• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.335-342
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• 2023

This study was attempted to confirm the effects of learning flow, academic stress, and resilience on self-efficacy in college students. This study targeted 304 university students in B and G cities. Data analysis was analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis using the SPSS 22.0 program. The average self-efficacy of the subjects was 3.14±0.62 points, and the difference in self-efficacy according to general characteristics was significant in gender(t=-2.533, p=.012) and satisfaction with major(F=5.687, p=.004). Self-efficacy of the subjects was positive correlation with learning flow(r=.574, p<.001), resilience(r=.525, p<.001), and negative correlation with academic stress(r=-.262, p<.001). Resilience of the subjects showed positive correlation with learning flow(r=.325, p<.001) and negative correlation with academic stress(r=-.291, p<.001). Learning flow showed negative correlation with academic stress(r=-.211, p<.001). Factors influencing the self-efficacy of the subjects were identified as academic commitment (β=.442, p<.001) and resilience (β=.363, p<.001) and the explanatory power was 45.6%. Therefore, in order to improve college students' self-efficacy, it is necessary to develop and apply education and programs that can improve learning flow and resilience.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.239-248
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• 2023

This study is a descriptive correlation study to identify the relationship among online collaborating learning attitudes, empathy, critical thinking disposition, and sense of community in nursing students in the online learning environment during COVID-19. Data were collected from 129 nursing students. The SPSS/28.0 program was used to analyze the data using descriptive statistics, Pearson's correlation coefficient, independent t-test, one-way ANOVA, Scheffé test, Pearson's correlation analysis, and hierarchical multiple regression. Factors that significantly affect sense of community in nursing students were online collaborating learning attitudes and critical thinking disposition, and the explanatory power was about 42.2%. Based on these results, in order to increase sense of community of nursing students in non-face-to-face learning environment, it is required to strengthen the problem-solving-centered learning method cultivating the online collaborating learning attitude and critical thinking disposition.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.311-318
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• 2020

This study was done to explore the correlation among self-determination, learning commitment and learning outcomes and identify factors related learning outcomes under academic credit bank system. The survey was conducted self-report questionnaire. The data collection period was form April to November 2018. Participants were 144 registered nurses working currently under academic credit bank system. Collected data were analyzed using SPSS/WIN 24.0. Learning outcomes had a positive correlation with self-determination and learning commitment. learning commitment. Self-determination was positively correlated learning commitment. Factors affecting learning outcomes included self-determination and learning commitment. And self-determination and learning commitment accounted for 32.1% of the variance in learning outcomes. Therefore, developing learning outcomes support for improving self-determination and learning commitment. Future research will be needed to clarify the effects of learning outcomes promotion program on self-determination and learning commitment.

• Journal of Korean society of Dental Hygiene
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• v.15 no.3
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• pp.371-377
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• 2015

Objectives: The purpose of the study was to investigate the relation between learning strategy and academic achievement in the dental hygiene students. Methods: A self-reported questionnaire was completed by 207 dental hygiene students in Gyeongnam from April 1 to 30, 2014. The questionnaire consisted fo 51 questions of learning strategy and 1 question of academic achievement. The data were analyzed using SPSS 17.0 program for descriptive analyses, t-test, Pearson correlation and multiple regressing analysis. Results: The organized strategy and learning time management had a significantly positive influence on high scores in the junior and senior students. Learning strategie(r=0.419) and cognitive strategies(r=0.343), metacognitive strategies(r=0.239), resource management strategies(r=0.415) had significantly positive correlation to academic achievement. Cognitive strategy of learning strategies(p<0.05) and resource management strategies(p<0.001) had a positive effect on higher academic achievement. Conclusions: The learning strategies will provide the dental hygiene students with active participations.

• The Journal of Korean Association of Computer Education
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• v.11 no.6
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• pp.85-94
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• 2008

This study is to find strategies to promote distance learning effectiveness in the online learning environment. The research showed that the level of learner's perception of the structure of transactional distance was not significantly different according to sex (p>.05). There was significant correlation between the level of learner's perception of the structure and academic satisfaction(p<.01). And, the level of learner's perception of the structure and learning durability appeared to have statistically significant correlation. However there was no significant difference(p>.05) between academic achievement. Among the three subordinate factors, the course interaction organization had the most influence on the learner's academic satisfaction and the learner's learning durability was influenced the most by the content organization.

