bounded parameter uncertainties. We take into account an iterative learning algorithm with current cycle feedback in order to achieve both robust convergence and robust stability. The synthesis problem of the developed iterative learning control (ILC) system is reformulated as the ${\gamma}$-suboptimal $H_{\infty}$ control problem via the linear fractional transformation (LFT). A sufficient convergence condition of the ILC system is presented in terms of linear matrix inequalities (LMIs). Furthermore, the ILC system with fast convergence rate is constructed using a convex optimization technique with LMI constraints. The simulation results demonstrate the effectiveness of the proposed method.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.541-550
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• 2024

The aim of this study is to find a way to improve the effectiveness of feedback that can contribute to the development of government work evaluation through comparison of systems between Korea and the United States. To this end, this study compared and analyzed the cases of Korea and the United States in relation to the feedback system of political affairs evaluation. In the case of the United States, it was confirmed that it was linked to a relatively high level of the learning dimension of the feedback system of achieving and improving policy goals, while in Korea, such linkage was segmented and controlled. In the case of Korea, it was confirmed that the government work evaluation system was in power, and its purpose was to improve policies and to control the evaluation target rather than learning for it. In the case of the United States, it is noteworthy that the autonomy of its own ministries is guaranteed as much as possible, the clarity and achievement of the goals presented by the ministries are prioritized, and the feedback also has a support and learning system as a regular system, not an ex post system. It is necessary to focus on policy improvement that can be linked to the achievement of policy goals in government work evaluation. It is also necessary to take a quarterly monitoring system, but to transform the ex post evaluation system into a learning and supportive system that can achieve policy goals, not control.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.482-489
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• 2013

The purpose of this study was to identify the relationship of instructional design, perceived learning transfer, and satisfaction. The data were collected using questionnaire from the sample of 239 nursing students. The level of learning transfer was explained by introduction with learning context & providing guidance and initial attention. The level of learning transfer was explained by learning object with motivation, learning goal alignment, accessibility and feedback & adaptation. The level of program satisfaction was explained by introduction with learning context & providing guidance and initial attention. The level of program satisfaction was explained by learning object with motivation, presentation design, interaction availability, feedback & adaptation, learning goal alignment and contents quality. The findings serve as basic data to design e-Learning program to improve learning transfer and satisfaction.

• English Language & Literature Teaching
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• v.15 no.4
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• pp.237-264
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• 2009

The present study explores patterns of teachers' corrective feedback and learners' uptake in Korean EFL undergraduate classroom setting. It also examines consistencies and discrepancies in the perception of corrective feedback by teachers and learners. Teachers' and learners' preferences and perception of corrective feedback are further analyzed to determine whether or not those differ from actual practices in English language learning classrooms. The results of the study are as follows. First of all, teachers' corrective feedback type varied according to the learners' error type and English proficiency level. There was a lack of consistency between the teachers' feedback practices and the learners' error types. Second, for the phonological errors, learners' data witnessed the most frequent uptake on recast. For the other error types, however, the learners' uptake rates were high for the explicit corrective feedback. Third, the teachers' explicit knowledge of corrective feedback was rather low and the preferences differed from teacher to teacher. The teachers' feedback perception and preferences did not consistently reflect their actual practices. Finally, patterns of the learners' expectations of corrective feedback varied according to learners' proficiency level. Teachers' and learners' expectations of corrective feedback were also compared and some mismatches were detected.