While many researchers have investigated the adoption and usage of online learning in different settings, one area that has yet to be examined thoroughly, particularly in the context of online learning in Yemen, is the self-efficacy role. The purpose of this paper is to extend the Delone and McLean information system success model by incorporating a self-efficacy construct as an antecedent to user satisfaction and actual usage to predict student performance.
Questionnaire survey method was used to collect primary data from 448 students in nine public universities in Yemen. The six constructs in the proposed model were measured using existing scales. The data analysed using confirmatory factor analysis and structural equation modelling via AMOS.
Three main results were revealed, namely that overall quality (system, information and service quality) and self-efficacy have a positive impact on user satisfaction and actual usage; that actual usage significantly predicts user satisfaction; and that both user satisfaction and actual usage have a positive impact on student performance.
First as the study population were students from nine public universities, it excluded academics and administrative staff. Second, the study depends on self-reported measures to test the proposed research model. This is because getting objective data about the performance was not probable due to the issue of privacy.
The findings of this study can be a guideline for Yemeni higher education institutions to develop efficient and effective plans to improve the performance of education institutions, and train and develop student ability to use online learning. Additionally, it highlights the areas that university management needs to concentrate on, namely information systems (IS) tools that will contribute to higher student enrolment, address the lack of infrastructure and improve the quality of education outcomes, things which represent Yemen’s main challenges in the higher education sector.
This paper adds to the existing literature of IS by combining overall quality, self-efficacy, actual usage and user satisfaction to predict performance impact of online learning among students in nine public universities in Yemen. Furthermore, the predictive power of the proposed model has a higher ability to explain and predict performance impact compared to those obtained from some of the previous studies.
