Predicting the intention to use google glass: A comparative approach using machine learning models and PLS-SEM

Technology-based education is the modern-day medium that is widely being used by teachers and their students to exchange information over applications based on Information and Communication Technology (ICT) such as Google Glass. There is still resistance shown by a few universities around the globe when it comes to shifting to the online mode of education. While few have shifted to Google Glass, others are yet to do so. We base this study to explore Google Glass Adoption in the Gulf area. We thought that introducing the teachers and students to all the pros that Google Glass presents on the table might get their attention in considering using it as the medium to exchange information in their respective institutes. This paper presents the structure of a framework depicting the association between TAM and other Influential factors. All in all, this investigation analyzes the incorporation of the Technology Acceptance Model (TAM) with the major features associated with the method such as instructing and learning facilitator, functionality, and trust and information privacy to improve correspondence among facilitators and students during the learning process. A total of 420 questionnaires were collected from various universities. The data that was gathered through the surveys was employed for the analysis of the research model using the Partial least squares-structural equation modeling (PLS-SEM) and machine learning models. The outcome showed that the factor of functionality and trust and privacy goes hand in hand with perceived usefulness and perceived ease of use associated with Google Glass. Both the Factors, Perceived usefulness and perceived ease of use have a significant impact on Google Glass adoption. This implies the significant impact of Perceived ease of use and Trust and privacy on the adoption of Google Glass The study also offers practical implications of outcomes for future research.