Educational Technology in a Post-Pandemic World: Global Trends, East Asian Perspectives, and Persistent Divides (2020–2026)
TL;DR
This systematic literature review synthesises 30 peer-reviewed studies published between 2020 and the review search cut-off in 2026, with particular attention to East Asian evidence in a global comparative perspective, to propose testable propositions and a future research agenda focused on longitudinal outcomes, learner agency, privacy, institutional readiness, and comparative equity.
Abstract
The COVID-19 pandemic accelerated the institutionalisation of online and hybrid education. At the same time, the subsequent diffusion of generative artificial intelligence (GenAI), learning analytics, and smart learning environments introduced new pedagogical, governance, and equity challenges. This systematic literature review synthesises 30 peer-reviewed studies published between 2020 and the review search cut-off in 2026, with particular attention to East Asian evidence in a global comparative perspective. Guided by PRISMA 2020, the review examines four mutually conditioning dimensions of post-pandemic educational technology: technological affordances, pedagogical integration, institutional capacity, and equitable participation. The synthesis shows that technology adoption and infrastructure expansion alone do not establish educational value. Meaningful outcomes depend on whether institutions translate technological capability into pedagogically appropriate course design, assessment, feedback, learner support, responsible data practices, and accessible conditions for participation. East Asian studies demonstrate rapid development in GenAI adoption, smart classrooms, learning analytics, and institutional digitalisation, but also reveal persistent rural–urban, literacy, participation, and outcome inequalities. Across contexts, the evidence further indicates that AI governance is not merely an administrative issue: policies governing transparency, privacy, accountability, academic integrity, and staff development can shape whether AI-mediated education mitigates or reproduces existing digital divides. The review advances an alignment framework in which durable and equitable educational value emerges when technological affordances are matched by pedagogical integration, institutional capacity, equitable participation, and responsible AI governance. It concludes by proposing testable propositions and a future research agenda focused on longitudinal outcomes, learner agency, privacy, institutional readiness, and comparative equity.