Antecedents of Satisfaction and Use of Mobile Learning in Higher Education

Abstract

The migration to emergency remote teaching has forced universities to adapt their teaching methodologies with the help of tools such as remote teaching, which has become a significant component of higher education technology. Additionally, higher education has enabled students to study, collaborate, and exchange ideas using the internet, technology, and mobile devices. Thus, this study analyzed which factors positively impacted satisfaction with mobile learning during the COVID-19 pandemic and which factors positively impacted the intention to use such devices in the future. Using research based on the Unified Theory of Acceptance and Use of Technology, data were collected from 498 undergraduate students at the State University of Campinas, Brazil, and analyzed using partial least squares structural equation modeling. In terms of intention to use, the results reveal that the most influential constructs are performance expectation, price, and hedonic motivations, while effort expectation, social influence, and facilitating conditions did not present a significant impact. Concerning the level of satisfaction, the constructs that have the most influence are hedonic motivations, performance expectation, effort expectation, price, and social influence. Only facilitating conditions did not show a significant impact on satisfaction. The results provided important information for improving the learning environment, teaching methods, curriculum formulation, and educational policy development. Furthermore, they contribute to Sustainable Development Goal 4 – Quality Education, by promoting new learning opportunities. Methodology: The research is based on the Unified Technology Acceptance and Use Theory. Data were collected from 498 undergraduate students from the State University of Campinas, Brazil, and analyzed with the application of the Partial Least Squares Structural Equation Modeling. Findings: The results in terms of Intention of Use reveals the most influential constructs are: Performance Expectation, Price and Hedonic Motivations, while Expectation of Effort, Social Influence and Facilitating Conditions did not show significant influence. On the other hand, in terms of Satisfaction, the constructs that most influence are: Hedonic Motivations, Performance Expectation, Effort Expectation, Price and Social Influence. Only Facilitating Conditions showed no significant influence on Satisfaction. Conclusions: The results provided important insights for improving the learning environment, teaching methods, curriculum formulation, and educational policy development, highlighting how to increase students' satisfaction and intention to use m-learning. In addition, they contribute to Sustainable Development Goal 4 – Quality Education, by promoting new learning opportunities.