• English Language & Literature Teaching
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• v.16 no.4
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• pp.133-152
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• 2010

There is disagreement, among researchers, on the benefits of corrective feedback on L2 learners' written output. Some scholars advocate the usefulness of corrective feedback while some claim that error correction is ineffective and even harmful. So far, however, research outcomes cannot settle this debate. Based on this debate, this study examines whether there is a difference among diverse types of feedback on the effects of L2 learners' writing improvement. This study found that teacher's direct feedback was more effective than any other types of feedback on the effect of participants' writing improvement. In particular, teacher's direct feedback helped their improvement on grammar, mechanics, and form. Among the types of peer feedback, self-correction was the most effective. In teacher feedback, form-focused feedback had more effects than content-focused feedback, but no difference with regard to peer feedback. In addition, teacher's content-focused feedback was more effective than peer's content-focused feedback. Overall, in all types of feedback, teacher feedback was more effective than peer feedback. However, direct (form-focused) feedback was the most effective in teacher feedback, and self-correction in peer feedback. The least effective feedback in both teacher and peer feedback was indirect (form-focused) feedback, which is simple underlining of errors.

• Educational Technology International
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• v.25 no.1
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• pp.1-25
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• 2024

This study aims to analyze the impact of learners' usability perceptions of topic modeling-based visual feedback and generative AI interpretation on reflection levels in online discussions. To achieve this, we asked 17 students in the Department of Korean language education to conduct an online discussion. Text data generated from online discussions were analyzed using LDA topic modeling to extract five clusters of related words, or topics. These topics were then visualized in a network format, and interpretive feedback was constructed through generative AI. The feedback was presented on a website and rated highly for usability, with learners valuing its information usefulness. Furthermore, an analysis using the non-parametric Mann-Whitney U test based on levels of usability perception revealed that the group with higher perceived usability demonstrated higher levels of reflection. This suggests that well-designed and user-friendly visual feedback can significantly promote deeper reflection and engagement in online discussions. The integration of topic modeling and generative AI can enhance visual feedback in online discussions, reinforcing the efficacy of such feedback in learning. The research highlights the educational significance of these design strategies and clears a path for innovation.

• Journal of Korea Trade
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• v.25 no.6
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• pp.57-77
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• 2021

Purpose - International strategic alliance has been regarded as a strategic decision made by firms' managerial problems and ensure performance growth. From the perspective of the proactive behavior for changing strategies in a global market, this study aims to identify whether performance feedback influences firms' decisions to pursue strategic alliances. This study examines the effects of performance feedback on performance when firms use strategic alliances. Design/methodology - To analyze the impact of performance feedback on forming an international strategic alliance, this study adopt the concept of performance feedback to develop a research model and our hypotheses. Thus, this study used a two-stage least squares unbalanced panel data analysis with random effects. This study is based on 24,543 observations from Korean manufacturing firms from 2007 to 2016. Findings - The results show that firms pursue the formation of strategic alliances more actively, if their past financial and R&D performance are lower than their aspiration level, based on the result of performance feedback. An in split sample analysis for examining the effect of a firm's technology sophistication based on the OECD's classification, negative innovation performance discrepancy has positive effects on the probability of international alliance in high-tech and medium-high-tech industries. Financial performance also improves when a firm decides to form a strategic alliance based on the results of performance feedback. Originality/value - This research extends recent efforts to better understand the effect of performance feedback on firms' performance when they use strategic alliances. These findings suggest that the CEOs and managers of firms should consider the performance feedback perspective when deciding to pursue a strategic alliance to improve performance. In other words, the decision-makers in a firm must analyze and consider various complex variables inside and outside the firm and expand such subjects of examination to more complex and dynamic factors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.906-911
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• 2005

In this paper, for spatial multiplexing with limited feedback, we propose subspace method based preceding in which the active bases are selected at the receiver from a finite number of basis sets Down at both receiving and transmitting ends, conveyed to the transmitter using limited feedback, and assembled into a preceding matrix at the transmitter. The selected bases are conveyed to the transmitter using feedback information on both the index of the selected basis set, which defines the most appropriate set of coordinates for describing a multiple-input multiple-output (MIMO) channel, and the principal bases maximizing the capacity in the selected basis set. We show that the proposed subspace method based preceding provides a capacity similar to that of the closed-loop MIMO even with limited feedback.

• Korean Journal of Clinical Pharmacy
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• v.27 no.2
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• pp.55-62
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• 2017

Experiential education is a core curriculum of pharmacy education. In experiential education, formative feedback is an integral component of learning and teaching process. Feedback is defined as information provided by a preceptor regarding student's performance based on direct observation. With effective feedback, students can have opportunities to reinforce or correct behaviors and to acquire knowledge or skills. Students highly value and appreciate feedback. They rank provision of effective feedback as one of the most important qualities of preceptors. Preceptors, however, lack an understanding of feedback or practical skills necessary for providing effective feedback. As a result in reality, the feedback provided to students can be differentially effective in improving students' learning. This article describes a theoretical understanding of feedback including definition and value, as well as types of feedback. In addition, practical aspects in providing feedback, such as contents, timing, techniques, and models, are addressed. By understanding the value of feedback and mastering various feedback skills, preceptors will promote students' learning and enhance educational outcomes of experiential education.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• ETRI Journal
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• v.29 no.5
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• pp.700-702
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• 2007

We present a relevance feedback approach based on multi-class support vector machine (SVM) learning and cluster-merging which can significantly improve the retrieval performance in region-based image retrieval. Semantically relevant images may exhibit various visual characteristics and may be scattered in several classes in the feature space due to the semantic gap between low-level features and high-level semantics in the user's mind. To find the semantic classes through relevance feedback, the proposed method reduces the burden of completely re-clustering the classes at iterations and classifies multiple classes. Experimental results show that the proposed method is more effective and efficient than the two-class SVM and multi-class relevance feedback methods.

• Journal of Educational Research in Mathematics
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• v.12 no.3
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• pp.313-329
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• 2002

The importance of professor's outline in a feedback instruction was examined through various documents and the way in which the evaluation was fulfilled in Korean educational environment and its reflection upon the evaluation result were investigated by means of research. Based upon the survey results in connection with the progress and basis of teachers' on the spot feedback mathematics instruction in schools, it was found that most of teachers who engaged in feedback mathematics instruction were going over the most frequently missed problems. I proposed that we should bring up the point at issue and grasp its tendency of a class and entire group's results by means of a relative comparative analysis method, and thereupon establish a fixed category and choose substantial feedback scholarship according to that category. From this basis, the sub-sequent research topics include the substantial feedback effects of the selected problems that should be given priority, a group analysed and classified by means of comparison of tendency as well as feedback outline depended on students' characteristic, and the determining factors of tendency(a condition of professors, a level of students, geographical difference(s), and gender difference(s), etc...).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.852-857
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• 2008

A new adaptive neuro-control algorithm for a SISO strict-feedback nonlinear system is proposed. All the previous adaptive neural control algorithms for strict-feedback nonlinear systems are based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semi-global sense.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1353-1361
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• 2018

With the availability of real-time educational data collection and analysis techniques, the education paradigm is shifting from educator-centric to data-driven lectures. However, most offline and online education frameworks collect students' feedback from question-answering data that can summarize their understanding but requires instructor's attention when students need additional help during lectures. This paper proposes a content restructure recommendation framework based on collected student feedback. We list the types of student feedback and implement a web-based framework that collects both implicit and explicit feedback for content restructuring. With a case study of four-week lectures with 50 students, we analyze the pattern of student feedback and quantitatively validate the effect of the proposed content restructuring measured by the level of student engagement.