Blended Learning Models in Smart University Education

Abstract

The study aimed to systematically review and analyze blended learning models within smart university environments, focusing on design frameworks, success factors, and educational outcomes. This qualitative review employed a thematic analysis approach. Data were collected through a systematic review of peer-reviewed articles published between 2015 and 2025 from databases such as Scopus, Web of Science, Springer, ScienceDirect, and ERIC. After screening and applying inclusion criteria, 12 high-quality studies were selected based on theoretical saturation. Data were analyzed using NVivo 14 software through open, axial, and selective coding. The results revealed three major themes: (1) design models—including flipped, flexible, project-based, and adaptive intelligent frameworks; (2) key success factors—technological infrastructure, digital competence of instructors, student motivation, and institutional support; and (3) learning outcomes—enhanced self-regulation, improved academic performance, development of 21st-century skills, and increased learner satisfaction. The integration of pedagogy and technology emerged as a central determinant of blended learning success in smart universities. Blended learning in smart higher education represents a transformative paradigm that balances human interaction with digital technology to enhance learning quality and student engagement. Successful implementation requires robust technological infrastructure, digital training for faculty members, and adaptive assessment and feedback systems. The findings provide insights for policymakers, educational leaders, and curriculum designers aiming to optimize blended learning frameworks in smart university ecosystems.