PREDICTING THE INTENTION TO USE GOOGLE GLASS IN THE EDUCATIONAL PROJECTS: A HYBRID SEM-ML APPROACH - Alfaisal, Raghad (2022)
The emergence of newer technology and rapid global changes has led to the development of technology-based education environments, wherein teachers and students interact via technological interfaces such as Google Glass. Very few educational institutions have, however, opted to use this interface. The reason for this tendency is not very well understood or adequately researched. Therefore, this study aims to understand the factors influencing the adoption of Google Glass in the UAE. Our hypothesis is that providing information about the salient features and practical applications of Google Glass to teachers and learners would result in a higher percentage of educational institutions using this technology. The findings of this study will be based on the interrelation between the Technology Acceptance Model (TAM) and other influential factors. It will evaluate the integration of TAM with the well-known influential features of the device such as enhancement of teaching, facilitation of learning, functionality of motivating learning, and assurance of trust and information privacy. These features play a key role in facilitating communication between teachers and students in the classroom environment. Our approach will make use of hybrid analysis techniques involving Structural Equation Modeling (SEM) and Machine Learning (ML). This work of research thus proposes to offer practical inputs that can help decision-makers and other practitioners focus particularly on creating conducive environments for the use of Google Glass as well as further adopt strategies for meeting their specific needs.