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

Abstract

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. Six drivers were included to examine 11 paths of the study framework. The instrument was adapted from previous studies and validated through content validity. Further, it was piloted to 76 PSETs for the 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 the eleven paths are significant. The strongest significant relationship is reported to emerge between perceive 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 use of m-LMS. Recommendations for future research regarding the behavioral intention to use m-LMS in developing countries are provided.

Learning Management System Usage among Undergraduates in a Developing Context: An Extension to the Technology Acceptance Model

“…In accordance with the above, it is evident that there are more researchers who have used Subjective Norm, for example [59], [78], [82], [83], [1], [26], [85], [86], [87], [88], [89], [90], [91], [92], Experience in the internet & computer [59], [77], [81], [82], [84], [85], [93], [94], [95], [96], [97] Self-Efficacy [59], [83], [84], [85], [1], [71], [72], [73], [86], [95], [98], [99], [74], [97], Technical Support [59], [42], [73], [74], [83], [100], [101], [102] and Anxiety [72], [73],…”

“…Researchers [78], [88] identified that Subjective Norms have no significant impact on Perceived Usefulness while other researchers [26], [59], [82], [86], [87], [89], [90], [91], have identified that Subjective Norms have a significant positive impact on Perceived Usefulness.…”

“…Researchers [78], [82], [86], [90], identified that Subjective Norms have no significant impact on Intention to Use computers while another researchers [59], [89], [92], identified that Subjective Norms have a significant positive impact on Intention to Use computers.…”

“…Subjective Norm was assumed to influence intentions of use directly [59], [89], [92] and Subjective Norm influence intentions of use through Perceived Usefulness [26], [59], [78], [82], [86], [87], [89], [90], [91]. The Perceived Ease of Use influences Perceived Usefulness of a system [59], [78], [122], [141].…”

Quality Assurance for Sustainable Higher Education: Structural Equation Modeling

“…Meanwhile, KSC and employability were proposed to be predicted by educational process, practical activities, and research activities (Figure 1). The study implemented a cross-sectional survey design [25][26][27]. This design is described as quantitative research procedures, providing a survey administration to samples or the whole population.…”