Artificial intelligence (AI) has had a profound impact on engineering. To stay at the forefront of these changes, higher education institutions are increasingly embedding AI-oriented instruction into engineering programs to ensure curricula remain relevant. As AI reshapes the engineering landscape, an important question emerges: are engineering students adequately equipped with the mathematical foundations and competencies necessary to effectively develop, fine-tune, deploy, and evaluate AI models? This project develops a framework for a skills-based mathematical assessment instrument that bridges the gap between theoretical knowledge and practical AI-oriented,engineering applications.   

Through this funded QMUL-Cornell Global Hubs Research Seed Grant project, this will be achieved through establishling a firm, lasting and synergistic collaboration between Dr Werth at Cornell and Dr Shah at QMUL through mutual research visits, joint data collection, and analysis involving student researchers from both institutions. The project will culminate in peer-reviewed journal publications, applications for external grant funding, and a proof-of-concept framework for a cross-national mathematical skills inventory for engineers. This inventory will aim to address the skills-based challenges encountered in the context of mathematics within first- and second-year engineering programs.