PREDICTORS OF STUDENT DISENGAGEMENT IN FULLY ONLINE HIGHER EDUCATION PROGRAMS

Introduction: The rapid expansion of fully online higher education has increased access for diverse student populations but has also intensified concerns regarding student disengagement. Disengagement in online learning extends beyond withdrawal or dropout and includes behavioral, motivational, psychological, and contextual dimensions that may precede formal attrition. This study sought to identify key predictors of student disengagement in fully online higher education programs within a globally diverse sample of online learners. Methods: A cross-sectional, correlational design was employed, with data collected from 140 students enrolled in fully online degree programs across multiple continents. Participants completed a detailed sociodemographic questionnaire and a purpose-designed 46-item disengagement instrument assessing behavioral, psychological, instructional, and contextual dimensions of disengagement. Descriptive statistics, Pearson correlation analyses, and multiple linear regression were conducted using STATA 18. Results: Overall disengagement levels were low to moderate (M = 2.39, SD = 0.48). Psychological and contextual factors emerged as the strongest correlates and predictors of disengagement. Digital fatigue, mental well-being burden, and time-zone or external demands were each independently correlated with higher disengagement. Instructional and social factors, including course design clarity, instructor presence, feedback quality, and sense of community, also significantly predicted disengagement after controlling for sociodemographic variables. Among background characteristics, full-time employment predicted higher disengagement, while older age was associated with lower disengagement. Conclusion: These findings suggest that student disengagement in fully online higher education is a multidimensional phenomenon shaped more strongly by psychological strain, instructional experiences, and contextual constraints than by static sociodemographic variables. Interventions aimed at reducing disengagement should therefore extend beyond course design improvements to include strategies addressing digital fatigue, mental well-being, and temporal flexibility in globally distributed online programs.