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Transforming Education in the Middle East: Leveraging RPA and ML to Enhance Learning and Operational Efficiency

Majid Lateef Abdulrazaq,Saadah Hamdi Suwaidan,Haider AbdulKareem Alzuhiry,S. Aldulaimi,M. Abdeldayem

Published 2025 in 2024 International Conference on IT Innovation and Knowledge Discovery (ITIKD)

ABSTRACT

This study focuses on the adoption and effectiveness of Robotic Process Automation in conjunction with Machine Learning in blended learning environments in the Middle East. It seeks to understand the barriers encountered by trainer mentors in embracing these innovations and underscore the benefits they pose in improving learners, operational efficiency, and teacher's outcomes. The methodological approach taken in this study for writing the review is to identify, consider, and evaluate the quick and industry sources of information relevant to the integration of RPA and Machine Learning in mixed learning environments. This study adds to the ever-growing concern of transformation of learning and teaching processes in the Middle East by providing an in-depth analysis of the problems and possibilities brought by RPA and ML in blended learning. The primary concern is to formulate multi-layered, comprehensive strategies through integrated regional schemes for the incorporation of RPA and ML in mixed learning without infringing on data protection laws and ethical practices. Additionally, participate in the Framework and Infrastructure Training to Expand the Digital Economy and provide access to reasonable cloud-based solutions. Engage other stakeholders besides government agencies by collaborating with technology companies to test and implement RPA and ML solutions. Eventually, we need to foster a culture of innovation by making RPA and ML technology more visible to teachers, students and stakeholders.

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