• Journal of KSNVE
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• v.14 no.3
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• pp.6-22
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• 2004

지능형 로봇 이란 주어진 환경 (현장, 인간 공존 등)에서 별도의 조작이 없이도 스스로 환경을 인지 판단하고 작업을 수행하거나, 인간과의 상호작용을 통하여 서비스를 제공하는 로봇 (중략)

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.481-490
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• 2019

The purpose of this paper is to recognize and embody the implications of the concept of interactivity. Among the many types of interactivity already proposed, this paper sheds light especially on the so-called contingent interactivity. The contingency means a condition in which a particular performance or selection of a subject is considered neither necessary nor conclusive, and also the potential for various activities of this subject. The contingent interaction comes into being when the involvements of users in dealing with a message or content are experimental or creative. The interaction does not orient toward the completion of content or the immersion to a particular reality. Rather, the results of a user's contingent performance are not the finalized content and have characteristics that lead to the continuous modification. In order to embody this meaning of contingent interactivity, the paper examined the two example, the film re-cut and game modding. In both cases, it is comprehensive that the user of these two new media activities lies in the contingent situation.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.531-536
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• 2016

This study highlights the effectiveness of analyzing the feelings children have when interacting with robots in a dramatic play setting using augmented reality in Human Robot Interaction (HRI). Existing dramatic play activities using robots by QR-markers were edited, and their weaknesses have been corrected so that children could interact more effectively with robots. Additionally, children's levels of interest and engagement in dramatic play activities, the accuracy of robotic props, and the smartness of robots were analyzed throughout children's interactions during such activities using augmented reality. Younger participants were more likely to find robots interesting and intelligent, and participants with no previous experience with robots had relatively higher levels of interest in robots and tended to notice changes in robots' costumes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.63-73
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• 2008

Recent years have seen an explosion of interest in interactive agents motivating human learners to engage in edutainment systems which are designed to be entertaining and educational at the same time. Especially, work on socio-emotional processes has focus on understanding of human's social behavior in training and entertainment a applications. In contrast with work on social emotion, where research groups have developed detailed models of emotional processes, models of personality have emphasized shallow surface behavior. Here, we build on computational appraisal models of emotion to better characterize dispositional differences in how people come to understand social situations. Known as explanatory style, this dispositional factor plays a key role in social interactions and certain socio-emotional disorders, such as depression. Building on appraisal and attribution theories, we model key conceptual variables underlying the explanatory style, and enable agents to exhibit different explanatory tendencies with respect to their personalities. Furthermore, we developed an interactive AR agent based on our framework and applied it into an interactive teaming system that allows participants to explore individual differences in the explanation of social events, with the goal of encouraging the development of perspective laking and emotion-regulatory skills.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.11a
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• pp.66-68
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• 2011

VTS 협력항해는 수많은 상황판단과 자율적인 행위자들의 의사결정들의 집합체이다. 선박이 서로 영향을 끼치며 상호작용하기 때문에 발생하는 불확실성이 바로 VTS 협력항해가 해결해야 하는 문제 상황이다. 이러한 불확실성으로 인한 항해위험을 극복하기 위해서는 상황자각과 의사결정이 항해사 개별 차원에서 뿐만 아니라 모든 항해자들이 서로 도우면서 VTS 협력항해 전체적인 차원에서 이루어져야 한다는 점을 중점적으로 논의하였다. 본고에서는 해양사고의 원인으로서 조선기술의 미숙보다는 항해관련 인지기술이 더 직접적으로 작용한다는 점을 주장하면서, 더 나아가 기왕에 발생한 해양사고를 상황자각 관점에서 접근함으로써 해양사고의 인적과실과 관련한 심층적인 분석을 할 수 있다는 것을 밝혔다. 항해의 인지과업을 1단계 상황자각에서부터 분산의사결정에 이르는 과정으로 세분화하고, 이런 관점에서 접근함으로써 해양사고의 원인으로 작용하는 인적과실을 심도 있게 분석할 수 있었다. 인지과업의 세분화를 통해서 항해사들이 각 단계별로 에러를 수정할 수 있는 여유를 확보할 수 있게 하고, 사고로 이어지는 인과 고리를 차단하는 한편 보다 안전한 대안을 찾아 실행할 수 있다는 점을 부각시켰다. 이런 연구결과를 항해사의 훈련 과정에 접목함으로써 해양사고의 위험을 획기적으로 줄일 수 있다는 것을 밝히고자 노력하였다.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.74-85
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• 2018

