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Overview and General Guidance

Note: Please check back regularly for updates or reach out to us directly at teachinglearning.artsci@utoronto.ca.

Crafting assessments with generative AI in mind can provide an opportunity to modify and clarify your learning outcomes and identify how these are measured in each assessment. Evaluating or reevaluating how learning outcomes are assessed will help you to communicate the reason and rationale behind your assessments to students. This will help them to better understand the steps in the learning process and the value of each assessment. Remember, if you do not specify that it is allowed, generative AI is considered an unauthorized aid under the University’s Code of Behavior on Academic Matters.

When determining your approach to generative AI in the classroom, reach out to your undergraduate Associate Chair or Director to understand the department's stance on generative AI tools and to discuss methods of using or prohibiting such tools in your specific discipline.

Please note: An enterprise version of Microsoft Copilot is now available to all instructors, librarians, staff, and students at the University of Toronto. When signed in using your UTORid (a green “protected” badge will show), the enterprise edition conforms to the University’s privacy and data protections. Copilot is free to use, and provides ChatGPT access, document analysis, and Dall-E image generation. Microsoft Edge browser is recommended to access extended functionality. Additional resources from the Centre for Teaching Support & Innovation that may be helpful: Generative AI Tools; Generative AI in the Classroom; and Microsoft Copilot.

Engage with your Students

Whether you choose to permit or prohibit the use of generative AI tools in your course assessments, fostering communication with your students about emerging technologies is crucial. Ideally, your syllabus should outline your course policies on generative AI and each assessment may have a supplemental statement that further clarifies if students are allowed to use an AI tool and in what capacity.

Engaging your students in meaningful conversations about the role of generative AI in their learning will help you to understand student viewpoints and motivations, and to communicate your own expectations about the use of these tools. Below are some strategies you might consider:

Outline the assignment rationale and procedures

- Communicate the value of the assessments and what students can gain from completing them.
- Review assignment instructions in class and provide an opportunity for questions. Engage students in a conversation about why you chose to permit or prohibit the use of generative AI, and how generative AI may or may not help them with an assignment or activity.
- Include an integrity statement that students must complete upon turning in the assignment.
Promote discussion and engagement through:
- Community/Course Agreements. Ask students to work collaboratively to reach consensus about generative AI use in the course and/or assignments.
- Debates. Arrange a classroom debate about generative AI as it relates to your course topics and/or themes.
- Discussion and Reflection. Incorporate student-to-student and instructor-student discussions about AI into class time. Activities like low-stakes writing, reflective writing, think-pair-share, and jigsaws can be effective ways of generating and recording ideas. Example discussion questions are below.

Discussion Questions

Have you used generative AI? What for? What is your familiarity level with these tools?
In your own words, describe what generative AI does (or, how it works for you).
What do you feel generative AI has helped you to accomplish?
What is an example of when you were impressed with output from generative AI?
What is an example of when you were disappointed with generative AI?
Why should we use generative AI for [X course / Y learning outcome]?
Why shouldn’t we use generative AI for [X course / Y learning outcome]?

Assessment Ideas that Prohibit the Use of Generative AI

Below are strategies for assessments and activities if you want to prohibit or mitigate the use of generative AI tools in your classroom. The list is by no means exhaustive; please consult References and Additional Resources below, and check this page regularly for updates.

