Improving Mental Health Support in Engineering Education using Machine Learning and Eye-Tracking.

This study proposes an innovative approach to improve mental health support for students in engineering using machine learning (ML) and eye-tracking technology. Leveraging cutting edge technology, this approach aims to fill a gap in the literature by providing a tool to tackle the growing mental health crisis among engineering students, furthermore, this approach provides a novel method to integrate technology-based mental health support into engineering curriculum.