GenAI Literacy Course Modules

Introduction

This Coursework and GenAI: A Practical Guide for Students open educational resource is intended to provide instructors with customizable content modules designed to enhance Generative AI literacy among students. The editable format supports flexible adaptation, ensuring that these modules can be integrated into existing courses across various disciplines.

Description of resources

Content structure: The content is divided into three sub-sections related to Generative AI literacy:

  • Understand how GenAI functions and its potential issues to consider.
  • Evaluate when to use GenAI and how to discern the quality of the content output.
  • Use practical strategies for using GenAI for various tasks in your academic work.

The content across these three dimensions of literacy can be utilized either collectively or individually based on course integration needs and preferences. Instructors can modify and integrate this content to fit the discipline context or align with planned course assignments. Please retain the creative commons licence information that is found on the Welcome page.

Content formats

  • Standalone: Coursework and GenAI: A Practical Guide for Students is available as a standalone resource in an open Quercus shell, available to any instructor or student. As there is no student course enrolment required for this version, student views and quiz participation cannot be tracked from this example.
  • Quercus modules: The material is designed for import into any course shell in the Quercus (Canvas) learning management system. Once uploaded to a course shell, instructors may edit as needed, adding additional content or removing components to suit the learning context. 
  • Other file formats: Content is provided for download in Microsoft PowerPoint and Microsoft Word formats to provide other options for instructors.

Integration suggestions

There are many approaches to integrating the content within your course.

  • Uploading the modules to your course shell will provide potential for closer integration with planned activities and option to customize content to the course and discipline context. Read how to import a Quercus (Canvas) course export package.  The export package is linked in the “Content Downloads” section below.
  • Including formative assessments or using material as scaffolding for graded assignments within Quercus can introduce the generative AI literacy material as core content in your course, directly linked to achievement of learning outcomes

Content Downloads

    • Choose this option if you would like to modify the content but are not intending to integrate with any grading components within your course.
    • Choose this option if you would like to modify the content and also have the final formative assessment for each module as a graded activity.
  • Microsoft PowerPoint
    • Choose this option if you would like to adapt the content for presentation in class, or a shorter version of the module content to share as an embedded or linked slide presentation in Quercus.
  • Microsoft Word
    • Choose this option if you would like to adapt the content to create materials unique to your discipline or course needs, including scaffolding for integration into GenAI literacy-related activities or assessments.

Additional resources for instructors

For additional guidance on instructional strategies see Centre for Teaching Support & Innovation web site resources at Teaching with Generative AI at U of T or contact your divisional teaching and learning centre.

GenAI Literacy Initiative

Read full details about the  GenAI Literacy OER Course Modules Initiative, including features, objectives and participants.

Acknowledgements

The GenAI Literacy Course Modules project was funded by the Office of the Vice-Provost, Innovations in Undergraduate Education.

The content has been developed by Digital Learning Innovation, Information Technology Services in consultation with the Centre for Teaching Support & Innovation, the University of Toronto Libraries and Student Life.

Our thanks to the faculty members and colleagues who contributed their time and insight to the development of this resource. For information on this GenAI literacy initiative strategy and implementation see the project background.

For questions or suggestions related to the content or accessibility of these modules contact digital.learning@utoronto.ca.

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