Akademik Veri Yönetim Sistemi
EDUCATION AND INFORMATION TECHNOLOGIES, cilt.29, sa.4, ss.3807-3836, 2024 (SSCI)
Online learning environments offer flexibility for learners who would like to study at a distance. However, research informs us that online learners are usually less likely to complete the learning experience and more likely to drop out compared to learners studying in traditional face-to-face learning environments. One major factor for low completion rates emerges as learners’ satisfaction with the learning experience. The purposes of the study were to investigate the structural relationships among the factors that affect online learners’ satisfaction and to develop a structural model that explains satisfaction in online learning environments. We used social cognitive theory and the Macro Model of Motivation and Performance as theoretical frameworks and investigated the structural relationships among metacognitive self-regulation, self-efficacy for interacting with the instructor and peers, task value, learning design, perceived learning, and satisfaction with the learning experience. Participants consisted of 1297 higher education students who were enrolled in fully online courses. We adopted the structural equation modeling approach to investigate the relationships among the factors in the research model. Results revealed that self-regulation, self-efficacy, task value, and learning design had significant effects on perceived learning and satisfaction and perceived learning significantly influenced satisfaction. Moreover, learning design had a large effect on perceived learning and perceived learning mediated the relationships between satisfaction and self-efficacy, task value, and learning design. The findings have implications for designing online learning environments that incorporate learning design standards and generate greater levels of learning outcomes.