Designing a Digital Twin Framework for General Foundation Program Students to Enhance Skill Development and Support National Competitiveness

Abstract

The General Foundation Program (GFP) serves as the primary gateway for Omani students entering higher education, focusing on the development of academic and soft skills essential for national development. However, traditional assessment methods, primarily static grades, fail to capture the complexity of a student’s journey or their readiness for the Fourth Industrial Revolution (4IR). This research proposes a Student Digital Twin (SDT) framework—a dynamic, data-driven virtual profile that mirrors a student's academic performance, learning behavior, and digital skill acquisition in real-time. By utilizing a qualitative conceptual synthesis, this paper outlines a four-layer architecture designed to provide personalized pedagogical support. The model explicitly aligns GFP learning outcomes with the strategic goals of Oman Vision 2040, transforming the foundation year into a predictive, high-tech engine for national competitiveness.