• Title/Summary/Keyword: e-Learning satisfaction

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A Study on the Structural Equation Modeling for the effect of e-Learning (대학생의 이러닝 학습효과 영향요인에 대한 구조방정식 모형 연구)

  • Heo, Gyun
    • Journal of Internet Computing and Services
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    • v.15 no.6
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    • pp.77-84
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    • 2014
  • The purpose of this study is to explore factors affecting the effect of e-learning, and to find out the casual relationship among these factors. Subjects are 2,091 students who have participated in e-learning based class during the period of second semester in 2013. Those of them, 1,732 students response to the survey questions. After gathering data, they are analyzed by using Confirmative Factor Analysis and Structural Equation Modeling. From the result of Confirmative Factor analysis, data have reduced four factors, and are named as four latent variables likes e-learning effect, contents satisfaction, managing assistant factor, and system functional factor. From the result of Structural Equation Modeling, it is known as the relation and impact among factors: (a) "managing assistant factor" affects to "contents satisfaction" directly. (b) "contents satisfaction" affects to "e-learning effect" directly. (c) "system function factor" affects directly to "contents satisfaction", but does not affect directly to "e-learning effect". (d) both "managing assistant factor" and "system function factor" have an indirect effect on "e-learning effect" via "contents satisfaction".

Effects of Learning Expectation and Perceived Knowledge Sharing on User Satisfaction and IS Continuance (학습기대와 지식공유 지각이 사용자 만족과 지속사용에 미치는 영향)

  • Kim, In Chan;Baek, Seung Nyoung
    • The Journal of Information Systems
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    • v.28 no.4
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    • pp.377-401
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    • 2019
  • Purpose The purpose of this study is to investigate the effects of learning expectation and perceived knowledge sharing on user satisfaction and IS continuance in the Korean Army which is currently using the Regiments' Information System to help their Integrated Administration Management. Based on both the Information System(IS) Continuance Model and IS Success Model, this study also examine the role of system quality on user satisfaction. We develop a research model(structural equation model) and its hypotheses that learning expectation, perceived knowledge sharing, and system quality increase users' satisfaction, which leads to IS continuance. The effect of learning expectation on perceived knowledge sharing is also hypothesized. Design/methodology/approach Online Survey using e-mails was administered to test our research model and associated hypotheses. Among the 360 e-mail letters including our survey questionnaire, 285 responses were collected via e-mails. Meaningful 225 cases were analyzed for our study. SPSS Statistics 24.0 and SmartPLS 3.0 were used to analyze both measuremant test and hyotheses test by using the data set. Findings Survey results show that learning expectation(confirmation variable), learning expectation, perceived knowledge sharing(a perceived usefulness variable), and system quality(a system characteristic) each increases user satisfaction, which leads to IS continuance, under the control of the effect of habit to use information systems. Learning expectation also has a positive influence on perceived knowledge sharing. Theoretical and practical implications are presented.

Key Factors Affecting Students' Satisfaction and Intention to Use e-Learning in Rwanda's Higher Education (르완다 고등교육기관 학생들의 e-러닝 만족도 및 사용의도에 영향을 미치는 핵심요인 연구)

  • Violaine, Akimana;Hwang, Gee-Hyun
    • Journal of Digital Convergence
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    • v.17 no.5
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    • pp.99-108
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    • 2019
  • This study aims to explore key factors which influence user's decision-making on the adoption of e-learning. We integrated UTAUT and Information Success Models to test that four independent factors affect student satisfaction to use e-learning in Rwanda's higher education. Data was collected by surveying students of University of Rwanda and Protestant Institute of Social Sciences (n=206). The analysis results showed that performance expectancy, facilitating conditions and effort expectancy except for social influence have a significant effect on students' satisfaction. This can help university administrators understand the factors that influence students' adoption of e-learning and incorporate these results into Rwanda's e-learning design and implementation. In final, Rwanda's government can contribute to establishing the e-learning policy and allocating its relevant resources centered on student needs.

