Predicting the Intention to use Mobile Learning: A Hybrid SEM- Machine Learning Approach

Abstract

This research deals with the present perceptions of university students regarding mobile learning when it comes to their higher education. The learning type that depends on the different mobile device features can be referred to as mobile learning. It's easy to spot a plethora of mobile devices in most of the colleges; however, how ready students are when it comes to adopting mobile learning in the UAE needs more research. This study develops an integrated model through the integration of two different theoretical models, namely the technology acceptance model (TAM), theory of planned behavior (TPB). Four hundred eighty-nine university students provided with self-report data, which was analyzed using structural equation modeling. According to the results, the TAM gave a fine explanation of the acceptance of m-learning by university students. In terms of specifics, they had a better intention of adopting mobile learning under the influence of behavioral control, subjective norm, and attitude. For raising the mobile learning acceptance by university students, several important implications were acquired from the results. The present research aims to have a better look at how UAE's university students can use mobile phones for learning. This was made possible by using a suggested TAM & TPB for analyzing how the university students of UAE can utilize mobile devices to conduct homework, share knowledge, look on the Internet for discipline-specific info, and access course material.