• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.542-559
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• 2020

This study was conducted to derive theoretical and practical implications in situations where innovation of the business is desperate in the face of the emergence of agile organizations and digital transformation. To do so, we tried to verify the correlation between negative feedback-seeking behavior and innovative behavior and whether the learning goal orientation of these two variables has a moderated mediating effect by coaching leadership. It analyzed the collected questionnaire from 381 members working in domestic companies; SPSS 25.0, AMOS 25.0, and Process Macro 3.0 were used. The analysis result showed that the negative feedback seeking behavior had a positive effect on the learning goal orientation, and the leader's coaching leadership found to have a moderating effect between the negative feedback seeking behavior and the learning goal orientation. Learning goal orientation has been found to have a moderated mediating effect between negative feedback seeking behavior and innovative behavior. This study is significant in the sense that it reveals the process of how members seeking negative feedback in the organization could be led to innovative behavior and shows the necessity of organizational support for coaching leadership for the vitalization of innovative behavior.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.317-322
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• 2019

Programming judge systems for programming training support are typically built on the Web, where the examiners uploads a programming problem, which the student reads and submits an answer to the problem. The judge system executes the submitted answer of source code to provide feedback such as pass, failure, and error messages. Students who receive the feedback except for the pass continues debugging the source code until they are judged to pass. We developed an online judge system to support programming training and analyzed answers submitted by the students and found that many of the students who were not judged to pass that test did not know exactly where they were wrong but continued to solve the problem. The current judge system generally feeds runtime error messages back to students. However, with only runtime error message, it is difficult for student who train to find the wrong part of the answer. Therefore, in this paper, we propose a system that provides the feedback of programming failure by analyzing the control flow of the test cases used in the source code submitted by the student. The proposed system helps students find the wrong parts more quickly by feeding back the paths where faults in the control flow may exist. In addition, we show that this system is applicable to the answer source code that the actual student submitted.

• Journal of the Korean School Mathematics Society
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• v.8 no.2
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• pp.249-271
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• 2005

The study was aimed to show effects of the newly step branch's feedback models on the mathematics underachievers' mathematics achievement and attitude toward the mathematics, extent of self-check. The subject are 26 mathematics underachievers in the End grade of H middle school located in Taejeon. They were divided into an experimental group and a control group, and the attribution disposition. Experiment group was provided step branch's feedback and control group was provided general formative' feedback. The duration of the treatment was over a period of six weeks. The result of study, the step branch's feedback was effects for increasing he mathematics achievement and attitude toward the mathematics than the general formative' feedback(p<.05). In addition, the step branch's feedback group had better extent of self-check than the general formative' feedback.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.133-152
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• 2004

As the Internet facilitates the rapid increase of information availability, the study on SDI service that provides users with relevant document in a timely manner has been developed. However, the practical use of this service has been low. This thesis aims at analyzing the reasons for this and developing relevance feedback based SDI system to improve the performance of the existing SDI system. Experimental systems that are developed for this study are SDI system based on users' minimum intervention feedback, SDI system based on perfect automation feedback, and SDI system based on users' maximum intervention feedback. The fourth system that utilizes the traditional SDI system is also studied to evaluate the level of performance improvement of the newly developed three types of SDI system. As a result of this study, SDI system based on users' maximum intervention feedback showed greatest performance improvement. The next performance improvement happened in order of SDI system based on perfect automation feedback, SDI system based on users' minimum intervention feedback, and the traditional SDI system. Feedback based systems showed greater performance improvement as they went through more feedback processes.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.407-409
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• 2017

지능형 튜터링 시스템(Intelligent Tutoring System, ITS)은 학습자에게 자동으로 학습코스를 제공하는 시스템으로, 현재 비전공자 대상 코딩 교육용 ITS 수요가 증가하고 있음에 따라 본 연구팀도 비전공자 대상 코딩 교육용 ITS "Everycoding"을 개발하였다. 더 나아가 학습자 별 맞춤형 코딩 교육 튜터링 시스템 개발 요구가 늘어나고 있다. 이에, 본 연구에서는 기계학습 기법을 적용하여 개발한 협업 능력 기반의 학습자 모델을 군집 분석하고, 그에 따른 학습자 별 맞춤 피드백을 제공하는 기준을 제안한다.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.231-232
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• 2011

마이크로티칭은 교사들의 모의수업을 녹화한 후 피드백, 평가, 성찰의 과정을 통하여 수업 스킬을 개선하는 교수-학습방법으로 교직수업 및 교원연수 등에 활용되고 있다. 그러나 마이크로티칭을 진행하는 데에는 상당한 시간적, 물리적 부담이 부가되며, 때문에 더욱 의미있는 학습, 평가와 성찰의 기회가 허락되지 않기도 한다. 따라서 이를 효율적, 효과적으로 지원할 수 있는 방안이 모색되어야 한다는 요구가 있다. 본 연구에서는 동영상 위키 시스템에 기반을 둔 마이크로티칭 지원도구를 개발하였다. 이 시스템은 텍스트, 음성 기반 피드백 기능을 지원하여 교수자의 피드백을 보다 원활하게 도우며, 동영상 위키의 속성을 활용하여 동료피드백을 지원하여 능동적 상호작용이 이루어질 수 있다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.2
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• pp.49-55
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• 2000

In this paper, we show that our previously proposed second-order iterative learning control method with feedback is more effective and has better convergence performance than the second-order iterative learning control method without feedback, particularly in the case of the existence of initial condition errors. Also the convergence proof of the proposed method is given. And through the simulation result of applying the proposed method to the linear time-varying system, we show that our proposed method has enhanced robustness and stability in case of the existence of initial condition errors.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5543-5552
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• 2014

The advancement of smart-phones and their market expansion has led to the development of numerous educational applications (apps). In this study, learning activities were designed for real-time feedback utilizing a smart clicker app for effective communication between the instructors and students, and to provide educational results, such as learning flow and academic achievement. These strategies were applied in the actual educational fields, and 70 college students were taking classes with the same curriculum. Experiments involving an experimental group and control group were conducted. The results of the t-test were follows. In terms of learning flow, a significant difference was observed between the two groups, but not in terms of academic achievement.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1561-1566
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• 2017

Due to the advances in machine learning and artificial intelligence technologies, many new services have become available. Among such services, recommendation systems have already been successfully applied to commercial services and made profits as in online shopping malls. Most recommendation algorithms in commercial services are based on content analysis or explicit feedback rates as in movie recommendations. However, many online shopping malls have difficulties in content analysis or are lacking explicit feedbacks on their items, which results in no recommendation system for their items. Even for such service systems, user log data is easily available, and if recommendations are possible with such log data, the quality of their service can be improved. In this paper, we extract implicit feedback like click information for items from log data and provide a recommendation system based on the implicit feedback. The proposed system is applied to a real in-service online shopping mall.