This project will reimagine engineering education by creating innovative tools and strategies that support the success of all students, particularly in the critical first two years of the undergraduate experience. Grounded in the concept of neurodiversity as the natural variation in how individuals think, learn, and process information, the project embraces the idea that every student brings a unique cognitive profile to the classroom. The project will use artificial intelligence (AI) to build learning environments that flex to meet a wide range of student strengths, needs, and preferences. Through redesigned courses, professional development for faculty, and AI-powered tutoring and academic coaching, the project will help students develop essential academic behaviors such as time management, self-regulation, and metacognitive awareness. The interventions will be designed to be accessible to all students and will be embedded in existing instructional and advising structures. By improving student engagement and persistence in engineering pathways, this work will contribute to a more diverse, capable, and innovative engineering workforce. It will advance the national interest by expanding access to high-quality STEM education and supporting a broader spectrum of learners whose talents may not be fully realized in traditional academic settings.

This project will implement a coordinated institutional change strategy at the University of Missouri and the University of Connecticut, focused on transforming gateway courses in engineering and mathematics using universal design for learning principles and inclusive pedagogy. Faculty will participate in a structured professional development sequence that includes the Neuroinclusive Teaching Institute and interdisciplinary I-teams to support course redesign and the integration of AI-powered tools. A virtual academic coach, built on large language models, will be deployed in tutoring, peer mentoring, and advising contexts to guide students through personalized learning strategies outside the classroom. All tools and redesigned instructional practices will be made openly available to all students. The project will advance fundamental knowledge in two distinct areas: first, in engineering education, it will examine how the deployment of AI tools in instructional and support environments affects engagement, self-regulated learning, and engineering identity formation across cognitively diverse learners. Second, it will provide insight into the policies and institutional practices that promote a culture that values the strengths of all students. Based on prior experience, these cultural shifts are essential for both the transformation and long-term sustainability of educational change. In addition to advancing research, the project will generate actionable tools and structures to support adoption of AI-enhanced, neuroadaptive practices across institutions. These will include a faculty teaching workshop with adaptable materials for engineering and math courses; AI-coaching tools with companion training for advisors and peer mentors; and a roadmap for onboarding faculty into neuroadaptive, technology-enabled teaching models. Research activities will assess how these innovations influence students, faculty, and departments, contributing new knowledge to the national conversation about AI in education and the professional formation of engineers. Together, these efforts will create a replicable model for building more responsive learning environments in undergraduate engineering education.