As you finalize your course outlines for the upcoming semester, we encourage you to include a statement that provides guidance for the appropriate use of AI. Your AI statement is an opportunity to begin a dialogue with students about making ethical, deliberate choices. Consider co-designing these guidelines with your students during the first week of classes, and plan to revisit and adapt them as the term progresses. Following are two models that can help you establish a common ground.<\/p>\n\n\n\n
AIAS is a five-level scale from no AI assistance to full AI collaboration. Each level describes a different kind of assignment task, not a degree of permission. The scale helps educators consider how their assessment might need to be adjusted considering GenAI tools, and clarity to students how and where GenAI tool might be used in their work. Note, we shared the original 2023 AIAS in a previous blog<\/a>. If you have been using the AIAS, consider revisiting the updated as v2.1.<\/p>\n\n\n\n This visual model categorizes classroom tasks into three colour-coded permission levels.<\/p>\n\n\n\n An effective AI policy is never generic. It\u00a0should\u00a0align\u00a0with\u00a0what you want students\u00a0to learn.\u00a0When students understand the pedagogical\u00a0why<\/em><\/strong>\u00a0behind\u00a0the\u00a0boundaries, they are more likely to make responsible choices. Following are\u00a0three\u00a0examples of how to align your policy with specific course outcomes.\u00a0<\/p>\n\n\n\n Course learning\u00a0outcome<\/strong>:<\/em><\/strong>\u00a0<\/em>Draft original analytical essays that\u00a0demonstrate\u00a0a distinct, authoritative voice and critical reasoning, by\u00a0careful reading\u00a0and synthesizing\u00a0course\u00a0texts.\u00a0<\/p>\n\n\n\n AI statement:<\/strong>\u00a0Writing is an essential vehicle for thinking. Because the\u00a0objective\u00a0of this course is to cultivate your unique human voice and original critical analysis, the use of generative AI to write draft assignments or summarize readings is prohibited (Red Light). Outsourcing this work denies you the cognitive practice needed to grow as a thinker. However, you are welcome to use basic spelling and grammar checkers (Yellow Light) to polish your own completed drafts. Our focus is on\u00a0the human\u00a0‘aliveness’ and\u00a0original\u00a0perspective of your ideas.\u00a0<\/p>\n\n\n\n Course learning outcome:<\/strong>\u00a0Construct strategic business plans that meet industry standards by\u00a0using\u00a0emerging digital technologies to analyze complex market datasets.\u00a0<\/p>\n\n\n\n AI statement:<\/strong>\u00a0To prepare you for the modern workforce, we welcome the thoughtful integration of generative AI tools in this course (Green Light).\u00a0Using\u00a0AI to brainstorm strategic ideas or analyze datasets directly supports our course\u00a0learning goals. However, you are solely responsible and accountable for the accuracy of what you\u00a0submit. Generative AI\u00a0frequently\u00a0hallucinates\u00a0fake facts, numbers, and citations. You must verify every output against reliable, original sources. Every assignment\u00a0using\u00a0AI must conclude with an <\/strong>AI disclosure statement detailing the tools used, your prompts, and your verification process.\u00a0<\/p>\n\n\n\n Course learning outcomes:<\/strong>\u00a0\u00a0<\/p>\n\n\n\n Theory: Analyze computer-controlled vehicle network faults to manufacturer diagnostic standards by interpreting wiring diagrams and system parameters during written unit exams. <\/p>\n\n\n\n Practical: Execute precision circuit measurements to industry safety tolerances using digital multimeters on live shop vehicles <\/p>\n\n\n\n AI statement:\u00a0<\/strong>In the skilled trades, your professional competence and workplace safety rely on alignment of your head (technical knowledge), your hands (practical skill), and your heart (pride in safe, ethical craftsmanship).