Prohibit Generative AI: Assessment and Activity Ideas
Strategies	Notes
Add in-class activities, assessments, and tests including in-person final exams	Requiring pen-and-paper answers means that students should not be able to access generative AI tools or other prohibited resources. Keep in mind that students could use generative AI to review for these assessments. While this may not be permitted, it is more difficult to enforce. Talk to students about the advantages and limitations, such as why reviewing using generative AI may lead them down the wrong path for the assessment. Why is it important, in other words, to consult lecture notes and academic sources while studying? If you assess in-class participation and engagement, consider re-weighting this assessment to put more emphasis on in-class and real-time activities.
Require citations and check for accuracy	Some AI tools are not able to reliably provide correct sources and citations. For example, the cited author may be correct, but the tool might fabricate the source and pagination. You may find using modified citations helpful, such as requiring students to include page numbers or other information not typically needed for certain citation formats, like APA.
Focus assessment materials and prompts on topics local to the course	Asking students to engage directly with lectures, tutorial or lab sessions, and classroom discussions can help to promote student engagement with the course material and make it more difficult to generate a genuine answer using generative AI. Examples might include: Close analysis of a passage, article, film, or art piece. Personal reflection on a research method studied in the course. Student responses to a current event or new academic article.
Incorporate assessments that specify the use of particular research tools or methods	This might include statistical software for data analysis and modeling, geographic information systems for mapping and spatial analysis, Endnote or Zotero for reference management, or GitHub for coding projects. Using specific tools or methods may limit how helpful generative AI can be.
Incorporate low-stakes problem sets or writing activities.	Students can complete these activities during lectures, tutorials, or at home. Low stakes activities that are not graded or have low weight may disincentivize or prohibit use of generative AI. Examples might include: “Ticket out the door”: What is one question or thought you had during today’s lecture? Write this on a notecard or scrap of paper (best if provided). Quercus discussion board posts (e.g., One thing you noticed from this week’s reading, one thing you struggled with. A “bad thesis” or wrong answer, to collectively correct or improve on during class.
Add drafts or revise-and-resubmit components to assessments	This helps to encourage students to engage with and directly refer to peer or instructor feedback, and close-reading of their own work.
Provide students with an optional assessment format or a self-designed prompt	This allows students to explore and connect their own interests to the course material. For example: Offer an alternative to a final paper such as a podcast or 5-minute video that is accompanied by a shorter research statement. Ensure you have an outline for how to grade the alternative medium and outline expectations for length, editing, and polish. Allow students to design their own final prompt, connecting course topics to their areas of interest. This could even result in an academic publication, if students are interested. Let students vote on a detail or section of a take home assessment, providing a more collaborative process.
Incorporate experiential and community-engaged learning opportunities	Experiential and community-engaged learning opportunities might include formal and informal community partnerships, real-world applications of your discipline, field trips to an art museum or local educational centre, or interviews with field experts.

Assessment Ideas that Allow the Use of Generative AI

Below are strategies for assessments and activities if you want to allow the use of generative AI tools in your classroom. The list is by no means exhaustive; please consult References and Additional Resources below, and check this page regularly for updates.

For certain assignments, you may want to allow the use of generative AI, but not make it the central attraction or learning goal of the assignment. In these cases, you may allow use of generative AI as an authorized aid.

Reminder: exercise caution when using third-party tools that have not been vetted by the University for privacy or security. There are also concerns about equity and access. Tools like ChatGPT are popular and heavy traffic may prevent users from reliably accessing the tool to work on or complete assignments.

Allow Generative AI: Assessment and Activity Ideas
Strategies	Notes
Authorize students to use generative AI as a reviewer and study aid.	For example, to: Check grammar, syntax, and tone. Consider talking to your students about what writing style and language is appropriate for and expected in your discipline. Debug code. Generative AI can help debug code by analyzing the provided code, identifying potential errors or issues, and suggesting possible solutions or areas to investigate based on its training data and programming knowledge. Brainstorm research topic ideas and help to outline and organize an essay, lab report, or other written assignment. Strengthen arguments using generative AI as a “Socratic opponent” (Sabzalieva and Valentini, 2023, p. 8), which asks students to play “devil’s advocate” with their thesis or ideas on a topic.
Ask students to include written reflections on how they used or engaged with the tool	For example, to: To generate an essay outline, draft a thesis statement, and so on. Dobrin (2023) includes a number of helpful prompts for student reflection, including: “What was your purpose in using GenAI to complete this assignment?” “Does using GenAI limit how you would otherwise respond to this assignment?”
Incorporate citations.	Ask students to cite generative AI tools when used, which could include the AI prompt used. Ask students to add research, evidence, and citations to an AI-generated answer.

