Relationships among e‐learning systems and e‐learning outcomes: A path analysis model

In this study, path analysis modeling is applied to examine the relationships among e‐learning systems, self‐efficacy, and students' perceived learning outcomes in the context of university online courses. Independent variables included in the study are e‐learning system quality, information quality, computer self‐efficacy, system‐use, self‐regulated learning behavior, and user satisfaction as potential determinants of online learning outcomes. A total of 674 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest were used to fit the path analysis model. The results indicated that system quality, information quality, and computer self‐efficacy all affected system use, user satisfaction, and self‐managed learning behavior. The findings from the current study have significant implications for the distance educators, students, and administrators. First, university administrators must continuously invest to upgrade the systems so that e‐learning systems exhibit faster response time, better systems accessibility, higher system reliability and flexibility, and ease of learning. Second, the instructor in e‐learning courses should facilitate, stimulate, guide, and challenge his/her students via empowering them with freedom and responsibility. Third, In order for the e‐learning system to be successful, it should provide e‐learners with the information and knowledge they need.