• 문화기술의 융합
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• 제9권5호
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• pp.335-342
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• 2023

본 연구는 대학생을 대상으로 학습몰입, 학업스트레스, 회복탄력성이 자기효능감에 미치는 영향을 확인하기 위해 시도되었다. 본 연구는 B, G시의 대학생 304명을 대상으로 하였다. 자료분석은 SPSS 22.0 프로그램을 이용하여 기술통계, t-test, ANOVA, 피어슨 상관계수, 다중회귀분석으로 분석하였다. 대상자의 자기효능감 평균 3.14±0.62점이었고, 일반적 특성에 따른 자기효능감의 차이는 성별(t=-2.533, p=.012), 전공만족도(F=5.687, p=.004)에서 유의한 차이를 나타냈다. 대상자의 자기효능감은 학습몰입(r=.574, p<.001), 회복탄력성(r=.525, p<.001)과 정적상관관계를 나타냈고, 학업스트레스(r=-.262, p<.001)와 부적상관관계를 나타냈다. 대상자의 회복탄력성은 학습몰입(r=.325, p<.001)과 정적상관관계를 나타냈고, 학업스트레스(r=-.291, p<.001)와 부적상관관계를 나타냈다. 학습몰입은 학업스트레스(r=-.211, p<.001)와 부적상관관계를 나타냈다. 대상자의 자기효능감에 영향을 미치는 요인은 학업몰입(β=.442, p<.001), 회복탄력성(β=.363, p<.001)으로 확인되었고, 설명력은 45.6%로 나타났다. 따라서 대학생의 자기효능감을 향상시키기 위해 학습몰입과 회복탄력성을 향상시킬 수 있는 교육 및 프로그램 개발과 적용이 필요하다.

• 문화기술의 융합
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• 제9권1호
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• pp.239-248
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• 2023

본 연구는 코로나 19로 인한 온라인 학습환경에서 간호대학생의 공동체 의식에 대한 온라인 협동학습 태도, 공감능력 및 비판적 사고성향의 영향을 확인하기 위한 서술적 상관관계 연구이다. 본 연구 대상은 간호학과에 재학 중인 129명이었으며, 자료분석방법은 SPSS 28.0 프로그램을 이용하여 기술통계, independent t-test, one-way ANOVA, Scheffé test, Pearson's 상관분석, 다중회귀분석을 이용하였다. 간호대학생의 공동체 의식의 가장 큰 영향요인은 온라인 협동학습 태도이었으며, 비판적 사고성향이 두 번째로 유의한 영향요인으로 나타났고, 42.2%의 설명력을 보였다. 본 연구결과를 바탕으로 비대면 학습환경에서 간호대학생의 공동체 의식을 높이기 위해서는 온라인 협동학습 태도와 비판적 사고성향을 함양할 수 있는 문제해결 중심의 학습방법을 강화할 필요가 있다.

• 디지털융복합연구
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• 제18권11호
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• pp.311-318
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• 2020

본 연구는 학점은행제 간호학과에 재학 중인 간호사를 대상으로 자기 결정성, 학습몰입, 학습성과의 정도와 상관관계를 파악하고 학습성과에 영향을 미치는 요인을 알아보기 위해 실시하였다. 자료수집은 B 시 소재 1개 학점은행제 간호학과에 재학 중인 간호사 144명을 대상으로 구조화된 설문지를 이용하였다. 자료수집 기간은 2018년 4월 1일부터 11월 20일까지였다. 자료는 SPSS/WIN 24.0을 이용하여 T-test, ANOVA, 상관관계 분석, 다중회귀 분석을 이용하였다. 대상자의 자기 결정성은 학습몰입, 학습성과와 정적상관관계가 있었고, 학습몰입과 학습성과도 정적상관관계가 있었다. 학습성과에 영향을 미치는 요인은 자기 결정성, 학습몰입이었고 총 설명력은 32.1%였다. 따라서 학점은행제 재학 간호사의 학습 성과를 증진하기 위하여 일반적 특성에 상관없이 자기 결정성, 학습몰입을 향상할 필요가 있다. 그러므로 간호사가 근무하는 기관에서도 간호사의 자기 결정성과 학습몰입을 증진할 방안이 필요하다. 본 연구결과가 학점은행제 재학생의 학습 성과를 향상하는데 기초자료로 활용될 수 있을 것이다.

• 한국치위생학회지
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• 제15권3호
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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.

• 컴퓨터교육학회논문지
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• 제11권6호
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• pp.85-94
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• 2008

이 연구는 온라인을 기반으로 한 원격교육의 학습효과를 증진시키기 위한 방안으로 학습자들이 지각하는 교류거리의 구조지각수준에 따른 성별, 학습만족도, 학습지속성, 학업성취도와의 관계를 알아보았다. 연구결과 학습자의 일반적 특성인 성별에 따른 교류거리의 구조지각수준은 의의 있는 차이가 없었다(p>.05). 교류거리의 구조지각수준과 학습자가 지각하는 수업만족도와 학습지속성과는 통계적으로 의의 있는 상관이 있는 것으로 나타났지만 학업성취도와는 유의한 차이가 발견되지 않았다(p>.05). 교류거리의 구조하위영역 중 수업만족도에 대한 영향력이 큰 하위영역은 과정 상호작용이며, 학습지속성에 대한 영향력이 큰 하위영역은 내용구성으로 나타났다.

• 대한가정학회지
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• 제48권1호
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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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• 제15권2호
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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.

• 한국멀티미디어학회논문지
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• 제23권4호
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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.

• 한국치위생학회지
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• 제15권5호
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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.

• 디지털산업정보학회논문지
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• 제14권4호
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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.