2026 ASEE Annual Conference & Exposition

At xxxxxx University, two Engineering Technology courses are integrating artificial intelligence (AI) tools to enhance student engagement and support faculty instruction. Using Microsoft Copilot with enterprise data protection, the project tracks student progress and provides timely, personalized feedback. The two courses, from freshman to junior levels, apply an AI-based approach to identify students at risk during key points in the semester and help them stay aware of their academic standing.

The initiative aims to improve student success and retention through early and responsive support. Faculty use AI-generated data to monitor course performance and adjust teaching strategies to strengthen engagement. This paper outlines the implementation process, describes the methods used to identify at-risk students, and shares preliminary outcomes on student performance and persistence.