• Korean Journal of Schizophrenia Research
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• v.23 no.1
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• pp.15-28
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• 2020

Objectives: This study investigated the relationship between clock-drawing test (CDT) performance and neuropsychological functions in patients with chronic schizophrenia. Methods: Thirty-one patients with schizophrenia and 30 healthy controls participated in this study. The CDT was administered in three conditions and analyzed using both quantitative and qualitative scoring systems. Comprehensive neuropsychological tests were administered. Results: The results of the quantitative analysis showed that the schizophrenia group performed significantly worse in all three conditions of the CDT compared with the control group. However, no significant differences were observed between the two groups, when the IQ and educational level were controlled. The qualitative analysis showed that the schizophrenia group exhibited significantly more errors in "graphic difficulty" compared with the control group. In addition, CDT quantitative scores were significantly correlated with visuospatial function, memory, attention and executive functions in patients with schizophrenia. Conversely, each qualitative error type was correlated with specific cognitive domains. Furthermore, "graphic difficulty" and "spatial/planning deficit" were identified as predictors of depression symptoms in patients with schizophrenia. Conclusion: The present study demonstrated that the CDT is useful for assessing cognitive dysfunctions in patients with schizophrenia, while qualitative analyses provide more specific information about cognitive deficits compared with quantitative analyses.

• Smart Media Journal
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• v.3 no.3
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• pp.26-35
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• 2014

The statistical graphics is a design field focusing on the user perception aspects for the correct information delivery and the effective understanding, with the use of the quantitative data through the information analysis, extraction, visualization process. The statistical graphics with the big data composition factor is termed as the statistical big data graphics. In the statistical graphics the visual factors are used to reduce the errors in the perception part and to successfully deliver the information. However, in the statistical big data graphics the visual factors of the enormous data are causing the cognitive discouragements. The purpose of this study is to extract the cognitive discouragement factors from the big data statistical graphics, categorizing the types of the statistical big data graphics as 'network type', 'segment type', and 'mixed type', based on their compositional shapes, and explored the characteristics according to them. Especially, based on the visual main factors in the statistical big data graphics, We extracted the cognitive discouragement factors that appear in the high visualization as the four categories: 'multi-dimensional cases', 'various color', 'information overlap', and 'legibility of the writing'.

• The Journal of the Korean dental association
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• v.58 no.11
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• pp.670-682
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• 2020

This research examined the difference in cognitive load and the virtual presence depending on auditory feedback and task difficulty in haptic-based dental simulation. In the field of dental education, practice-centered training using handpiece has been crucial because a practitioner's psychomotor experience has a significant impact on the mastery of treatment skills. For the novice, it is necessary to reduce errors in dental treatment to enhancing skill acquisition in the haptic practice. In the training process, the force-feedback is crucial to elaborate subtle movement to guide what to do and how it should be hard or soft. However, It is not easy to add force-feedback to generate kinetic experience training. As an alternative method, we examined that auditory feedback can help learners' skill training. In this study, we analyzed how the presence/absence of auditory feedback at the different levels of task difficulty impacts learners' psychological demand and virtual presence in the virtual reality simulation. For this study, 29 dental college students participated in a dental simulation. The participants were grouped into two conditions that are with and without auditory feedback. Additionally, two consecutive tooth preparation tasks with different levels of difficulty were used in the simulation. The auditory feedback condition gives alarms to a learner when he treats a non-targeted tooth with a virtual handpiece. The user's cognitive load and virtual presence were measured to examine the effects of auditory feedback. The results revealed that the main effect was found in cognitive loads. Also, a significant interaction effect was shown in the virtual presence. We discussed the effective design methods for the virtual reality-based dental simulation through the result of this study.

• The Mathematical Education
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• v.45 no.3 s.114
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• pp.263-273
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• 2006

The purpose of this paper is to research the factors and the effects of immediacy in mathematics teaching and learning and mathematical problem solving. The factors of immediacy are visualization, functional fixedness and representatives. In special, students can apprehend immediately the clues and solution using the visual representation because of its properties of finiteness and concreteness. But the errors sometimes originate from visual representation which come from limitation of the visual representation. It suggests that students have to know conceptual meaning of the visual representation when they use the visual representation. And this phenomenon is the same in functional fixedness and representatives which are the factors of immediacy The methods which overcome the errors of immediacy is that problem solvers notice the limitation of the factors of immediacy and develop the meta-cognitive ability. And it means we have to emphasize the logic and the intuition in mathematical teaching and learning. Clearly, we can't solve all mathematical problems using only either the logic or the intuition.

