• Korean Journal of Childcare and Education
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• v.11 no.5
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• pp.191-214
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• 2015

The purpose of this study was to investigate variables which have an influence on young children's peer interactions. The data of 966 4-year-old children and their parents and class teachers were extracted from the 5th Panel Study on Korean Children in 2012 by Korea Institute of Child Care and Education. The data were analyzed by means of ANOVA, Pearson's coefficient and multiple regression. The results were as follows: First, boys' play disruption and play disconnection were higher than girls', and girls' play interaction was higher than boys'. Second, sociability and activity of temperament, and teacher-child interaction were related to peer disruption. Third, teacher-child interaction and sociability of temperament significantly affected play interaction. Controlling parenting behavior of the mother was positively related to peer interaction in girls. Fourth, teacher-child interaction, sociability and emotionality of temperament significantly affected play disconnection. Social parenting behavior of the father was negatively related to play disconnection in boys. Lastly, teacher-child interaction was the clearest indicator for young children' peer interactions. These findings suggested a potential role of the teacher in young children's peer interactions.

• 한국지구과학회:학술대회논문집
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• 2003.09a
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• pp.101-101
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• 2003

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1602-1610
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• 2004

As various genome projects have produced enormous amount of biosequence data, functional sequence analysis in terms of tile nucleic acid and protein becomes very significant. In functional genomics and proteomics, the functional analysis of each individual gene and protein remains a big challenge. Contrary to traditional studies, which regard proteins as not components of a whole protein interaction network but individual entities, recent studies have focused on examining functions and roles of each individual gene and protein in view of a whole life system. In this regard, it has been recognized as an appropriate method to analyze protein function on the basis of synthetic information of its interaction and domain modularity. In this context, this paper introduces the PIVS (Protein-protein interaction Inference & Visualization System), which predicts the interaction relationship of input proteins by taking advantage of information on homology degree, domain modules which input sequences contain, and protein interaction relationship. The information on domain modules can increase the accuracy of the function and interaction relationship analysis in terms of the specificity and sensitivity.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.622-635
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• 2018

On top of presenting the possibility of expanding the game space to social space through mobile communication, MSNG reinforces the strengths of SNS and the fun of games through closer networks between users. This study empirically verified the effects of the characteristics of MSNG on interactions and user satisfaction by dividing the main characteristics of MSNG into graphics, challenge spirit, and reward, and then dividing the main characteristics of mobile social network service into social interaction and technical interaction. In the results of study, the main characteristics of MSNG such as graphics, challenge spirit, and reward all had significant effects on the social interaction and technical interaction while the social interaction and technical interaction of MSNG also had significant effects on the user satisfaction, so that the hypotheses of this study were all selected. The influence of the characteristics of MSNG on interactions might be because of shared feedbacks through graphics, game tasks, and reward in the performance process of MSNG, and such interactions make diverse people have the horizontal or circular communication, which is led to the increase of user satisfaction.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.115-121
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• 2018

The purpose of this study is to examine the effects of kindergarten teachers' rights and obligations on teacher - A questionnaire survey was conducted on 174 teachers in kindergartens in Seoul, Gyeonggi, and Incheon. The results of this study are as follows: First, teachers' rights have a statistically significant effect on the rights of education and status in linguistic interaction, which is a sub-domain of teaching-infant interaction. And in behavioral interactions, the rights of labor have had a negative impact. In the linguistic interaction and emotional interaction, which are subdivisions of teacher-infant interaction, teacher's duty had a statistically significant effect on the duties of status, while teacher's duty was the sub-domain of inter- Duties of integrity and duty and duty of status did not affect.

• Journal of The Korean Association For Science Education
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• v.42 no.5
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• pp.557-566
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• 2022

This study analyzed paired middle school students' verbal and physical interactions in small group learning using augmented reality. Twelve 8th graders were paired to take classes of solubility and melting/boiling points based on augmented reality. These classes were videotaped and recorded. After the classes, all the students participated in a semi-structured interview. The results were analyzed in three sections; individual statement units of verbal interaction, interaction units of verbal interaction and physical interaction. In the individual statement units of verbal interaction, the proportion of information question/explanation was found to be high. In the interaction units of verbal interaction, the proportion of simple interaction was the highest, followed by elaborated interaction. Beneath the elaborate interaction, the proportion of cumulative interaction was found to be the highest, followed by reformative interaction. In the physical interaction, writing a worksheet and gazing at a virtual object were higher. On the basis of the results, effective ways to form a proper environment in small group learning using augmented reality are discussed.

• 한국정보교육학회:학술대회논문집
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• 2005.08a
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• pp.341-348
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• 2005

본 연구는 상호작용에 대한 제 이론을 고찰하고 상호작용 증진을 위한 여러 가지 요소를 고려하여 웹 기반 학습 환경 설계 전략을 제시하는데 그 목적이 있다. 지식 정보화 사회에 들어오면서 여러 가지 통신 환경이 급속하게 발달하였다. 학교 현장에서 이러한 여러 가지 인터넷 환경을 고려한 수업이 설계되고 실시되고 있다. 학교 현장에서 실시되고 있는 이러한 적용에서 상호작용에 대한 고찰이 미흡하고 상호작용을 고려한 여러 가지 시스템이 구현된 것이 드문 것 같다. 이에 본 연구에서는 웹 기반 학습 환경에서 가능한 다양한 상호 작용에 대한 개념 및 상호작용의 내용에 따른 유형을 알아보고 상호작용을 증진시키기 위한 설계 전략을 고찰해 보았다.

• Journal of Science Education
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• v.37 no.1
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• pp.117-130
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• 2013

The purpose of this study was to analyze the patterns and features of interaction in teacher interviewing with high school students' small group for biology learning. The interactions in variety between the students and between the students and the teacher were made as the interviews with each small group were repeated to feedback for biology learning. The patterns of interaction were categorized into four types by interactive level of interaction among group members and a teacher: leader representation without interaction among students and the teacher(LR, leader representation), interaction among a part of students and the teacher(PSI, partial students interaction), active interaction among students inside the group, but only interaction between the teacher and the leader student(SAI, students active interaction), and interaction between all of the students and the teacher(teacher-students active interaction). Even though complex patterns of interactions were made among the students at the initial stage of insufficient understanding on the study concept, the simple interaction processes were shown as students had gradually completed the understanding on the concept. It was displayed that the interaction in the small group for biology study provides the opportunity to confirm and understand the concept to the students who were poor at the understanding on the concept, and it can influence positively on the mutual creation of study concept.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.9
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• pp.419-428
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• 2017

In an embedded system, modules exchange data by interacting among themselves. Exchanging erroneous resource data among modules may lead to execution errors. The interacting resources produce dependencies between the two modules where any change of the resources by one module affects the functionality of another module. Several investigations of the embedded systems show that interaction faults between the modules are one of the major cause of critical software failure. Therefore, interaction testing is an essential phase for reducing the interaction faults and minimizing the risk. The direct and indirect interactions between the modules generate interaction faults. The direct interaction is the explicit call relation between the modules, and the indirect interaction is the remaining relation that is made underneath the interface that possesses data dependence relationship with resources. In this paper, we investigate the errors that are based on the indirect interaction between modules and introduce a new test criterion for identifying the errors that are undetectable by existing approaches at the integration level. We propose a novel approach for generating the interaction model using the indirect interaction pattern and design test criteria that are based on different interaction errors to generate test cases. Finally, we use the fault injection technique to evaluate the feasibility and effectiveness of our approach.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.4
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• pp.299-308
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• 2004

In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance probability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a Protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated for the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as teaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.