• Title/Summary/Keyword: social and emotional learning

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A study on the attitude toward robot utilization in dental hygiene students (예비치과위생사의 로봇활용에 대한 태도)

  • Min, Hee-Hong;Ahn, Kwon-Suk
    • 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.

Detection of Depression Trends in Literary Cyber Writers Using Sentiment Analysis and Machine Learning

  • Faiza Nasir;Haseeb Ahmad;CM Nadeem Faisal;Qaisar Abbas;Mubarak Albathan;Ayyaz Hussain
    • 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.

Development an Emotional Education Program for Young Children (유아용 감성교육 프로그램 개발 연구)

  • Lee, Seung Eun;Lee, Yeung Suk
    • 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.

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A Deep Learning Model for Extracting Consumer Sentiments using Recurrent Neural Network Techniques

  • Ranjan, Roop;Daniel, AK
    • 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.

POI Recommendation Method Based on Multi-Source Information Fusion Using Deep Learning in Location-Based Social Networks

  • Sun, Liqiang
    • 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.

Analysis of Social Interaction Process in Science Teachers' Learning Community (과학교사 학습공동체에서 나타나는 사회적 상호작용 과정의 분석)

  • Cha, Gahyun;Jang, Shinho
    • 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.

Study on the Model Development for Experiential Learning with Ubiquitous Everyday English (유비쿼터스 생활영어 체험학습장 교수-학습 모형 개발 연구)

  • Baek, Hyeon-Gi;Kim, Su-Min;Kang, Jung-Hwa
    • 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.

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A Study on Students' Adaptation to Changes in Their Learning Environments at School - Focused on Students' Experience of Transition to the New Variation Type Middle School - (학교 학습환경 변화에 따른 학생적응에 관한 연구 - 신축 교과교실제 중학교로의 이전경험을 중심으로 -)

  • Rieh, Sun-Young
    • 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.

Joy Expression and Its Cognitive and Social Contexts in Children's Play (놀이의 기쁨 - 정서표현과 그 맥락적 특성 -)

  • Kim, Heeyeon
    • 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.

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Analyses of the Patterns of the Synchronous and Asynchronous Social Media Usage in College e-Learning Settings (대학 이러닝 환경에서 실시간과 비실시간 소셜미디어 활용유형 차이분석)

  • Eom, Sang-Hyeon;Lim, Keol
    • Journal of Digital Convergence
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    • v.15 no.4
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    • pp.27-34
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    • 2017
  • As information technology has been developed in a rapid way, a lot of users get to be familiar with social media. Accordingly, the possibility of social media for educational use has increased. From the view point of learning, social media help learners make communities of practice that can lead to collective intelligence. In this study, two different types of social media, synchronous and asynchronous, were compared in terms of usage patterns in the e-learning settings of college level. Content analysis has figured out four factors: learning content, tasks and assignments, emotional communications, and chatting. There found to be a statistical differences in the postings in all of the factors except tasks and assignments. In the qualitative interviews, the participants told various usage patterns of synchronous and asynchronous social media. In sum, the learners generally preferred synchronous social media. Rather, asynchronous social media were mainly used for deep thinking and summarizing. Last, suggestions were made to improve educational environments for the learners in the digital and social media age.