Academics' behavioral intention and usage of IoT in e-learning: moderation of gender and experience

Abstract

As the world shifts to e-learning, IoT is becoming increasingly important in the learning and teaching environment. The key concerns are the elements that influence academics' behavioral intention to adopt IoT, and how the whole operation affects their performance. However, there is a research gap in past studies that have not addressed this issue sufficiently. As a result, this study employed the Unified Theory of Acceptance and Use of Technology (UTAUT) as a guideline to examine the factors that influence academics' behavioral intentions to use IoT. Furthermore, the moderating effects of both gender and level of experience on this relationship were inspected. The structural models were validated, and the predefined hypotheses were presented (n = 321). The results from the Structural Equation Modeling approach using Amos 26 indicate that performance expectancy, social influence, and effort expectancy directly influenced behavioral intentions to utilize IoT. The findings also showed that facilitating conditions were the most important determinant of academics' actual usage of IoT. The structural model was further investigated according to the experiences of the male and female academic groups. The findings revealed a different pattern of strength and significant relationships between groups with the overall model, implying that gender and experience act as moderators. This study provides a wealth of antecedents from which to construct a thorough theory of IoT adoption. The theory explores the elements that influence academics' willingness to utilize IoT from the standpoints of the technology itself, social context, and individual user characteristics. By employing the proposed approach, Universities can modify their EL strategies to make the most of their resources and in turn improve efficiency.