Teaching and Learning AI Fellowships
Teaching and Learning AI Fellowships allow faculty members to develop and evaluate new AI applications that support teaching and student learning. Supported through Copilot 365 licenses, project funding, and dedicated support, the Fellows will have designed novel AI applications, piloted them in various learning environments, and evaluated their efficacy by the end of the winter 2027 term.
Five Fellowships were awarded. Summaries of their project outcomes and action ready resources will be added as projects are completed or reach major milestones.
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Fellows: Ada Hurst; Sharon Ferguson (Faculty of Engineering | Management Science and Engineering)
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Project: Develop a domain-aware, multi-agent AI framework that uses clarity, concision, and completeness agents to give students scalable formative feedback on video presentations
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Fellows: Brenda Lee (Faculty of Science | Physics and Astronomy); Joshua Crone (Faculty of Science); Collaborator: Mirko Vucicevich (Faculty of Science)
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Project: Build a scalable diagnostic preparation platform that guides students through conceptual pre-lab interviews, identifies knowledge gaps, supports teaching assistant planning, and strengthens readiness for experiential learning
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Fellow: Kanstantsin Tsedryk (Faculty of Arts | School of Critical and Creative Humanities); Collaborators: Annik Bilodeau (TSI); Emma Betz (Faculty of Arts); Mario Boido (Faculty of Arts); Grit Liebscher (Faculty of Arts); Mikalai Kliashchuk (Faculty of Arts); Rocky Penate (Faculty of Arts)
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Project: Design customizable, task-based chatbots for French, German, and Spanish courses that provide scaffolded language practice, support cultural awareness, and offer real-time formative interaction
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Fellows: Christine Barbeau (Faculty of Environment | School of Environment, Resources and Sustainability); Erin O’Connell (Faculty of Environment)
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Project: Evaluate an instructor-trained shadow grading workflow that uses custom Copilot agents to generate parallel formative feedback and grades, reduce marking inconsistencies, and improve turnaround times in large classes
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Fellows: Elena Neiterman (Faculty of Health | School of Public Health Sciences); Michelle Ogrodnik (Faculty of Health); Abel Espin Torres (Faculty of Health)
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Project: Develop an AI-enabled training tool that helps instructors capture expectations and build customized, course-specific onboarding modules for teaching assistants in specialized roles
Grant Opportunities
Explore University of Waterloo funding opportunities that can help you develop, test, and evaluate teaching and learning ideas at different scales.
LITE Seed Grants provide funding for smaller-scale teaching and learning projects, course-level innovation, and instructional development activities. With a LITE Seed Grant, you can:
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Assess new approaches to teaching and learning
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Examine student learning within existing instructional approaches
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Pursue instructional development opportunities
Amount: Up to $7,500
Timeline: Up to 18 months
Application Deadline: June 1 and October 1 annually. Consult the Learning Innovation and Teaching Enhancement Grants webpage for current submission dates
Teaching Innovation Incubator projects provide funding and support for institution-wide, cross-functional, and cross-faculty teaching and learning initiatives. With TII support, project teams can:
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Explore efficient and effective strategies for innovative teaching and learning
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Develop new approaches to teaching, assessment, and educational technology use
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Apply societal advances to improve Waterloo’s learning environment
Amount: Up to $20,000 for project-specific expenses
Additional Support: Project coordination support and access to Incubator resources
Timeline: Up to 24 months
Application Deadline: December 1 annually. Consult the Teaching Innovation Incubator webpage for current intake details.