• Journal of the Korean Home Economics Association
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• v.48 no.1
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• pp.127-136
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• 2010

The purpose of this study was to investigate the relationships between the young children's creative trait and personality affecting their learning readiness. The participants were 131 young children in kindergartens or nursery schools and their mothers from Seoul, Gyeonggi and Chungnam province. The instruments were the Korea Learning Readiness Test, Young Children's Creative Traits Test, and Young Children's Personality Test. The data were analyzed by one-way ANOVA, t-test, Pearson's partial correlation, stepwise multiple regression, and Scheff$\'{e}$ test by SPSS PC(version17.0) program. The results were as follows. Firstly, there were no significant differences in young children's learning readiness, creative trait and personality by children's age, location, school type, father's age, mother's educational level and mother's job type, while there were significant differences in the creative trait and the subfactor scores of personality by children's sex, father's educational level and parents' job type. Secondly, there was a positive partial correlation(r = .20~.24) between young children's learning readiness and creative trait, while there were no correlations between their learning readiness and personality and between their personality and creative trait. Thirdly, cognitive factor of creative trait and father's educational level did not effectively explain the children's learning readiness.

• Educational Technology International
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• v.15 no.2
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• pp.89-115
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• 2014

This research aims to develop an elementary school English e-learning system based on the 'Self-determination theory (SDT)', which is widely applied to traditional face-to-face foreign language classes. The study also attempts to verify whether SDT-a traditional motivational theory that has been applied to face-to-face classes- is effective in an e-Learning environment with students who use this newly developed system. For the purposes of this project, the following three actions were carried out. First, a motivational strategy based on SDT was deduced. In SDT, the needs for autonomy, competence, and relatedness were introduced as basic psychological needs, and assumed that these three needs provided the natural motivation for learning, growth, and development. Second, an e-Learning system was created based on the deduced motivational strategy. Third, the system was implemented in 115 private tuition academies, and education was provided to 1,400 users for one year across the country. Afterwards, by surveying users, correlation between the role of the three psychological needs in learning English, and also the correlation between each need and motivation were investigated. Research results showed that traditional motivational theories used in face-to-face classes so far were effective in an e-Learning environment.

• Journal of Korea Multimedia Society
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• v.23 no.4
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• pp.595-602
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• 2020

We propose a generative probabilistic model with Dirichlet prior distribution for topic modeling and text similarity analysis. It assigns a topic and calculates text correlation between documents within a corpus. It also provides posterior probabilities that are assigned to each topic of a document based on the prior distribution in the corpus. We then present a Gibbs sampling algorithm for inference about the posterior distribution and compute text correlation among 50 abstracts from the papers published by IEEE. We also conduct a supervised learning to set a benchmark that justifies the performance of the LDA (Latent Dirichlet Allocation). The experiments show that the accuracy for topic assignment to a certain document is 76% for LDA. The results for supervised learning show the accuracy of 61%, the precision of 93% and the f1-score of 96%. A discussion for experimental results indicates a thorough justification based on probabilities, distributions, evaluation metrics and correlation coefficients with respect to topic assignment.

• Journal of Korean society of Dental Hygiene
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• v.15 no.5
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• pp.805-811
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• 2015

Objectives: The purpose of the study is to investigate the relationship between self-efficacy and learning attitude according to smoking experience in the middle school students. Methods: A self-reported questionnaire was completed by 608 middle school students in Gyeongnam from July 1 to 23, 2013. The questionnaire consisted of general characteristics of the subjects, smoking behavior, self-efficacy, and learning attitude. The questionnaire was adapted and modified from Kang, Park, and Koh. The self-efficacy was divided into general efficacy and social efficacy. The learning attitude was divided into attention concentration, learning method, and self learning. Data were analyzed using SPSS Win 21.0 program. Results: The nonsmoking students tended to have higher general efficacy and social efficacy than the smokers (p<0.01). The nonsmokers had more attention concentration in learning attitude than the smokers (p<0.001). The learning method (p<0.001) and self learning (p<0.001) showed the same results between the two groups. The smoking experience had the negative correlation with general efficacy (r=-0.164) and social efficacy(r=-0.154). The general efficacy is positively related to social efficacy (r=0.568). The smoking experience had the negative correlation to attention concentration (r=-0.235), learning method (r=-0.211) and self learning (r=-0.148). The attention concentration was positive relation with learning method (r=0.690) and self learning(r=0.662. The learning method had positive relation to self learning (r=0.764). Conclusions: The smoking students tended to have lower self-efficacy and learning attitude, so it is necessary to implement the smoking prevention program in the middle school students.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.