Assessment Ideas that Invite the Use of Generative AI

It may be beneficial for students to undertake an assessment that deliberately, and in detail, engages with generative AI. These assessments may also include a reflection piece on what it was like to work with the tool and what students learned by using it. The list is by no means exhaustive; please consult References and Additional Resources below, and check this page regularly for updates.

Invite Generative AI: Assessment and Activity Ideas
Strategies	Notes
Use generative AI to synthesize data sets	Generative AI can help with data analytics by providing insights and generating reports based on the data you provide, helping you understand trends, patterns, and make informed decisions. Always be careful when providing data to generative AI tools, and ensure you protect the privacy and security of your data. Consider using data models rather than data sets.
Use generative AI to write or expand on code	Generative AI can write, check, and improve code.
Use generative AI to review iterations of their work	Ask students to consider 3 iterations of their work when using prompts. How does each iteration differ from the next, and what prompts did they use to produce the differences?
Help students develop their critical readings, reflection, and fact-checking skills.	Provide students with a prompt (or ask them to draft their own) related to the course material, then ask them to generate a generative AI response to that prompt. Individually or with peers, students can assess the response for accuracy, depth, and nuance. Additional components of the assignment may involve: students writing a reflection on what the tool got right and wrong. students revising the AI-generated answer with correct information, more nuanced explanations, and deeper analysis. Have students write a guide to studying for or researching your course topic with the assistance of generative AI tools.
Ask students to create, review, and revise prompts for generative AI and reflect on the failure or success of those prompts.	What do students learn from crafting responses to feed to generative AI tools? Where did they have to specify or broaden their information? Where did they, or the tools, go wrong? Have students provide drafts of their conversations with generative AI tools like ChatGPT.

References and Additional Resources

Books, Blogs, and Articles

Artificial Intelligence: Where Are We Now? (June 1, 2022). Educase Review Special Report.

Dobrin, S. (2023). Talking about Generative AI: A Guide for Educators. Broadview Press.

Dobrin, S. (2023). AI and Writing. Broadview Press.

Gimpel, H., Ruiner, C., et al. (2023). Unlocking the power of generative AI models and systems such as GPT-4 and ChatGPT for higher education: A guide for students and lecturers. Honenheim Discussion Papers in Business, Economics, and Social Sciences, 2-2023.

Mollick, E & Mollick, L. (2023, June 12). Assigning AI: Seven Ways of Using AI in Class, with Prompts. SSRN.

Qadir, J. (2022). Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education. TechRxiv.

Sabzalieva, E. and Valentini, A. (2023). ChatGPT and Artificial Intelligence in higher education: Quick Start Guide. UNESCO International Institute for Higher Education in Latin America and the Caribbean (IESALC).

Suggestions for assignment and assessment design. (n.d.). University of British Columbia, Centre for Teaching, Learning and Technology.

Annotated Resources on Generative AI. (2023, August 1). University of Guelph, Office of Teaching and Learning.

Workshops and Presentations

Boyes, D., Gustafson, A., Ju, W., Sanders, N., Steipe, B., Suarez, D., Sullivan, & L. Zweig, D. (2023, March 2). University of Toronto, Department of Linguistics Pedagogy Workshop: AI-Generated Text and Teaching in Linguistics [Video]. YouTube. (1:28:40).

Gibbs, A., Williams, A., & McCahan, S. (2023, February 28). Designing Assessments in the Age of Artificial Intelligence [Video]. University of Toronto, Centre for Teaching Support and Innovation. (1:54:09). Presentation slides located on SharePoint. Video requires access through Teams; please contact ctsi.teaching@utoronto.ca for access.

Lametti, D. (2023, January 31). AI and Academia: The End of the Essay? [Video]. Maple League of Universities. Youtube. (1:02:29). Slides can be accessed on Dropbox.

McCahan, S. (2023, February 18). Generative Artificial Intelligence in Teaching and Learning [Video]. University of Toronto. MyMedia. (18:12). UTORid login required.

Suarez, D. & Gustafson, A. (2022, November 1). Teaching Writing in the Age of Mechanical Content Production [Video]. Arts & Science Teaching & Learning Community of Practice, University of Toronto. MyMedia. (37:25). UTORid login required.

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