AI Learning Lab: Student-Driven Innovation for Neuroadaptive Learning Ecosystems
The AI Learning Lab will serve as the student-facing experimental hub for developing, testing and refining AI tools that support learning across the College. It is designed as a complement to the faculty-facing AI-Neuroinclusivity (AI-NI) framework, and it directly operationalizes the project’s goals by:
- Empowering students to actively shape AI-augmented learning practices
- Providing authentic data about how different AI tools support self-regulated learning
- Creating a pipeline where students co-design, test and evaluate AI-driven supports for large bottleneck/impactful courses
- Building a sustainable bottom-up culture of responsible AI use in engineering education
The Lab has two major student-led initiatives, each designed to generate best practices, training materials and course-embedded tools that scale across the curriculum.
Students as Participatory Action Researchers Exploring Learner Perspectives on AI
Purpose
Elicit and engage student voice as drivers of change within the College of Engineering related to student advancement through AI initiatives and strategies that support the full spectrum of neurodiverse learners in engineering programs.
Student Co-Design of a Custom AI Learner Support Tool
Purpose
To develop, refine and train a custom AI tool for CMP_SC 1050 (Algorithm Design and Programming I) or other selected course through iterative collaboration with students who are currently taking the course or have recently completed it.