Socio-psychological and technological predictors of academic resilience in online graduate programs in STEM and natural sciences
Paper Details
Socio-psychological and technological predictors of academic resilience in online graduate programs in STEM and natural sciences
Abstract
This study developed a conceptual model of academic resilience in online graduate programs in STEM and natural sciences across select Philippine public higher education institutions. Employing a convergent parallel mixed-methods design, the research examined how socio-psychological and technological factors influence the capacity of graduate students to adapt and thrive in virtual learning environments. Quantitative data were collected from 350 STEM-focused graduate students using a correlational design and analyzed via Structural Equation Modeling (SEM) to determine the effects of self-efficacy, social support, satisfaction, and digital adaptability on academic resilience. Complementary qualitative insights were gathered through thematic analysis of semi-structured interviews with 30 purposively selected graduate students actively engaged in online STEM education. Findings revealed that self-efficacy exerted the strongest direct influence on academic resilience (β= 0.65, p= 0.001), followed by social support (β= 0.48, p= 0.002). Notably, satisfaction partially mediated the impact of self-efficacy (β= 0.55), while digital adaptability fully mediated the link between social support and resilience (β= 0.60). Thematic results reinforced these statistical findings, emphasizing the importance of learner confidence, access to peer and instructor support, and the value of well-structured, engaging online content in science-related disciplines. The study highlights the critical interplay of psychosocial readiness and digital competence in sustaining academic engagement within STEM and natural science programs. Recommendations include developing resilience-centered instructional design, targeted faculty training, and institution-led support systems to enhance graduate students’ capacity to persist in technology-mediated scientific education.
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