Gen AI Literacy Course Modules

Image of a computer with books in front of it.The Gen AI Literacy OER Course Modules initiative, funded by the Vice-Provost Innovations in Undergraduate Education (VPIUE), aims to provide instructors with customizable content modules designed to enhance Generative AI literacy among students. A key feature of this initiative is designing for adaptability, ensuring that these modules can be integrated into existing courses across various disciplines. 

Key features of the initiative include: 

  • Alignment: Aligned with institutional principles and recommendations developed by the University of Toronto AI Task Force as well as ongoing liaison with key stakeholders including Student Life (SL), Centre for Teaching Support & Innovation (CTSI) and the University of Toronto Library.
  • Adaptability: Modules can be customized to fit a range of course requirements and learning outcomes. Content will be available as Open Educational Resources in varied formats, potentially including web URL, PPT, and Quercus modules. 
  • Agility: Stakeholder consultation, design and development phases through to release of first draft will be on a quick development timeline for first iteration. 

Other program objectives: 

  • Inclusion of an instructor guide on suggested uses and integration options.  
  • Aiming for general concepts and “futureproof” content, using high level material that can be adapted or integrated as supplementary material or scaffolding to course specific activities and assessments.  
  • Avoid duplication by linking to existing VPIUE, SL, CTSI and library guidance where possible.
  • Formation of an additional faculty reference group for those with interest in providing feedback or taking up early adoption.
  • Consultation with students via VPIUE Gen AI Student Advisory group.

Implementation plan: 

  • Phase 1: Needs assessment and stakeholder consultation. 
  • Phase 2: Content development, instructor user feedback.
  • Phase 3: Launch via Open UToronto web site for pilot testing.
  • Ongoing: Future updates and improvement based on feedback.

The pilot cohort includes: 

  • Ariel Chan, Dept. of Chemical Engineering and Applied Chemistry, FASE 
  • Aarthi Ashok, Dept. of Biological Sciences, UTSC
  • Melody Neumann, Dept. of Cell & Systems Biology, FAS 
  • Maria Assif, Dept. of English, UTSC 

DLI project team: 

  • Laurie Harrison, Director, Digital Learning Innovation
  • Will Heikoop. Coordinator, Digital Learning Innovation
  • Alex Olson, Senior Research Associate, Centre for Analytics and AI Engineering (CARTE)

Reference Group

We also welcome faculty who have agreed to share their input and advice through inclusion in a reference group for the pilot, providing feedback on the module content and receiving early access to the materials for use in summer/fall 2025 courses. Reference group members include:

  • Susan Bondy, Dalla Lana School of Public Health
  • Paul Gries, Dept. of Computer Science, FAS
  • Kimberley MacKinnon, Department of Curriculum, Teaching and Learning, OISE
  • Michael Reid, Astrophysics
  • Sharon Switzer-McIntyre, Dept. of Physical Therapy, TFM
  • Daphne Tan, Music

Watch this space for updates on the initiative’s progress.  

Contact digital.learning@utoronto.ca for more information.