• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.83-89
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• 2021

This study examined how the learning styles and emotions of 234 students enrolled in early childhood education-related departments affected their ability to participate in the learning community. The research collected the variables of the pre-service early childhood teachers' ability to participate in the learning community, the emotions that they experienced while learning, and their learning styles. The collected data were analyzed through correlation analysis and regression analysis. The results indicate that the students' ability to participate in the learning community was positively correlated with the following: their analytical learning attitude (among learning styles); learning motivation; degree of preference for discussion and discussion types; positive and negative emotions, which are subcategories of learning emotion; and the degree of preference for experimentation and their practice type among teaching methods. Second, regression analysis showed that the students' ability to participate in the learning community could be predicted by negative emotion as a subcategory of their learning emotion, learning motivation, degree of preference for the experiment and practice type, their analytical learning attitude, and the degree to which students value studying the content of their major subjects.

• Journal of Korean Elementary Science Education
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• v.39 no.2
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• pp.255-267
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• 2020

Students' engagement is important for meaningful learning and it has multifaceted aspects for their science learning. This study investigated elementary students' perceptions of science learning engagement. The subjects of this study were 341 4^th to 6^th elementary students. The survey questionnaires were 5-Likert scale questions and free response questions on science learning engagement. The results showed that elementary students' perceptions of behavioral engagement were higher than emotional and cognitive engagement. Keyword network analysis with NetMiner program showed that the frequent key words of science learning engagement were 'experiment', 'listening', and 'teachers' explanation', which were mostly the behavioral types of engagement. The degree centrality and eigenvector centrality of these key words appeared high. 'Interest', which is emotional engagement, were also one of the frequent key words, but the centralities of this word were relatively low. The Frequent key words of science learning disengagement were mostly related with off-tasks, not doing expected behaviors and negative emotions about science and science learning. Educational implications on science learning engagement were discussed.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.51-58
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• 2020

This study redesigned the Korean speaking classes to foreign undergraduate students as flipped learning classes and verified their effect on speaking-related emotional variables. In addition, international students' perceptions of what experiences are needed to improve speaking efficacy in Korean were examined. For this purpose, the 'Creative speaking' subject for freshmen was redesigned to flipped learning class and operated for one semester. To analyze the effect of speech-related emotions, a paired t-test was conducted on 26 foreign students' pre-post scores of speech efficacy and anxiety. Also awareness of experiences needed to improve speech efficacy was surveyed and content analysis was conducted. As the result, the speaking efficacy of students after flipped-learning has been significantly improved. This means that flipped learning classes for the Korean speaking are effective for the positive emotions of foreign students speaking Korean. In addition, international students perceived that Korean speaking efficacy can be improved by practicing speaking in Korean, learning with Korean colleagues. Based on these results, several discussions and suggestions were presented.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.40-46
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• 2020

With the development of the Internet, users share their experiences and opinions. Since related keywords are used witho0ut considering information such as the general emotion or genre of an unstructured document such as a movie review, the sensitivity accuracy according to the appropriate emotional situation is impaired. Therefore, we propose a system that predicts emotions based on information such as the genre to which the unstructured document created by users belongs or overall emotions. First, representative keyword related to emotion sets such as Joy, Anger, Fear, and Sadness are extracted from the unstructured document, and the normalized weights of the emotional feature words and information of the unstructured document are trained in a system that combines CNN and LSTM as a training set. Finally, by testing the refined words extracted through movie information, morpheme analyzer and n-gram, emoticons, and emojis, it was shown that the accuracy of emotion prediction using emotions and F-measure were improved. The proposed prediction system can predict sentiment appropriately according to the situation by avoiding the error of judging negative due to the use of sad words in sad movies and scary words in horror movies.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.165-176
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• 2018

With the development of information and communication technology, the possibility of utilizing 3D virtual reality in education has been sought. Especially, the screen composition in the virtual reality has the possibility of inducing the emotion of the user which may affect the learning. However, there is little research on what aspects of the screen can cause emotions. The purpose of this study is to analyze the user's perception of screen components inducing emotion in virtual reality learning environment. Using Multi Dimensional Scaling (MDS), the user's perception of the main screen in a representative virtual reality learning environment platform was investigated. As a result, the dimension of depth on the screen and the dynamics of the avatar related to the movement were confirmed. This study is meaningful to explore technical variables that can induce emotions among screen elements in virtual reality contents.

