You may consider making slight changes to clarify and foreground what distinctive human skills you are assessing, as shown in the following examples of analysis-level learning outcomes: 

In comparing both learning outcomes, the differences can be subtle, but powerful. For example, in the “Statistics” example above, there is a distinct call out that students will draw meaningful conclusions from data. In doing this, the instructor foregrounds the distinctive human skills that students will develop, regardless of whether they will engage generative AI tools in assessments.

Including learning outcomes that encourage AI literacy

Given that generative AI is an emerging tool, developing AI literacy may be meaningful for students, and an important part of their future skillset and entry into the workforce. By incorporating space for AI literacy skill development, students may be better able to use and critically reflect on generative AI technologies, even if they may not be able to develop AI models themselves (Laupichler et al., 2023: 2). In order to incorporate AI literacy into the course, consider following Universal Design for Learning (UDL) principles by explicitly clarifying how course-level learning outcomes relate to the topic. This approach will help students generate meaning around the course, thereby developing their effort and persistence. 

Rather than approach AI literacy as something that one either has or lacks, it can be helpful to consider how it relates to different categories of skills. Following Bloom’s Taxonomy, AI competencies can be categorized into four cognition domains, organized from lower to higher order thinking skills. As an instructor, you may consider starting small, asking what discreet AI skills you could meaningfully integrate into the course in the form of a learning outcome, in alignment with the other course-level learning outcomes (Almatrafi et al., 2024): 

• Know & understand: Ability to explain the basic functions of AI and how to use AI applications. 
• Use & apply: Ability to use and adapt AI tools to achieve an objective.  
• Evaluate & create: Ability to analyze the outcomes of AI applications critically. 
• Navigate ethically: Ability to understand and judge ethical issues related to generative AI, such as privacy, bias, misinformation, and ethical decision-making. 

2. Design or revise your assessments

Once you have revisited your course-level learning outcomes, the next step would be to design or revise your assessments, in alignment with the learning outcomes. In designing your assessments, you may wish to discourage or encourage generative AI, depending on whether you find that students’ use of generative AI tools would disrupt or support their achievement of the course-level learning outcomes. 

If you plan to discourage generative AI use, you may want to:

• Require citations and check for accuracy. Requiring specific citations and page numbers may discourage students from relying on generative AI.  
• Focus assessment materials and prompts on topics local to the course. This approach can help to promote student engagement, and in addition it would be more difficult to generate a relevant answer using generative AI. Also make clear that tests and exams will require mastery of work completed for assignments.  
• Add drafts or revise-and-resubmit components to assessments. By scaffolding assessments with iterative feedback, students will be encouraged to revise assignments in direct relation to peer or instructor feedback.  

If you plan to encourage generative AI use, you may want to:

• Authorize students to use generative AI as an educational tool in specific, constructive ways. Consider allowing students to use AI tools as a study aid and reviewer, to debug code and explain errors, to brainstorm ideas and arguments, or to edit writing.  
• Include written reflections on how students’ used or engaged with the tool in assessments. For instance, you may ask “What was your purpose in using GenAI to complete this assignment?” (Dobrin 2023) and incorporate an evaluation of that reflection into the final grade. 
• Incorporate citations when GenAI is used. Consider asking students to cite generative AI tools when used, which could include the AI prompt used. You may consider sharing the University of Toronto Libraries resource, “Citing Artificial Intelligence (AI) Generative Tools (including ChatGPT).”

Examples of using generative AI as an educational tool in assessments:

• Critique and improve AI-generated outputs. Consider asking students to critically analyze, fact-check, and evaluate outputs generated by AI tools, including texts, equations, or code. You may provide a prompt and the output text, or you could show students how to prompt the tool to generate a response.  Individually or with peers, students can then assess and improve the response for accuracy, depth, and nuance. For example, you may ask students to answer: What important knowledge did they learn from the class that the AI missed?; What is a more nuanced or correct answer or explanation, compared to the GenAI output?; What aspects of the writing are compelling, misleading, or redundant?
• AI-assisted problem-solving. For problem-based assessments, you may consider asking students to leverage generative AI tools to generate potential solutions, brainstorm ideas, and receive clarification. You may wish to invite students to use generative AI to write or expand on code or synthesize data sets. From there, you could prompt students to demonstrate their own understanding by evaluating and refining AI-generated content. 
• AI-assisted writing. For writing assignments, you may consider allowing students to use generative AI tools to help with ideation, outlining, or drafting. However, you may devote a portion of the evaluation to having them substantially revise and refine the AI-generated content, to reflect their critical thinking and writing skills.
• Adding creative elements to assignments. You may consider inviting students to use generative AI tools to add more creative elements to their work, such as using generators for images that they add to slide presentations, or to include infographics. Students could also use AI text generators to create draft scripts for videos in which they demonstrate key learning outcomes. Harnessing generative AI in this way can provide opportunities for students to demonstrate their learning in different modalities. 

