• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.699-701
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• 2004

This paper proposes the algorithm of servo- writing based on feedback error learning neural networks. The controller consists of feedback controller using PID and feedforward controller using gaussian radial basis function network. Because the RBFNs are trained by on-line rule, the controller has adaptation capability. The performance of the proposed controller is compared to that of conventional PID controller. Proposed algorithm shows better performance than PID controller.

• Korean Journal of Cognitive Science
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• v.28 no.1
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• pp.65-90
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• 2017

Rewards or penalties become informative only when contingent on an immediately preceding response. Our goal was to determine if the brain responds differently to motivational events depending on whether they provide feedback with the contingencies effective for learning. Event-related fMRI data were obtained from 22 volunteers performing a visuomotor categorical task. In learning-condition trials, participants learned by trial and error to make left or right responses to letter cues (16 consonants). Monetary rewards (+500) or penalties (-500) were given as feedback (learning feedback). In random-condition trials, cues (4 vowels) appeared right or left of the display center, and participants were instructed to respond with the appropriate hand. However, rewards or penalties (random feedback) were given randomly (50/50%) regardless of the correctness of response. Feedback-associated BOLD responses were analyzed with ANOVA [trial type (learning vs. random) x feedback type (reward vs. penalty)] using SPM8 (voxel-wise FWE p < .001). The right caudate nucleus and right cerebellum showed activation, whereas the left parahippocampus and other regions as the default mode network showed deactivation, both greater for learning trials than random trials. Activations associated with reward feedback did not differ between the two trial types for any brain region. For penalty, both learning-penalty and random-penalty enhanced activity in the left insular cortex, but not the right. The left insula, however, as well as the left dorsolateral prefrontal cortex and dorsomedial prefrontal cortex/dorsal anterior cingulate cortex, showed much greater responses for learning-penalty than for random-penalty. These findings suggest that learning-penalty plays a critical role in learning, unlike rewards or random-penalty, probably not only due to its evoking of aversive emotional responses, but also because of error-detection processing, either of which might lead to changes in planning or strategy.

• Journal of the Korean School Mathematics Society
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• v.10 no.1
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• pp.71-89
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• 2007

The present study was investigate the effects of feedback on mathematical achievement and attitude toward mathematics. Referring to the improvement of mathematics achievement, feedback groups(group I and II) turns out to be more efficient than the normal learning group(group III)(p<.05), there found no significant differ between group I and II(p>.05). As for the poor level of mathematics achievement, feedback groups(group I and II) turns out to be more efficient than the normal learning group(group III)(p<.05), there for fine level, found no significant differ between feedback group(group I and II)and the normal learning group(group III)(p>.05). Referring to the improvement of attitude toward mathematics, feedback groups(group I and II) turns out to be more efficient than the normal learning group(group III)(p<.05), there found no significant differ between feedback groups(group I and II)and the normal learning group(group III)(p>.05). As for the level(find or poor) of mathematics achievement, feedback groups(group I and II) turns out to be more efficient than the normal learning group(group III)(p<.05), there found no significant differ between feedback group(group I and II) and the normal learning group(groupIII)(p>.05).

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.4
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• pp.577-586
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• 2014

Purpose: This study investigates patterns of small group interaction and examines the influence among graduate nursing students of online collaborative learning strategies on small group interaction patterns, task performance and learning attitude in web-based team learning environments. Method: To analyze patterns of small group interaction, group discussion dialogues were reviewed by two instructors. Groups were divided into two categories depending on the type of feedback given (passive or active). For task performance, evaluation of learning processes and numbers of postings were examined. Learning attitude toward group study and coursework were measured via scales. Results: Explorative interactions were still low among graduate nursing students. Among the students given active feedback, considerable individual variability in interaction frequency was revealed and some students did not show any specific type of interaction pattern. Whether given active or passive feedback, groups exhibited no significant differences in terms of task performance and learning attitude. Also, frequent group interaction was significantly related to greater task performance. Conclusion: Active feedback strategies should be modified to improve task performance and learning attitude among graduate nursing students.

• 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.

