Exploring the Potential for Teaching

This is an evolving resource that is intended to support educators in developing their knowledge of GenAI tools (opportunities and limitations), so that they can make informed decisions about its use or impact in their courses. With this knowledge, educators are invited to be transparent with students about their decisions and explanations for the approach to learning in their courses with the emergence of GenAI tools.

Generative AI’s emergence has quickly introduced a vast array of dedicated AI tools as well as being rapidly integrated into everyday tools used by students, instructors and employers. Re-designing course assessments to address this reality – whether to incorporate or mitigate student use – often requires significant time, thoughtful consideration, and careful planning. Laurier’s Teaching Excellence and Innovation team recognizes the diverse teaching contexts across disciplines at our institution. We offer both individual and program-level support to help you find sustainable solutions for assessment redesign that align with class size, curriculum, and grading capacity.

We recognize that faculty have diverse approaches and perspectives to technology integration and we work alongside instructors to understand and navigate generative AI’s challenges and opportunities for teaching and learning. Our generative AI resources provide assessment design consideration, suggestions for how and when to incorporate AI tools strategically within your courses, as well as strategies to mitigate unauthorized AI use. A few considerations to support your assessment design decisions:

1. Familiarizing yourself with generative AI through experimentation can provide valuable insights into its capabilities and limitations. Exploration of the risks, opportunities and challenges posed by AI tools helps instructors make informed decisions about how AI might impact their assessment design. From running assessment questions through an AI, to designing assessments that incorporate generative AI outputs for students to critique, or generating images or content as course material, testing AI can provide insights and ideas for redeveloping your assessments to align with your course expectations regarding AI use. It’s important to be aware that as AI tools proliferate, changes to terms of use may occur at any time and some may require payment for use.

2. Openly communicate with students. Discussing AI use with your students at the outset sets clear expectations and boundaries. Clarify how AI can and cannot be used in your specific course, ensuring alignment with course objectives, student learning outcomes, activities, and assessments. Explore sample course syllabi statements that define acceptable use of AI in courses. As course requirements vary from instructor to instructor and student experiences differ across courses, transparency regarding authorized AI use fosters an open and responsible learning environment.

3. As with all academic work, helping students to uphold academic integrity is paramount. Any use of AI requires that both students and instructors accurately acknowledge AI sources or tools consulted. This includes proper citation of AI-generated sources, whether they be images, examples, or even drafts, outlines, or ideas derived from AI tools. The Laurier Library has created a guide to citing generative AI.

The AI Assessment Scale (AIAS) as a Guide

The AI Assessment Scale (AIAS) is a framework that can be used to guide assessment design decisions on when, where, and why to use AI tools. Understanding where and why your assessment sits within the five levels of the AIAS scale (see below) can support productive discussions with students regarding ethical and appropriate AI use in their course work.

In using this scale, consider how to help students understand both the opportunities and limitations of GenAI tools and their impact on the learning process for your assessments. What do students need to know to make informed decisions about GenAI use in your assessments? Mapping assessments onto the assessment scale and engaging in ongoing dialogue with students on course AI-use policies can help promote a culture of shared expectations and understanding regarding GenAI use.

The AI Assessment Scale

• Level 1: No AI - The assessment is completed entirely without AI assistance in a controlled environment, ensuring that students rely solely on their existing knowledge, understanding, and skills.

  • Example: “You must not use AI at any point during the assessment. You must demonstrate your core skills and knowledge.”

• Level 2: AI Planning - AI may be used for pre-task activities such as brainstorming, outlining and initial research. This level focuses on the effective use of AI for planning, synthesis, and ideation, but assessments should emphasise the ability to develop and refine these ideas independently.

  • Example: “You may use AI for planning, idea development, and research. Your final submission should show how you have developed and refined these ideas.”

• Level 3: AI Collaboration - AI may be used to help complete the task, including idea generation, drafting, feedback, and refinement. Students should critically evaluate and modify the AI suggested outputs, demonstrating their understanding.

  • Example “You may use AI to assist with specific tasks such as drafting text, refining and evaluating your work. You must critically evaluate and modify any AI-generated content you use.”

• Level 4: Full AI - AI may be used to complete any elements of the task, with students directing AI to achieve the assessment goals. Assessments at this level may also require engagement with AI to achieve goals and solve problems.

  • Example: “You may use AI extensively throughout your work either as you wish, or as specifically directed in your assessment. Focus on directing AI to achieve your goals while demonstrating your critical thinking.”