The research investigated the interaction effect of video resolution and device luminance on the perceived characteristics, presence, and fatigue viewing virtual reality. Experiments were composed of mixed design, and the resolution and luminance were classified into three types, HD, 2K, and 4K, and 20, 60, and 100, respectively. Participants watched video of 6-minutes randomly, and responded to the questionnaire after watching each video. The results showed that no interaction effect existed. Meanwhile, there are statistically significant differences on the luminance of depth perception, the resolution of visual intervention, and the resolution of adjustment fatigue. Also, higher resolution and luminance showed higher cognitive function, presence and fatigue.

• Annual Conference on Human and Language Technology
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• 1996.10a
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• pp.393-399
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• 1996

자연언어 대화에서 사용자의 정확한 의도(Intention)를 인지함에 있어서 나타나는 문제는, 자연언어 대화체의 생략성이 강한 문장의 불완전성 외에도, 여러 연속되는 대화체 문장에 분산되어 나타나는 사용자의 의도를 정확히 파악하는 것이다. 이러한 불완전한 대화체 문장 속에 산재되어 있는 사용자의 의도를 빠르고 신뢰성 있게 인지하여, 사용자와 시스템간의 원활한 자연언어 대화 상호작용 (Interaction)을 가능하게 하기 위하여 플랜 인지 시스템의 이용은 매우 효과적으로 보인다. 현재까지 개발된 대부분의 플랜 인지시스템들은 사용자의 액션 분석 및 플랜의 인지를 통하여 HCI를 지원하는 측면에 (예: 지능형 도움말) 집중되어 있다. 본 논문은 지역 광고 신문에 실린 매입-매도광고 데이타베이스의 검색을 위한 Natural language dialogue user interface에서 사용자 의도를 인지할 수 있는 플랜 인지 시스템을 기술하고 있다.

• School Mathematics
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• v.9 no.3
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• pp.375-396
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• 2007

The purpose of this study is to analyze how a mathematics teacher and a high school student make the meaning in a graph and how aspects of the interpretation of a graph are interacted during the signification process, and to suggest considerations for teaching and learning of a graph. The findings of a case study have led to conclusions as follows: All of them have a difficulty in making the meaning in a graph and construct the meaning as a nested signification model. In the process which they make the meaning, they interrelate cognitive, contextual, and affective aspects and construct interpretants. In this process, a teacher focuses on cognitive aspect, based on a qualitative approach. But a student considers contextual aspect more, based on a quantitative approach. This study suggests three considerations for teaching and learning of a graph.

• Journal of Industrial Convergence
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• v.20 no.1
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• pp.69-76
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• 2022

This study is a descriptive survey study to identify interaction influencing factors in nursing students with experience in child nursing practice. The collected data used the SPSSwin 25.0 program, and the influencing factors on the interaction were analyzed by multiple regression analysis. As a result of the study, among the general characteristics of nursing college students, major satisfaction and play beliefs showed influence on interaction, and the explanatory power for interaction was 36.0%. Based on the results of higher major satisfaction, higher play beliefs, better interaction with children, a child nursing practice curriculum is required to improve nursing students' major satisfaction and have positive beliefs about play, and play in the theoretical curriculum before child nursing practice.It is thought that it is necessary to acquire knowledge of the law and educate on the necessity.

• Journal of The Korean Association For Science Education
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• v.26 no.1
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• pp.16-24
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• 2006

The purpose of this study was to compare student-student verbal interaction from two type's experiments; problem-solving and task-solving. For this study, five 3rd grade middle school students were selected and their verbal interactions recorded via voice and video; and later transcribed. The student-student verbal interactions were classified as questions, explanations, thoughts, or metacognition fields, which were separated into deep versus surface learning approaches. For the problem-solving experiment, findings revealed that the number of verbal interactions is more than doubled and in particular, the number of verbal interactions using deep-approach is more than quadrupled from the point of problem-recognition to problem-solution. As for the task-solving experiment, findings showed that verbal interactions remained evenly distributed throughout the entire experiment. Finally, it was also discovered that students relied upon a more deep learning approach during the problem-solving experiment than the task-solving experiment.