\u00a0Automotive service relies heavily on digital technology, and AI-powered diagnostic assistants and troubleshooting chatbots are rapidly becoming standard tools on the shop floor. We want you to be fluent in these industry technologies, which is why our policies are designed to build the foundational knowledge you need to use them safely and critically.\u00a0<\/p>\n\n\n\n You do not have to build your policy from scratch. The educational community has collaborative and evolving resources designed to help you draft and customize your AI statement. Consider using the resources below as a starting point. <\/p>\n\n\n\n Creating your course policy on AI | Teaching Commons<\/a>. This post offers a practical roadmap for designing a student-centered AI syllabus policy that protects academic integrity while serving as an active starting point for transparent classroom conversation. <\/p>\n\n\n\n AI Syllabus Language Guide.<\/a> This comprehensive guide provides educators with a practical, step-by-step roadmap for building a transparent AI syllabus policy, with visual tools like the AI Stoplight Model. <\/p>\n\n\n\n Classroom Policies for AI Generative Tools<\/em><\/a>.<\/em> This resource highlights a range of educator-developed policies for using AI-generative tools, helping instructors create or refine their own. Click the policies tab to view the collection. <\/p>\n\n\n\n Generative AI syllabus statement generator<\/a>. This syllabus statement generator tool assists with creating language for an AI syllabus statement.\u202f <\/p>\n\n\n\n Classroom Policies for Generative AI Tools<\/a>. This crowdsourced Google document shows policies from various educators on generative AI tools. The resource is designed to help instructors create guidelines for using these tools.\u202fVisit the Policies tab to view the collection. <\/p>\n\n\n\n Student Use of AI: A Helpful Framework | Edutopia<\/a>.\u202f\u202fThis decision tree guides students to ask key questions about their AI use and to reflect on how it benefits their learning.<\/p>\n\n\n\n In upcoming blog posts, we will take a closer\u00a0look at the AI Assessment Scale (AIAS) v2.1,\u00a0and\u00a0strategies for documenting and disclosing AI use.<\/p>\n\n\n\n We are collecting examples of course AI use policy statements that are working well in practice. Sharing your policy helps us learn from one another and build a collection of examples that can support instructors across VIU. To contribute, submit your examples through our anonymous Microsoft Form [link<\/a>].<\/p>\n\n\n\n Bridgeman, A., & Liu, D. (2025). The Sydney Assessment Framework<\/em>. The University of Sydney. https:\/\/educational-innovation.sydney.edu.au\/teaching@sydney\/the-sydney-assessment-framework<\/a><\/p>\n\n\n\n Corbin, T., Dawson, P., Nicola-Richmond, K., & Partridge, H. (2025). \u2018Where\u2019s the line? It\u2019s an absurd line\u2019: towards a framework for acceptable uses of AI in assessment. Assessment & Evaluation in Higher Education<\/em>, 50<\/em>(5), 705\u2013717. https:\/\/doi.org\/10.1080\/02602938.2025.2456207<\/a><\/p>\n\n\n\n Eaton, L. (2026). Classroom Policies for AI Generative Tools\u2014Google Docs<\/em>. Retrieved July 28, 2023, from https:\/\/docs.google.com\/document\/d\/1RMVwzjc1o0Mi8Blw_-JUTcXv02b2WRH86vw7mi16W3U\/edit<\/a>.<\/p>\n\n\n\n2. The AI Stoplight 🔗<\/a><\/h4>\n\n\n\n
\n
\n
Aligning policies with your course learning goals <\/h3>\n\n\n\n
AI Stoplight examples<\/h1>\n\n\n\n
1. Writing-focused policy (e.g., literature or creative writing)<\/h4>\n\n\n\n
2. Application-focused policy (e.g., business analytics or design)\u00a0<\/h4>\n\n\n\n
3. Trades-focused policy (e.g., automotive service technician)\u00a0<\/h4>\n\n\n\n
\n
\n
\n
AI syllabus resources <\/h1>\n\n\n\n
Looking Ahead <\/h3>\n\n\n\n
Attribution<\/h3>\n\n\n\n