• Level 5: AI Exploration - AI is used creatively to enhance problem-solving, generate novel insights, or develop innovative solutions to solve problems. Students and educators co-design assessments to explore unique AI applications within the field of study.

  • Example: “You should use AI creatively to solve the task, potentially co-designing new approaches with your instructor.”

The AI Assessment Scale is licensed under Creative Commons Attribution, Non-Commercial, ShareAlike 4.0 International by Perkins, Furze, Roe, and MacVaugh (2024)

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Mitigating Unauthorized Use of Generative AI

The strategies offered below are starting points only and instructors may adapt these suggestions to best suit individual teaching contexts, specific courses, and disciplines.

• Administer assessments (tests, quizzes) in person, which may involve flipping your classroom to require students read or watch recordings outside class hours and complete activities and assessments in-class. Consider instituting course policies such as students must earn an overall passing grade on the in-person course assessments to pass the course.

• Engage students in class-based activities including critical discussions, problem-solving activities, polls, and group work requiring real-time thinking and application of concepts.

• Incorporate oral components of larger written assessments for students to demonstrate learning and expand or clarify their work during in-person or virtual meetings.

• Require students to show all work, submit drafts with tracked changes, annotations, outlines, or use collaborative tools (e.g., google docs) for transparency.

• Incorporate scaffolded assessments where tasks build on each other, promoting iterative learning, and providing guidance and feedback throughout the learning process.

• Consider asking for screenshots of library searches or databases to verify research strategies.

• Require students to incorporate course-specific or student-generated content (presentations, discussion posts, activities, slides, lecture materials) into group work, projects, tests, and other assessments.

• Encourage students to make connections between information sources, course materials, and their own contributions.

• Incorporate assignments where students connect current local or regional issues, personal experiences, or reflections to course concepts or course texts. 

• Build in metacognitive elements, prompting students to reflect on their learning and analyze their thinking processes (e.g., Why do you think x? What have you learned? How did you arrive at x?).

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Ways Laurier Colleagues Are Engaging with Generative AI

Explore our entire Generative AI playlist for even more resoruces for teaching. 

• Watch: Generative AI as a Learning Tool in Biology with Christian Danve Castroverde - Emphasizing scaffolded learning, detailed instructions, and transparent grading, Danve highlights the benefits and challenges of using AI tools in education and reflects on student performance and the potential for AI in learning

• Watch: Potential Uses for Generative AI in Teaching with Brandon Mattalo - Consider the opportunities for using generative AI to enhance pedagogical practices including contributing to assessment and rubric design, creating personalized learning experiences for students to get help and study effectively, and streamlining administrative tasks. Explore the ideas and tips in the video resource.

• Watch: Assessment Snapshot: Encouraging Critical Reflections on AI featuring Alanna Harman: Alanna Harman from Laurier's Kinesiology and Physical Education department shares the design, implementation, and outcome of her assessment involving student critiques of ChatGPT outputs. Learn about how innovative assessment design can encourage students to think critically about the role of generative AI in writing and analyzing concepts. 

• Watch: Academic Integrity and Generative AI: A Three-Pronged Approach featuring Lisa Kuron: Lisa Kuron discusses how fostering a climate of trust and respect, encouraging self-reliance, and adapting assessment designs to reflect critical thinking and personal engagement can mitigate some of the challenges posed by generative AI. She highlights the importance of teaching about the limitations of AI, using generative AI as an educational tool to demonstrate its biases and limitations, and encouraging students to rely more on their knowledge and skills.

• Watch: Tarah Brookfield sharing examples from her courses; including iterative ways of engaging with generative AI alongside students throughout a course, and how students have leveraged generative AI to bring creative assessments to life. 

• Watch: Richelle Monaghan sharing examples from her courses; including working with students to identify shortcomings and biases in generative AI. 

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Sharing Ideas

The Teaching Excellence and Innovation team value instructors’ perspectives and insights on the use of generative AI tools in the classroom. To continue to foster conversations across our campuses about generative AI tools likes ChatGPT, we would love to hear from you.

If you are interested, we invite you to share your suggestions, experiences, and feedback with us directly via email wluteaching@wlu.ca.

When you reach out, consider some of the following questions: 

• What tools have you used? 

• Have you leveraged generative AI tools in teaching activities? 

• Have you modified assessments to respond to generative AI? 

• Are there additional resources or supports you provide to students to help them understand appropriate use of generative AI? 

The Teaching Excellence and Innovation team are excited to follow up with you to learn more as you’re willing to share. Further community connection opportunities for Laurier instructors will be announced on Connect. 

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