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openalexJournal of Intelligent Decision Making and Information Science2026-07-23Cited by 0

Mapping the Landscape of Robotic Process Automation in Education: A Systematic Literature Review

Van-Huy Chu Xuan-Lam Pham

Robotic Process Automation (RPA) has increasingly been adopted to improve operational efficiency across multiple industries, including the education sector. However, despite the growing number of studies on RPA, existing research in educational contexts remains fragmented, particularly regarding its practical applications, organizational implications, and integration with emerging technologies. To address this gap, this study combines bibliometric analysis with a systematic literature review to provide a comprehensive overview of the evolving research landscape of RPA in education. Using a PRISMA-guided review process, 148 records were initially retrieved from the Scopus database. After screening, 78 publications were retained for bibliometric analysis, and 33 studies were selected for in-depth qualitative synthesis. The bibliometric analysis indicates a rapidly expanding research field characterized by increasing attention to intelligent automation and digital transformation within higher education systems. The systematic review complements these findings by synthesizing evidence on three interrelated aspects: the practical applications and benefits of RPA in educational environments, the organizational transformations required to support automation adoption, and the integration of RPA with emerging technologies. Overall, the literature suggests that RPA can substantially enhance administrative efficiency, reduce routine workloads, and enable data-driven decision-making in educational institutions. Nevertheless, the successful implementation of RPA depends on the ability of institutions to address key socio-technical challenges, including governance mechanisms, organizational readiness, and the development of relevant digital skills among staff. This study contributes a comprehensive synthesis of the current research landscape and identifies future research directions toward intelligent and learner-centered automation in higher education.

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