Exploring the Drivers Predicting Behavioral Intention to Use m-Learning Management System: Partial Least Square Structural Equation Model

This study aimed at reporting the drivers predicting Pre-Service English Teachers' (PSETs) behavioral intention to use m-learning Management Systems (m-LMS) in their learning activities. To achieve the purpose of the study, an extended Technology Acceptance Model (TAM) was administered. Seven variables were included to examine 11 paths of the framework. The instrument was adapted from previous studies and validated through content validity. Further, it was piloted to 76 PSETs for reliability. Two hundred and ten responses were analyzed for the main study. The results of the study were obtained by implementing the procedures of Partial Least Squares Structural Equation Modeling (PLS-SEM). The extended TAM-based drivers are reported to be valid and reliable in the measurement model stage. In the assessment of the structural model, nine out of eleven hypotheses are significant. The strongest significant relationship is reported to emerge between perceived usefulness and attitude toward m-LMS, while the weakest significant relationship is reported between self-efficacy and perceived usefulness. On the other hand, the two paths that are not positively correlated are between; 1) supporting condition and perceived usefulness; 2) subjective norm and behavioral intention to use m-LMS. Recommendations for future research regarding the use of m-LMS in developing countries are provided.