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This study delves into the intricate factors influencing the intention to use mobile learning among students in online flexible distance learning higher education institutions, with self-efficacy serving as a pivotal mediator. The primary objective is to comprehensively assess the direct and indirect impacts of performance expectancy, facilitating conditions, effort expectancy, and self-management learning on the intention to engage with mobile learning platforms. Through a meticulous survey methodology, questionnaires were disseminated via email using purposive sampling, yielding a commendable response rate. Out of the 544 surveys distributed, 431 were successfully collected, and 403 clean datasets were meticulously analyzed. Employing advanced Structural Equation Modeling (SEM) techniques with the aid of Smartpls4 software, the study rigorously examined the relationships between key variables. The empirical findings unveiled compelling insights, showcasing the significant positive relationships between effort expectancy, self-management learning, and self-efficacy to utilize mobile learning. Moreover, facilitating conditions and self-efficacy emerged as influential factors, with self-efficacy playing a crucial mediating role in shaping students' intentions. The study's theoretical implications extend beyond conventional technology acceptance models, shedding light on the intricate interplay of cognitive, motivational, and contextual factors in mobile learning usage. These findings offer a robust foundation for advancing existing technology acceptance frameworks and provide a nuanced understanding of the multifaceted dynamics influencing students' intentions toward mobile learning adoption. Furthermore, the practical implications underscore the importance of enhancing mobile learning initiatives by prioritizing usability, accessibility, technical support, and fostering learners' self-efficacy. This holistic approach aims to optimize the educational experience and promote effective utilization of mobile learning technologies in online flexible distance learning environments.
Osman et al. (Tue,) studied this question.