Understanding and predicting academic performance through cloud computing adoption: a perspective of technology acceptance model

Abstract

Cloud computing is becoming an integral part of education community due to its strong acceptance and innovative application for fulfilling their academics needs. In this paper, we theorize how cloud computing adoption enhances student academic performance through personal characteristics and knowledge management paradigm using TAM as a theoretical base. Using survey approach, the present study recruited 322 universities students who are well aware of using cloud-based services (G-mail, G-drive, and WhatsApp). The proposed model and structural relationships validated by employing structural equation modeling in AMOS 24.0 version. How knowledge management dimensions and individual characteristics affect cloud computing adoption and students’ academic performance by integrating the TAM. The results illustrate that knowledge sharing, learnability, and knowledge application are positively associated with perceived-usefulness. Similarly, perceived-self-efficacy and perceived-enjoyment have a positive effect on perceived-ease-of-use. Moreover, perceived-usefulness and perceived-ease-of-use have a significant influence on cloud computing adoption which, in turn, positively accelerates the academic performance. Practical and theoretical implications are discussed followed by limitations and future research directions.