A Study on Interaction Factors for Knowledge Transference of e-Learning (e-Learning의 원활한 지식전달을 위한 상호작용 환경에 관한 연구)

  • Kang, Inwon;Lee, Ji Won
    • Knowledge Management Research
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    • v.10 no.1
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    • pp.17-32
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    • 2009
  • Cyber University has been continuously increased since it is of great necessity of education through lifelong study. Recently, the management of cyber universities does not ensure education success, because some problems are coming out. Now we are to take an interest in qualitative level of e-learning. The purpose of this study is to classify and investigate interaction factors of e-learning, which were one of the restrictions to develop e-learning, influence learning flow and satisfaction. The authors discuss the implications of the findings for interaction and learning flow theory and practice.

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What Quality Factors Affect to the e-Learning Performance (e-러닝 성과에 영향을 미치는 품질요인에 관한 연구)

  • Kim, Sung-Gyun;Sung, Hang-Nam;Jeong, Dae-Yul
    • The Journal of Information Systems
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    • v.16 no.1
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    • pp.201-230
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    • 2007
  • Recently, the growth of e-Learning systems and its related information technology has presented a unique challenge for both schools and industry. It would make an extremely phenomenal paradigm shift in the educational method and practice. Methods of assessing the quality of e-teaming services and contents are critical issue in both practice and research. Moreover, many researchers are interested in what qualify factors more affect to the Performance of e-Learning service. Nevertheless, service quality is a construct that is difficult to define and measure. e-Learning services are composed of many factors, and they are more complicated than the traditional education services because they we performed on the distance basis and the many platforms of IT infrastructure. The purposes of our research are to classify the e-Learning service dimension and identify their factors, to develop the measurement of the factors, and finally to test empirically their relationship between the service factors and e-Learning service performance. For the development of the service factors we considered SERVQUAL model and SERVPERF model which were developed in the service marketing area. The SERVQUAL model was more fitted to the e-Learning services than the latter. From that we derived several factors that fit to our research domain, ie, tangibles, access, reliability, credibility, security, responsiveness, assurance, empathy. We combined three factors of them(reliability, credibility, security) into a factor, system stability for the semantic simplicity, and divided responsiveness factor into system operator responsiveness and teacher responsiveness as the entity based dimension classification. In the e-Learning services research, Most researcher are mentioned the quality factors of contents, so we added to two contents quality factors, ie, contents production method and richness of contents itself. We examined the relationship between the service quality factors and e-Learning performance(student satisfaction and service reuse intention). As result three quality factors(contents production method, teacher responsiveness, empathy) significantly affected student satisfaction. To the other performance variable, ie, service reuse intention, the teacher related quality factors(such as teacher responsiveness, assurance, empathy) affected only. In conclusion, even in the on-line distance teaming, the teacher's role md earnestness is as important as ever.

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The effects of computer self-efficacy, self-regulated learning strategy, and LMS quality on e-learner's satisfaction (이러닝 학습자 만족에 영향을 미치는 컴퓨터 자기 효능감, 자기 조절 효능감 및 LMS 품질)

  • Lee, Jong-Ki
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.4
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    • pp.97-106
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    • 2007
  • According to the 2004 Sloan Consortium Report, distance education is the fastest growing sector of higher education. This study suggests a research model, based on an e-Learning success model, the relationship of the e-learner's self-regulated learning strategy, computer self-efficacy, and system quality perception of the e-Learning environment. As a result, perceived usefulness, perceived ease of use, and service quality effect on e-learner's satisfaction. In addition to, self-regulated learning strategy based on computer self-efficacy is also important variable regarding e-learner's satisfaction.

