| Summary: | 碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 100 === With the rapid growth of the Internet and the proliferation of information technologies, online or electronic learning (e-learning) environments offer the possibilities for communication, interaction and multimedia material delivery that enhance learner-directed learning. E-learning can offer potential learners an alternative and innovative learning environment compared with traditional learning and, thus, represents an innovation in education. However, what the factors are influence the user continue to use E-learning system. The objective of this study is to propose a research framework that investigates the relation between perceived fit and system factors that can motivate learners in continuing utilizing an iLMS e-learning system. This study integrates DeLone & McLean’s IS success model (include: system quality, information quality, and service quality), computer self-efficacy, and system satisfaction to understand students continuance intention of iLMS e-learning system. A structural equation model reveals that computer self-efficacy, system quality, information quality, service quality determines system satisfaction, which in turn influence students'' continuance intention iLMS e-learning system. This is a study of university of science and technology of college students, in central Taiwan, 700 questionnaires issued, 693 were retrieved, and 650 valid questionnaires were retrieved and effective retrieved rate of 93.8%, except the invalid ones. Statistical methods are including the confirmatory factor analysis, descriptive unvaried analysis, independent t-test, ANOVA, pearson correlation analysis, and structural equation modeling analysis. The structural equation modeling analyzing the path dimensions relevance.
After analyzing these questionnaires, we came up with the following seven conclusions.
1.Students from different background have different satisfied ratings on the computer self-efficacy.
2.Students from different background have not satisfied ratings on the system quality.
3.Students from different background have not satisfied ratings on the information quality.
4.Students from different background have different satisfied ratings on the service quality.
5.Students from different background have different satisfied ratings on the system satisfaction.
6.Students from different background have not satisfied ratings on the continuance intention.
7.The computer self-efficacy, system quality, information quality, system quality and continuance intention positive correlation in the iLMS e-learning system.
The results provide insight into those factors (information quality, system quality, and computer self-efficacy) that are likely significant antecedents for planning and implementing an iLMS E-learning system to enhance student learning satisfaction.
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