Selected in May 2026, these five Teaching and Learning AI Fellowship projects will explore innovative approaches to teaching and learning at Waterloo, with a shared focus on enhancing pedagogy, student engagement, and AI-enabled education.
Meet the 2026-2027 Teaching and Learning AI Fellowship Projects
This project will develop a domain-aware, multi-agent AI framework (utilizing specialized clarity, concision, and completeness agents) to provide student-facing, scalable, and formative oral communication feedback on video presentations.
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This project will develop an AI-enabled training tool that structures instructor expectations to build customized, course-specific onboarding modules, ensuring Teaching Assistants are fully prepared for highly specialized roles.
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This project will build a scalable, multi-stage diagnostic preparation platform that guides students through guided conceptual pre-lab interviews to identify knowledge gaps, optimize TA hours, and boost readiness for experiential learning.
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This project will design customizable, task-based conversational chatbots across French, German, and Spanish courses to offer scaffolded language practice, cultural awareness, and real-time formative interaction.
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This project will evaluate an instructor-trained "shadow grading" workflow using custom Copilot agents to generate parallel formative feedback and grades, seeking to reduce marking inconsistencies and accelerate turnaround times in large classes.
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