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The Impact of Achievement Motivation on Academic Achievement and Satisfaction of Adult Learners in an e-Learning Environment

  • HA, Young-Ja;CHUNG, Se-Jin
    • Educational Technology International
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    • v.7 no.1
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    • pp.59-79
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    • 2006
  • The purpose of this study is to measure the impact of motivation on academic achievement and satisfaction of adult learners in an e-Learning environment, and to come up with strategies to improve the effectiveness of e-Learning for adult learners. In order to find answer, devices were developed, tested for validity and reliability, and use for testing variables for 289 adult learners. To measure the impact of achievement motivation on learning in job training, a multiple regression analysis was performed. The analysis results show that achievement motivation has an impact on academic achievement with significance level .001, but does not have an impact on a learner's satisfaction. Further analyses on the subcategories of achievement motivation show that individual-oriented motivation affects achievement with significance level of .001, while social-oriented motivation does not. From this finding, some strategies to boost individual-oriented motivation are suggested to enhance effectiveness of job training in e-Learning environment. Further strategies to boost individual-oriented motivation should be developed by studying various aspects of e-Learning such as learning environments, learning culture, learning modes and methods, and evaluation.

An Exploratory Study of e-Learning Satisfaction: A Mixed Methods of Text Mining and Interview Approaches (이러닝 만족도 증진을 위한 탐색적 연구: 텍스트 마이닝과 인터뷰 혼합방법론)

  • Sun-Gyu Lee;Soobin Choi;Hee-Woong Kim
    • Information Systems Review
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    • v.21 no.1
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    • pp.39-59
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    • 2019
  • E-learning has improved the educational effect by making it possible to learn anytime and anywhere by escaping the traditional infusion education. As the use of e-learning system increases with the increasing popularity of e-learning, it has become important to measure e-learning satisfaction. In this study, we used the mixed research method to identify satisfaction factors of e-learning. The mixed research method is to perform both qualitative research and quantitative research at the same time. As a quantitative research, we collected reviews in Udemy.com by text mining. Then we classified high and low rated lectures and applied topic modeling technique to derive factors from reviews. Also, this study conducted an in-depth 1:1 interview on e-learning learners as a qualitative research. By combining these results, we were able to derive factors of e-learning satisfaction and dissatisfaction. Based on these factors, we suggested ways to improve e-learning satisfaction. In contrast to the fact that survey-based research was mainly conducted in the past, this study collects actual data by text mining. The academic significance of this study is that the results of the topic modeling are combined with the factor based on the information system success model.

The Study of Factors Affecting the e-Learning Performance (e-Learning 학습 성과에 영향을 미치는 요인 분석)

  • Lee, Moon-Bong;Kang, Byung-Young
    • Journal of Korea Society of Industrial Information Systems
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    • v.12 no.5
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    • pp.173-182
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    • 2007
  • e-Learning can be seen as not only one of Internet based information systems which can provide education services, but also one of teaching-learning methods which can implement self-directed learning. This paper tests factors affecting the e-Learning performance based on information systems success model and self-efficacy theory using a field study. Questionnaires are collected from 216 students who are enrolling a e-learning class using online survey. The results are following: first, the service quality and self-efficacy are significant predictors of use intention, but system quality and information quality are not. second, the system quality, information quality, service quality and self-efficacy are significant predictors of user satisfaction. Third, use intention and user satisfaction are found to be a strong predictor of the learning performance.

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A Study on the Characteristics Satisfaction in Digital Convergence based Micro-Learning (디지털융합 기반 마이크로러닝 특성 만족도 연구)

  • HAN, Tae In
    • Journal of Digital Convergence
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    • v.18 no.6
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    • pp.287-295
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    • 2020
  • This study defined the characteristics of micro-learning emerging by mobile learning and micro-contents in the e-learning field, and analyzed the satisfaction of application, to see if micro-learning could become a new learning type in the future. To this end, the characteristics of micro-learning were defined through preliminary literature analysis, the characteristic satisfaction was verified in the well-equipped micro-learning site, and any other technical functions were suggested through expert opinion gathering. It was suggested that the future technology of e-learning should be linked to technical functions such as learning analysis and performance measurement. According to the results of this study, if micro-learning reflects its functional characteristics well, it will become an effective learning type in the e-learning field and will greatly contribute to education, learning, and training for the new millennial.