• The Journal of Korean Philosophical History
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• no.25
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• pp.99-135
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• 2009

This study is to investigate many kinds of conceptual models of social problem solving approach as well as decision making method, and then describes educational implications, especially for more effective method of teaching problem solving ability in order to reduce children' anti social behaviors and to be able to have their healthy and happy lives. Problem solving ability or decision making skills have been taken to goal of primary school curriculum, but is too cognitive or too centered to morality for student to get that kinds of skill or competency. As a result of new education method is developed on the basis of Socal Emotional Learning(SEL) as well as Emotional Intelligence which put on the importance on the role of emotion in the problem solving. This method have two distinctions. First, It has the background of culture specific views of emotion to be proper this method in our society. Second, It should be integrated into moral education as a part of school curriculum to establish secure and long term intervention.

• Journal of Korean society of Dental Hygiene
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• v.18 no.5
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• pp.729-740
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• 2018

Objectives: The purpose of this study was to investigate the factors affecting robot utilization in the education of pre-dental hygienists. Methods: A self-reported questionnaire was completed by 238 dental hygiene students studying in the Daejeon, Chungcheong, and Jeolla provinces during the period March 1-31, 2017. Results: Future oral health education media had high selection of 'movies,' 'video,' '3D printer,' 'robot,' and 'drone' In general education and oral health education, robots were appropriate as educators, assistant teachers, and media. This group had high levels of interest, experience, attitude, and learning scope of robots. Robot utilization education showed a significant positive correlation with the 'interest,' 'experience,' 'attitude,' and 'learning' subfactors (p<0.01). Factors influencing robot utilization education were the relationships among actual experience of robot, learning of robot production, social influence of robot, emotional exchange with robot, and the predictive power was 25.5% (p<0.05). Conclusions: Oral health education curricula using robots should be developed considering the emotional exchange and social influence between educator and learner.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• Korean Journal of Child Studies
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• v.25 no.6
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• pp.171-189
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• 2004

Children develop emotional intelligence during the early years of life, and according to experts, emotional intelligence(EI) is a more reliable predictor of academic achievement than IQ. However, nowadays children appear to be low on emotional well-being. This has potentially negative consequences, not only for academic achievement but also for personal relationships. The purpose of this study was to develop emotional education program for young children(EEPYC). In this study, EI is defined to carry out reasoning in regard to emotions and to use emotion for enhancement of thought. Designed to facilitate development of young children's EI. EEPYC is based on the four branch model, which is mental EI model and based on the guiding principle of Collaborative to Advance Social and Emotional Learning. The subgroups(curricular) that compose EEPYC are Emotional Perception, appraisal, and expression, Self-recognition program, Self-esteem program, Emotional Stress Regulation, Emotional problem solving & conflict resolution. EEPYC has the potential of fostering emotional intelligence. Moreover, EEPYC can promote a motivation, prosocial activity, and regulation of stress. This helps young children to develope cognition and emotion in harmonious fashion.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.238-246
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• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.352-368
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• 2021

Sign-in point of interest (POI) are extremely sparse in location-based social networks, hindering recommendation systems from capturing users' deep-level preferences. To solve this problem, we propose a content-aware POI recommendation algorithm based on a convolutional neural network. First, using convolutional neural networks to process comment text information, we model location POI and user latent factors. Subsequently, the objective function is constructed by fusing users' geographical information and obtaining the emotional category information. In addition, the objective function comprises matrix decomposition and maximisation of the probability objective function. Finally, we solve the objective function efficiently. The prediction rate and F1 value on the Instagram-NewYork dataset are 78.32% and 76.37%, respectively, and those on the Instagram-Chicago dataset are 85.16% and 83.29%, respectively. Comparative experiments show that the proposed method can obtain a higher precision rate than several other newer recommended methods.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.784-794
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• 2014

In this study, we operated science teacher learning community to enhance professionality of elementary science teachers. 8 participants with various background, which include their science content knowledge, teaching experience and beliefs about teaching, were involved in this study. Bales(1950)'s social interaction process framework was mainly used to understand the members' interaction, focusing particularly on process aspects not on contents aspects. The data analysis shows that the members in the science teacher learning community tried their best to maintain the positive reaction to other members in most occasions in the community meetings. On the other hand, there were also negative reaction process due to their different ideas and views, causing their emotional conflicts in some social relations and dialogical situations. Nevertheless, the results also imply that the dual reaction processes, which are positive and negative processes, are equally important to facilitate science teachers' professional knowledge and experience. The educational meanings are discussed in the aspects of science teacher education.

• Journal of the Korean Institute of Educational Facilities
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• v.27 no.2
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• pp.79-86
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• 2020

Since the introduction of the new Variation Type school, few studies have focused on students' adaptation to the changes in their learning environments at school. This paper is based on the Stage-Environment Fit theory, which asserts that a successful school life(in terms of motivation to learn) is ensured only when the school environment meets the social and emotional needs of students. Focusing on the third-grade student's adaptation to a new Variation Type school during their middle school period, the following conclusions were drawn. First, the transition to a new Variation Type school during middle school is much more difficult than adjusting to a new Variatio Type school upon admission to middle school. Second, this difficulty in adaptation is caused by socio-emotional dissatisfaction in adolescent students, for whom deconstruction of previous friendships can hinder motivation to learn. Third, third-grade students who experienced stress due to spatial changes tended to have a negative attitude towards the new Variation Type itself as they feel more tired from failing to use the space properly. Fourth, to transition successfully to a new Variation Type school, socio-emotional problems must be solved through the reduction of scale of the homebase, and the provision of various choices increasing the number of homebase.

• Journal of Digital Convergence
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• v.7 no.3
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• pp.49-60
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• 2009

The aim of this study was to develop a model for teaching-teaming by applying Ubiquitous at a learning experience field, in which connect characteristics of both ubiquitous application learning and experience teaming, making use of them. A literature survey of concepts was conducted, with the main areas to find out relationships between ubiquitous application learning and experience learning. Experience learning by applying ubiquitous learning methods maximizes its efficiency of experience learning in considering ubiquitous learning methods's characteristics of dynamic, interaction, sharing. Also it makes communications through positive participation and active interaction, and leads to a process of internal examination. The research data suggests that critical factors of experiencing learning applying ubiquitous are acquiring information and memory, information integration and exquisiteness, emotional and social activity, producing activity, help activity.

• Korean Journal of Child Studies
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• v.25 no.5
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• pp.193-208
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• 2004

This study purported to empirically examine joy expression and its cognitive and social contexts in children's play. The following question was asked: 1) What kind(s) of emotional expression(s) can be considered as a defining feature of play? 2) What cognitive/social play contexts are associated with joy expression. 30 children aged 3, 4, and 5 years were observed in terms of the length of each emotional expression at play/nonplay, and at cognitive/social play categories. The findings of this study showed that regardless of children's age and gender only joy expression could be considered as a defining feature of play, and that R&T play and chase games, or associative and cooperative social play were strongly related to joy expression. The findings were discussed in reference with existing assertions and perspectives, emphasizing the importance of joy expression in defining children's play despite of the predominance of interest expression in play. The findings were also discussed in reference with metacommunication functions and social construction of joy, considering cognitive/social contexts of joy. Implications for play researchers and practitioners were described in terms of developing playful learning strategies for childhood. Limitations of this study, and suggestions for further research were also provided.