• Journal of Engineering Education Research
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• v.20 no.3
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• pp.42-49
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• 2017

This study is about the influence of recording reflective journals and receiving feedback from professors on academic achievements in technical writing. We analyzed the differences between the test group who had recorded reflective journals and getting feedback, and the control group who had gotten feedback without reflective journals. And we compared academic achievements by conducting both professor evaluation and peer evaluation in technical writing. The results showed better learning effect, learning satisfaction and academic achievements in the test group than the other.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.269-277
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• 2008

This paper proposes a necessary and sufficient condition of convergence in the $L_2$-norm sense for a feedback-based iterative learning control (ILC) system including a multi-input multi-output (MIMO) linear time-invariant (LTI) plant. It is shown that the convergence conditions for a nominal plant and an uncertain plant are equal to the nominal performance condition and the robust performance condition in the feedback control theory, respectively. Moreover, no additional effort is required to design an iterative learning controller because the performance weighting matrix is used as an iterative learning controller. By proving that the least upper bound of the $L_2$-norm of the remaining tracking error is less than that of the initial tracking error, this paper shows that the iterative learning controller combined with the feedback controller is more effective to reduce the tracking error than only the feedback controller. The validity of the proposed method is verified through computer simulations.

• Asian Journal of Innovation and Policy
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• v.1 no.1
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• pp.92-115
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• 2012

The problem Japanese universities face is exactly the same as that of German universities: no international recognition in world rankings of universities despite their high levels of postwar economic and technological developments. This was indeed one reason why world-class Japanese firms, such as Toyota and Sony, have avoided working closely with Japanese universities for R&D partnership and new technology commercialization. To resolve this problem, the Japanese government has continuously implemented aggressive policies of the internationalization, privatization, liberalization, and privatization of universities since the onset of the economic recession in 1989 in order to revitalize the Japanese economy through radical innovation projects between universities and firms. National projects of developing medical robots for Japan's ageing society are some of the ambitious examples that emphasize feed-forward learning in innovation. However, this paper argues that none of these programs of fostering university-firm alliances toward feed-forward learning has been successful in promoting the world ranking of Japanese universities, although they showed potentials of reinforcing their conventional strength of introducing $kaizen$ through feedback learning of tacit knowledge. It is therefore argued in this paper that Japanese universities and firms should focus on feedback learning as a way to motivate firm-university R&D alliances.

• Journal of the Korea Society of Computer and Information
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• v.22 no.8
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• pp.101-106
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• 2017

In this paper, we propose a new teaching-learning model with two-step feedback on programming language learning, which is a basic preliminary learning for programming. Programming learning is aimed at improving problem solving skills and thinking by experiencing problem solving through programming. For programming, the learner must know how to work with the computer and what to do with it. To do this, concrete thinking should be established and described in an accurate programming language. In recent, most studies have focused on the effects of programming learning and have not studied the effects of education on language itself. Therefore, in this study, the teaching-learning model for programming language education is presented and applied to the field, and the results are compared with the existing instructional-teaching model.

• The Journal of Korean Association of Computer Education
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• v.20 no.6
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• pp.1-15
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• 2017

The purpose of this study is to design a LMS(Learning Management System) dashboard for instructor feedback support based on learning analytics and to apply a LMS dashboard incorporating such taxonomy which allows an instructor to give a student personalized feedback according to the class content and a student's traits. In the dashboard design phase, usable instructional data were selected from LMS based on feedback taxonomy in terms of learning analytics. Two validity tests were conducted with 8 instructional technologists over 8 years of experience, and were revised accordingly. The final dashboard screen has three parts: A comprehensive analysis screen to provide appropriate feedback based on instructor feedback taxonomy analysis, a summary screen for learner analysis, and a recommended feedback guide screen. Detailed analysis information are provided through other dashboards that are displayed in eight screens: login analysis, learning information confirmation analysis, teaching materials learning analysis, assignment/tests, and posts analysis. All of these dashboards were represented by analysis information and data based on learner analytics through visualization methods including graphs and tables. The implications of educational utilization of the dashboard for instructor feedback support based on learning analytics and the future researches were suggested based on these results.