Knowledge and innovative factors: how cloud computing improves students' academic performance
Interactive Technology and Smart Education
Purpose Collaboration, communication, critical thinking and creativity are the most essential Cs of education. However, at present, these Cs are interlinked with technology to make it more effective and reliable. Educational technology infuses higher education, many people use it on a daily basis. Students are eager to adopt such technologies that help them in academia. Hence, this study aims to investigate how cloud computing adoption influences the academic performance of students by incorporating innovative, knowledge, economic and technological factors in the model. Design/methodology/approach The data are collected by using the survey method and the five-point Likert scale is used for this purpose. The statistical techniques applied to the data set were confirmatory factor analysis and partial least square structural equation modeling. Findings All dimensions have been observed to have a positive association with perceived ease of use and perceived usefulness. On the other hand, the innovative factors which include relative advantage and complexity have a negative impact on perceived ease of use and perceived usefulness except for compatibility. Moreover, economic factors, all have a negative relationship. Finally, research shows that perceived ease of use and perceived usefulness have a direct and significant relationship with cloud computing adoption among students, which ultimately predicts their academic performance. Originality/value Present research makes the following vital contributions; first, focus on the role of innovative factors, economical, technological and knowledge factors together that were previously largely ignored. Second, it extends the model of technology acceptance model for analyzing the cloud computing adoption pattern among university students. Finally, this study uses PLS-SEM for analyzing the relationship.
Behavior, higher education, students, cloud computing, teaching methods, academic performance, technology acceptance model, Smart PLS, Pakistan