Skip to McMaster Navigation Skip to Site Navigation Skip to main content
McMaster logo

Office of the Provost & Vice-President (Academic)

Academic Excellence

Task Force on Generative AI Terms of Reference

Task Force on Generative AI Use in Teaching and Learning Terms of Reference

Scope and Outcomes

I. Purpose

The purpose of this task force is to investigate the impacts posed by generative AI on teaching and learning at McMaster University, and to provide strategic guidance and actionable recommendations for educators planning for fall courses.

II. Background

Generative AI, exemplified by models such as ChatGPT, Bing and Bard, is reshaping the landscape of education, bringing forth both opportunities and challenges. As a research-intensive university, it is imperative that we adapt to these developments and ensure that our pedagogical approaches and academic integrity standards remain robust, relevant, and effective.

III. Objectives

The task force will pursue the following objectives:

  • Review the current state of generative AI technology and its implications for higher education, with a focus on potential benefits and challenges for the McMaster context
  • Discuss risks to academic integrity that may arise from the use of generative AI and recommend proactive teaching strategies to mitigate these risks and communicate these with the community
  • Draft and endorse guidelines, resources and training for educators enabling them to make informed decisions in their teaching strategies, including if/when/how to use generative AI in teaching practices (e.g. designing assignments, grading/feedback)
  • Draft and endorse resources for students to familiarize them with generative AI tools to build both digital literacy skills and confidence in appropriate use of generative AI for learning.
  • Comment on drafted recommendations to share with the Senate Committee on Academic Integrity for consideration on the responsible adoption of generative AI in teaching and learning.

While the Task force may discuss intersections with generative AI and research, service and staff activities at the University, its mandate is to address the impact of generative AI on teaching and learning, with a focus on student learning. Recommendations pertaining to research, staff work, or service work fall outside the scope of this task force.

IV. Membership

The task force will be co-chaired by the Vice-Provost, Teaching and Learning and Deputy Provost, with coordination provided by the MacPherson Institute. The task force will consist of members with expertise in the following areas:

  • Faculty representatives from diverse disciplines
  • Representatives from University Technology Services
  • Educational developers
  • AI and machine learning researchers
  • Librarians and information specialists
  • Student Affairs representatives
  • Student representatives
  • Privacy and academic integrity experts

V. Timeline

The task force will convene in May 2023 and aim to submit a final report with recommendations by August 2023. Updates will be shared with the Provost’s office and relevant stakeholders periodically throughout the process.

VI. Reporting

The task force will report directly to the Vice-Provost, Teaching and Learning and the Deputy Provost and will provide monthly updates to the Senate Committee on Academic Integrity through a summary report and the Academic Integrity Officer.

VIII. Support

The Generative AI Task Force in Teaching and Learning will be supported by MacPherson Institute staff that will:

  • Schedule and coordinate logistics of task force meetings and events
  • Circulate an agenda and documentation prior to each meeting
  • Prepare and distribute minutes after the completion of each meeting
  • Support the writing of the Task force recommendations

VIII. Review

The task force’s recommendations will be submitted by September 10th and will be reviewed and assessed for implementation by the Vice-President, Academic in consultation with relevant stakeholders across the university.  The task force may be reconvened to address any subsequent developments in generative AI that warrant further examination or action.

Proposed Meeting Topics, Dates and Prework

  1. Current State of AI in Teaching and Learning: May 16, 3:10-4:30
    1. Briefing package prepared and distributed a week in advance
    2. Outcome: Describe perceived benefits and challenges in McMaster context from both student and faculty perspectives
  1. Academic Integrity and AI: June 26, 3:10-4:30
    1. Briefing package prepared and distributed a week in advance
    2. Outcome: Recommend proactive mitigation and communication strategies for educators to foster academic integrity at McMaster, including teaching practice and student approaches.
  1. Policy Considerations for AI: July 18, 3:10-4:30
    1. Draft of considerations for policies distributed a week in advance
    2. Outcome: Feedback (and endorsement) of considerations for policies to be submitted to the Senate Committee on Academic Integrity for consideration
  1. Student and Faculty Guidelines and Training in AI: August 29, 3:10-4:30
    1. Drafted Pressbook “AI in Teaching and Learning at McMaster University” and training options distributed a week in advance
    2. Drafted resource “AI in Learning at McMaster University” and conversation guides distributed a week in advance
    3. Outcome: Feedback (and endorsement) of drafted AI resources and training supports for faculty and students