Factors affecting social networks acceptance: An extension to the technology acceptance model using PLS-SEM and Machine Learning Approach

Abstract

Once the university started using social media more, the researchers started focusing more on how social media applications were being adopted and what motivated it without being limited to class-rooms only. There is a need to conduct further research about how the utilization of social media to teach in university affects education. Considering this, delving deeper into the educational outcomes and a research model related to the experiences and results of social media use is the aim of this research. Apart from that, the Technology Acceptance Model (TAM) research that deals with the behavior intention of using social networking media, perceived playfulness, perceived ease of use and perceived usefulness has been used for testing what affects the utilization of social media for online-teaching in higher education of United Arab Emirates. There was an assessment of 580 quantitative responses given by university students whose classroom sessions involved using social me-dia. In order to predict the behavioral intention of a pupil for using social networking media for elearning in the higher education institutions, it is possible to take some help from the factors such as perceived playful-ness, perceived ease of use and perceived usefulness, as per the partial least squares (PLS) and machine learning evaluation. The suggested model helps teachers to get to know more about how classroom sessions can become more productive through social media usage.