Automation Triggers in Learning Journeys: Effects on Student Satisfaction and Continuance at Universitas Bangka Belitung
DOI:
https://doi.org/10.30872/impian.v6i1.10Keywords:
automation triggers, learning continuance, learning journey, student satisfaction, structural equation modelingAbstract
This study aims to examine the effects of automation triggers within the learning journey on student satisfaction and learning continuance in digital learning systems at Universitas Bangka Belitung. The research adopts a quantitative approach with an explanatory design to analyze causal relationships among the variables. Data were collected from 325 students who actively use the Edlink platform through a structured questionnaire using a five-point Likert scale. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that automation triggers have significant positive effects on the learning journey and student satisfaction. The learning journey also significantly influences learning continuance, indicating that a structured and guided learning process encourages continued use. In addition, satisfaction has a strong positive effect on learning continuance, confirming that students who are satisfied with the system are more likely to continue using it. Furthermore, automation triggers directly influence learning continuance and also exert indirect effects through satisfaction and the learning journey as mediating variables. Overall, the findings indicate that automation triggers play a crucial role in shaping the learning experience and promoting long-term engagement in digital learning environments.Downloads
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