Our work sits at the intersection of innovation, evidence, and responsibility. We investigate how Generative AI is reshaping engineering and computing education, with a particular focus on ethical integration, faculty practice, and student learning. Through empirically grounded studies, validated research instruments, collaborative partnerships, and national dissemination efforts, REACT-E advances data-driven insights that inform how AI can be thoughtfully and effectively embedded into technical education. This page highlights our current projects, conference presentations, and scholarly publications that are shaping conversations across engineering education and beyond.
Insights into Faculty’s use of Generative Artificial Intelligence systems in Engineering Classrooms
Abstract
This study investigates the usage of Generative Artificial Intelligence (GenAI) tools among faculty in construction, engineering, and computing disciplines. With the rapid proliferation of Generative AI among students, faculty, and professionals, it is crucial to understand how faculty engage with GenAI, manage its use by students, and cultivate awareness of its applications within their respective professions. This research explores several key areas: a) the extent to which faculty have adopted these technologies, b) the barriers and challenges they face in integrating GenAI into their teaching practices, and c) their aptitude for training and professional development in GenAI tools. A critical question raised in this study is" What is the current awareness among faculty about available professional development opportunities related to GenAI, and how willing are they to integrate these tools into their curricula? The findings aim to offer insights into how we may start bridging gaps between pedagogy, technology, and the use of GenAI in engineering and related fields. Additionally, we offer an overview of faculty readiness and perceptions regarding the integration of GenAI, identifying areas where further support, training, or resources may be needed to enable the effective use of GenAI in educational settings. Understanding these aspects will inform how GenAI tools can be leveraged to enhance learning experiences in engineering classrooms, bridging gaps between technology and pedagogy.