• The Korean Journal of Health Service Management
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• v.11 no.4
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• pp.29-40
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• 2017

Objectives : The purpose of this study was to identify the effects of emotional competence, learning organization and nursing organizational culture on performance among clinical nurses. Methods : This study was conducted over a six-month period, with 170 nurses from general hospitals with 400 beds in three regions of Korea. Data were gathered from August 25th to September 10th, 2016, using a self-report questionnaire, and analyzed using the IBM SPSS 19.0 program. Results : The significant predictors of nursing performance were self-awareness (${\beta}=.32$), a master's degree or higher (${\beta}=.20$), relationship management (${\beta}=.26$), personal mastery(${\beta}=.23$), and 5~10 years in a clinical career (${\beta}=.16$). These variables explained 47.3% of the variance in nursing performance. Conclusions : To improve nursing performance, interventions that can enhance nurses' emotional competence and the need for program development to enhance their learning organization, as well as related variables, including academic credentials and clinical career, should be considered.

• Journal of Korean Elementary Science Education
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• v.24 no.1
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• pp.86-101
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• 2005

In this study, a brain-basrd model for science teaching and learning was developed based on the natural processes which human acquire knowledge about a natural object or on event, the major domains of science educational objectives of the national curriculum, and the human brain's organizational patterns and functions. In the model, each educational objective domain is related to the brain regions as follows: The affective domain is related to the limbic system, especially amygdala of human brain which is involved in emotions, the psychomotor domain is related to the occipital lobes of human brain which perform visual processing, temporal lobes which perform functions of language generating and understandng, and parietal lobes which receive and process sensory information and execute motor activities of body, and the cognitive domain is related to the frontal and prefrontal lobes which are involved in think-ing, planning, judging, and problem solving. The model is a kind of procedural model which proceed fiom affective domain to psychomotor domain, and to cognitive domain of science educational objective system, and emphasize the order of each step and authentic assessment at each step. The model has both properties of circularity and network of activities. At classrooms, the model can be used as various forms according to subjects and student characteristics. STS themes can be appropriately covered by the model.

• Hwankyungkyoyuk
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• v.12 no.1
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• pp.40-63
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• 1999

As the environmental problems are recognized as daily problems in our lives, not as issues of those who are engaged in specific professional fields, the interest in environmental education is increasing gradually. The environmental education is the one that studies the environment and its problems and seeks the solutions for them. This paper deals with how the Korean subject will include environmental education. The environmental problems are already dealt with in the Korean textbooks according to the 6th curriculum for the Korean subject. A noticeable fact is that those textbooks connect the skills for language skills with environmental education. That is, the textbooks try to improve 4 language skills (speaking, listening, reading, and writing) with the Korean data related to environment, which can be the most practical means. This tendency will be also reflected in the 7th curriculum for the Korean subject, and the means will be taken by which environmental education will be able to be implemented more effectively through a variety of learning activities. In case of speaking and listening, learning activities such as speaking of, listening to, or discussing the contents concerning environmental problems can be recommended. In case of reading and literature, learning activities such as reading articles or works concerning environmental problems. Through these learning activities the Korean education will be able to achieve the goal in the fields of knowledge, information, and autonomy or attitudes which are the goals of environmental education. If the contents of the Korean curriculum are described in detail, it can be known that the Korean subject have someting to do with knowledge, skills, and recognition more deeply. In the methods In obtain information and knowledge, it will be desirable to recognize knowledge and information indirectly through various reading data rather than to recognize knowledge and information directly. Or it will be desirable to increase the sensitivity about environmental problems through literary works. For this environmental education in the above, we need to utilize discussion or presentation-oriented leaching and learning in the Korean education. Also we need to approach environmental problems by using various teaching media. We need to emphasize the education in the affective domain, especially through expression of emotions. guidance of reactions, internalization, personification, and so on.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.558-572
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• 2019

Anthropomorphism is the attribution of human traits, emotions, or intentions to non-human entities. Anthropomorphic animal face masking is the process by which human characteristics are plotted on the animal kind. In this research, we are proposing a compact system which finds the resemblance between a human face and animal face using Deep Convolutional Neural Network (DCNN) and later applies morphism between them. The whole process is done by firstly finding which animal most resembles the particular human face through a DCNN based animal face classification. And secondly, doing triangulation based morphing between the particular human face and the most resembled animal face. Compared to the conventional manual Control Point Selection system using an animator, we are proposing a Viola-Jones algorithm based Control Point selection process which detects facial features for the human face and takes the Control Points automatically. To initiate our approach, we built our own dataset containing ten thousand animal faces and a fourteen layer DCNN. The simulation results firstly demonstrate that the accuracy of our proposed DCNN architecture outperforms the related methods for the animal face classification. Secondly, the proposed morphing method manages to complete the morphing process with less deformation and without any human assistance.