Exploring the Drivers of University Students' Engagement of Online Learning Platforms Among Non-Native Arabic Speakers: A Case of Thailand's Southern Border Provinces

Abstract

The current study aims to explore university students' engagement in the use of online learning with a theoretical foundation beyond the pandemic. This technology was recently introduced to higher education, but few studies have examined its effects. A combination of the technology acceptance model (TAM) and social cognitive theory (SCT) is used in this study to examine the factors that impact university students' engagement and their academic performance in using online learning to teach Arabic language among non-native speakers. A questionnaire will be given to university students to acquire data for the suggested model. The effect of students' engagement using the online learning platform will be investigated using a hybrid approach consisting of partial least squares structural equation modelling (PLS-SEM) and an artificial neural network (ANN) to capture linear and nonlinear relationships within a non-compensatory model. The study will be interesting for scholars, policymakers, and practitioners from the higher education context.