SUPPORTIVE LEARNING ECOSYSTEMS IN TECHNOLOGY-ENHANCED ENGINEERING EDUCATION: EFFECTS OF TEACHER SUPPORT, PEER SUPPORT, AND DIGITAL LEARNING CONTEXT QUALITY ON STUDENT ENGAGEMENT VIA ACADEMIC SELF-EFFICACY

Student engagement in technology-enhanced higher education is shaped not only by instructional design but also by the social and psychological ecosystem surrounding learners. This study examines how perceived teacher support, peer support in class, and technology-enhanced learning context quality influence student engagement through the mediating role of academic self-efficacy in engineering education. Using a quantitative cross-sectional design, data were collected from 423 undergraduate engineering students in India through purposive sampling. Covariance-based structural equation modeling (CB-SEM) was employed to test the hypothesized relationships. Results indicate that teacher support, peer support, and digital learning context quality significantly predict academic self-efficacy, which in turn exerts a strong positive effect on student engagement. All three support factors also demonstrate significant direct effects on engagement, confirming partial mediation. The model explains substantial variance in both academic self-efficacy and engagement, highlighting the importance of integrated support systems. The findings suggest that engagement in technology-rich classrooms emerges from a supportive learning ecosystem where relational trust and well-designed digital environments reinforce students’ competence beliefs. This study extends engagement theory into technology-enhanced engineering education and provides practical guidance for faculty development, peer learning design, and digital pedagogy. Strengthening academic self-efficacy through supportive ecosystems may represent a critical strategy for sustaining engagement in modern higher education.