Student Success in Online Education: Investigating the Influence of Digital Competence, Learning Engagement, and Instructor Support

The rapid integration of artificial intelligence, learning analytics, intelligent tutoring systems, adaptive assessment, and connected learning technologies is reshaping higher education learning environments. However, research often examines smart learning environments, adaptive technologies, personalized learning, and student experience as separate domains, limiting an integrated understanding of their educational impact. This paper brings these perspectives together by identifying five recurring mechanisms: smart-environment infrastructure, learner modelling, adaptive content and assessment, feedback and learning visualization, and learner agency and self-regulation. The synthesis indicates that adaptive systems are most consistently associated with improved learning fit, engagement, self-regulation, and perceived usefulness when adaptation is timely, interpretable, and aligned with meaningful learning tasks. However, technological capability alone does not ensure better learning experiences; outcomes depend on how learner data support pedagogical decisions, the level of learner control, instructor involvement, and attention to privacy, transparency, and equity. Based on these findings, the paper proposes the Smart Personalized Learning Experience Framework (SPLEF), which connects smart-environment capabilities and adaptive technologies with personalization quality, learner processes, and learning experience outcomes. The framework provides a design-oriented basis for advancing learner-centred, data-informed, adaptive, and ethically responsible personalization in higher education.