Blended Learning Design in Higher Education: A Systematic Review Through TPACK and AI Role Perspectives (2020–2025)

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Authors: Daniel Dang, Noor HS Alani, Wathsala Nayani, Emre Erturk
Cited by: 1
References: 79

Abstract

This systematic literature review (SLR) examines the evolving nature of blended learning (BL) in higher education from 2020 to 2025. While BL is widely promoted for its flexibility, accessibility, and inclusivity, its practical application is uneven. This review integrated findings from 63 peer-reviewed studies obtained from five major academic databases and employed the PRISMA 2020 protocol to ensure methodological transparency and research quality. Findings were analysed using the Technological Pedagogical Content Knowledge (TPACK) model and the AI Roles Framework to assess instructional design and technology integration. This analysis was conducted through a thematic approach to identify recurring patterns and key insights across the literature on BL and the use of emerging technologies such as AI, AR/VR, and learning analytics within BL. The study identifies three main challenges. There is an excessive application of tool-centric models such as TAM and UTAUT. Engagement with educators, administrators, and under-represented learners is limited. Ethical considerations related to the use of AI, AR/VR, and learning analytics are often overlooked. The most common issue is the higher dependence on models such as TAM and UTAUT. The review also shows that many educational applications reproduce similar design patterns and content structures, while insufficiently responding to learner diversity, digital readiness, accessibility needs, self-regulation capacity, and disciplinary context. While these models are helpful, they frequently limit complex teaching and learning environments to simple patterns of user behaviour. It is also clear that voices from teachers, support staff, and less-represented student groups are missing from the discussion. This is considered a serious concern because these technologies are increasingly being used in education. Moving forward, there is a clear need to shift away from rigid, technology-led models toward more adaptive, pedagogy-focused approaches. These findings contribute to a deeper understanding of blended learning as an interconnected educational system. They also offer implications for future research, inclusive digital pedagogy, and policy development in higher education.

Fields of Study & Subjects

Online Learning and Analytics E-Learning and COVID-19 Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Education Sciences
Publisher
MDPI AG
Volume
16
Issue
6
Pages
848–848
Publication date
28 May 2026
Language
EN