• Research in Mathematical Education
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• v.10 no.3 s.27
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• pp.169-187
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• 2006

Ubiquitous errors in algebra like $(x+y)^2=x^2+y^2$ are a constant reminder that most students' manipulation of algebraic symbols has become detached from structural principles. The U.S. mathematics education community (NCTM, 2000) has responded by shying away from algebra as a structural study, preferring instead to ground meaning in empirical domains of reference. A new analysis of such errors shows that students' detachment from structural meaning stems from an inadequate structural curriculum, not from the inherent difficulty of adopting an abstract perspective on expressions and equations. A structural curriculum is outlined that preserves the possibility of students' engaging fully with algebra as both an empirical and a structural study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.1
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• pp.86-88
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• 2016

In a previous work, a simultaneous reporting scheme for cooperative spectrum sensing has been presented for a resource efficient transmission over a report channel. In this paper, we present a method of reducing transmission errors on the report channel for it and evaluate its performance by simulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.185-192
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• 1994

The complexity and consistency are important factors that affect human information processing in use of product. In this study, complexity and consistency of product(remote controller) are measured by Task Action Grammar(TAG) model. Also, new design alternative of the user interface is presented and evaluated. The results show that the consistent system and the good correspondence between hierarchical structure of system and user's mental model lead to the reduction of errors and enhanced user's performance.

• Korean Journal of Cognitive Science
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• v.33 no.4
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• pp.205-228
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• 2022

This study aimed to confirm the effect of social and relational behavior types of robots on human cognition in human-robot interaction. In the experiment, the participants evaluated trust in robots by watching a video on the robot Nao interacting with a human, in which the robot made an error and then made an effort to restore trust. The trust recovery behavior was set as three conditions: an internal attribution in which the robot acknowledges and apologizes for an error, a condition in which the robot apologizes for an error but attributes it externally, and a non-action condition in which the robot denies the error itself and does not take any action for the error. As the result, in all three cases, the error was perceived as less serious when the robot apologized than when it did not, and the ability of the robot was also highly evaluated. These results provide evidence that human attitudes towards robots can respond sensitively depending on the robot's behavior and how they overcome errors, suggesting that human perception towards robots can change. In particular, the fact that robots are more trustworthy when they acknowledge and apologize for their own errors shows that robots can promote positive human-robot interactions through human-like social and polite behavior.

• Korean Journal of Cognitive Science
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• v.16 no.2
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• pp.123-140
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• 2005

The purpose of this paper is to examine the frequency and usage of sentence patterns appearing in electronic dictionaries used in Korean language education in order to design an automatic sentence patterns checking. First, the concept of sentence patterns is defined and it is classified into sentence structure patterns and sentencial expression patterns. Sentence structure patterns and sentencial expression patterns are analyzed how they are expressed in the Korean Learner's Corpus. learner's Corpus is built into the Standard Corpus, which all Korean Learners must learn, and the Errors Corpus made by learners. From these research, we will find out how frequently the Sentential Patterns are being used in the Standard Corpus which has been made of Korean Texts and how the Sentential Pattern are being used in the Errors Corpus which were constructed from Korean learner's writings. Finally, having described the Sentential Patterns on the Sentential Electric Dictionary, we determine the optimum speed in the search for the Sentential Pattern.

• Korean Journal of Cognitive Science
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• v.34 no.3
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• pp.197-226
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• 2023

Generative Text Summarization is one of the Natural Language Processing tasks. It generates a short abbreviated summary while preserving the content of the long text. ROUGE is a widely used lexical-overlap based metric for text summarization models in generative summarization benchmarks. Although it shows very high performance, the studies report that 30% of the generated summary and the text are still inconsistent. This paper proposes a methodology for evaluating the performance of the summary model without using the correct summary. AggreFACT is a human-annotated dataset that classifies the types of errors in neural text summarization models. Among all the test candidates, the two cases, generation summary, and when errors occurred throughout the summary showed the highest correlation results. We observed that the proposed evaluation score showed a high correlation with models finetuned with BART and PEGASUS, which is pretrained with a large-scale Transformer structure.