Revising assessments to reduce learning barriers

Regardless of whether you choose to allow the use of generative AI in assessments, you may consider using Universal Design for Learning (UDL) principles to proactively enhance access and build student agency in their learning. This does not eliminate the need for specific academic accommodations for students with disabilities. Rather, this closes the gap between student needs and instructional design, and offers a ramp to better facilitate academic accommodations for students with disabilities. When designing or revising your assessments with generative AI in mind, consider engaging in one or more of the following UDL strategies to reduce learning barriers:  

• Design options for various forms of assessments with generative AI. Given that there is no one means of action and expression that is optimal for all learners, you may wish to provide space for assessment choice, including those that involve generative AI-usage and those that do on. For instance, students may be able to show what they know through written submissions or visual representations, while engaging with pertinent tools.  
• Scaffold assignments so that students are working towards a final product for submission. Whether or not generative AI is part of the assessment, this effective approach benefits the students’ writing and learning and also creates authentic conditions that are more likely to deter unauthorized use of generative AI.  
• Align with real-world tasks. Encourage students to demonstrate their knowledge and skills in a way that is significant, meaningful, and aligned with real-world tasks. Ask real questions that stem from current debates in your discipline, and let students know that you expect engaged critical thinking that is appropriate for the level of your students and your discipline. Encourage speculation based on evidence and reasoning, not just compilation of existing information or expression of unsupported personal opinion.  
• Be Explicit about Expectations. Clarify and decode instructions and expectations by providing clear cues and prompts. You may provide rubrics and grading criteria to ensure students know what is expected of them in the assessment, and whether and when generative AI tools can be used. This may also reduce inappropriate or misguided peer-peer communication. See the “week to week” section for further examples on ways to provide clarity and purpose to students about assessments as they are introduced. 

3. Develop a communication plan with students and teaching assistants

Once you have decided on your course-level learning outcomes and assessments, you can determine your course policies and plan how you will communicate them. Your students will have varying levels of knowledge of generative AI, and many will look to you for guidance on what they are and are not allowed to do and how these tools will impact their learning.  

The University of Toronto has created sample statements to include in course syllabi and course assignments to help inform students what AI technology is, or is not, allowed in the course. Visit resource on Generative Artificial Intelligence in the Classroom: FAQs to access the most updated sample statements. In addition to providing an explicit course policy statement on generative AI for your syllabus, you may want to intentionally plan how you will share these expectations to students in class and on Quercus. Consider one or more of the following strategies:  

• Engage students in discussion about the policy discussions, to explain the rationale and how it relates to course-level learning outcomes. 
• Identify best practices for how to use and cite the use of generative AI tools, if they are permitted. 
• Identify relevant campus resources for students to support their learning skills development while using generative AI, thereby encouraging academic integrity. Potential student-facing resources that you may add your syllabus include: 
  • UTSG: Through the Centre for Learning Strategy Support (CLSS), students may book a learning strategy appointment or attend a workshop on effectively preparing for assessments and exams. Through the Writing Centre, students may book one-on-one consultations for developing their writing skills. 
  • UTM: Through the Student Resource Hub at the Robert Gillespie Academic Skills Centre, students may book a learning strategy or writing support appointment.
  • UTSC: Through the Centre for Teaching and Learning, students may book a writing support appointment. Through the Academic Advising and Career Centre, students may book a study-skills peer coaching appointment or attend a related workshop.
• Develop a plan for how you will communicate to your course teaching assistants their roles and responsibilities: How will they evaluate assessments and communicate course policies regarding generative AI use?