Teaching and Learning AI Fellowship

About the Teaching and Learning AI Fellowship

To promote innovation in the use of GenAI for teaching and learning, the Office of the AVPA is holding a competition to identify Fellows across disciplines who can develop and evaluate new GenAI applications that support teaching. Funding and support will be available at two different levels, depending on the nature of the project.

  • Tier 1 awards: 5 awards in total 
    • Microsoft 365 Copilot license
    • Up to $20k in funding to support project work
    • Assigned co-op student(s) trained to provide project coordination, evaluation support, student feedback, and user testing
    • Project support, and supervision and mentoring for involved students, from ITSU’s Teaching Innovation & Educational Leadership staff
    • Project consultation with ITSU learning consultants
    • Participation in shared events and communities of practice
    • Project teams are expected to be both Architect and Ambassador: You’ll craft the innovation, test it, assess its effectiveness, and then share what has been learned, thus becoming its champion for UW instructors. This therefore makes Tier 1 projects an example of Educational Leadership as defined in University policy.

  • Tier 2 awards: 20 awards in total 

    • Microsoft 365 Copilot license

    • Access to co-op students for targeted feedback and/or testing
    • Project consultations with ITSU staff members as capacity allows
    • Participation in shared events and communities of practice

Note: both project levels will receive support for meeting the knowledge mobilization dissemination expectations that come with the award.  

Responsible GenAI use is required. 

All supported projects must demonstrate awareness of academic integrity, transparency, copyright, and alignment with institutional GenAI use guidance. 

Applying for a Tier 1 AI Fellowship: What you need to know

Tier 1: Applicant Eligibility
  • Tier 1 Teaching and Learning AI Fellowships are reserved solely for University of Waterloo faculty members. 

Tier 1: Selection Criteria

Tier 1 Fellowships must address all the following selection criteria: 

  • Clear teaching and learning application.

  • Identification of learning modality (i.e., large class, active learning, fully online, laboratory, experiential learning).

  • Scope of GenAI innovation, appropriate for the “curious middle” rather than advanced technical experimentation.

  • Demonstrated capability to engage thoughtfully with GenAI, either through the applicant’s own experience or through consultation/partnership with expert staff/faculty.

  • Transferability beyond single course or disciplinary context.

  • Feasible implementation plan.

  • Identified dissemination strategy to share insights (to be supported by integrated teaching support unit staff).

  • Detailed budget with reasonable use of funds.

Note: To reflect the breadth of teaching traditions and learning modalities at Waterloo, selections aim to span multiple contexts, such as: large classes, active learning, fully online instruction, laboratories, and experiential learning. 

Tier 1: How to apply

Complete the Tier 1 Fellowship application and submit the application through the application webform. Your application will address the following: 

  • A clear teaching and learning application.
  • Learning modality identified (e.g., large class, active learning, fully online, laboratory, experiential learning).
  • Scope of GenAI innovation.
  • Capability to engage thoughtfully with GenAI (through experience and/or consultation/partnership with expert staff/faculty).
  • Transferability beyond a single course/discipline.
  • A feasible implementation plan.
  • A dissemination strategy to share insights (supported by integrated teaching support unit staff).
  • A detailed budget.

Note: Tier 1 Fellowship applications can be downloaded as a word document for drafting purposes however all finalized applications must be submitted through the application webform here. 

Applying for a Tier 2 AI Fellowship: What you need to know

Tier 2: Applicant Eligibility
  • Tier 2 Teaching and Learning AI Fellowships are reserved solely for University of Waterloo faculty members.

Tier 2: Selection Criteria

Tier 2 Fellowships must address all the following selection criteria:

  • Pedagogical alignment and rationale

    • Clear description of pedagogical use case and relevance to identified disciplinary/ASU context. 

    • Relevant learning outcomes. 

  • Appropriateness of GenAI integration

    • Thoughtful integration of Copilot in indicated teaching or learning context.

    • Evidence that GenAI usage will enhance/support learning goals.

  • Anticipated student impact

    • Reasonable and realistic projections of student engagement and/or downstream impact on student learning. 

    • Meaningful interaction with Copilot.

  • Ethical use of GenAI

    • Indication that use of GenAI is done with awareness of academic integrity, transparency, copyright.

    • Alignment with institutional GenAI use and guidelines.

Note: To reflect the breadth of teaching traditions and learning modalities at Waterloo, projects should aim to span multiple contexts, such as: large classes, active learning, fully online instruction, laboratories, and experiential learning. 

Tier 2: How to apply

Complete the Tier 2 Fellowship application and submit your application through the application webform. Your application will address the following:

  • Project identification; instructor/department; course name/code (or ASU context). 

  • Learning modality (e.g., large class, active learning, fully online, laboratory, experiential learning). 

  • Description of the pedagogical use case and how Copilot will be used (e.g., teaching, assessment, assignment feedback, grading support, content creation, student use). 

  • Expected learning outcomes; projected student impact; number of students impacted.

  • Modality of engagement (e.g., lecture, lab, tutorial, online learning environment). 

Note: Tier 2 Fellowship applications can be downloaded as a word document for drafting purposes. However, all finalized applications must be submitted through the application webform here.