As generative AI tools reshape course design, syllabus prep, and assignment planning, a new question has emerged for faculty: How much should we disclose about our own use of AI?
While we frequently discuss AI policies for students, modeling our own ethical use is a powerful way to uphold the Honor System. When we are transparent about our workflows, we demystify the technology and build trust.
But let’s be honest—faculty are already pressed for time. The last thing anyone needs is a mountain of administrative clerical work just to keep track of a quick brainstorming session with a chatbot.
To bridge this gap, a March 2026 EDUCAUSE Review article introduced the GenAI Use Transparency Framework. The beauty of this framework is that it rejects a “one-size-fits-all” mandate. Instead, it scales transparency to match the actual impact of the AI tool, protecting your time while keeping your teaching transparent.
The Four Levels of Faculty GenAI Use
The framework breaks AI integration into four distinct tiers, clarifying exactly when you need to keep an internal record and when you should share it with your students.
Source: From Prompt to Practice: A Framework for Transparent GenAI Use in Higher Education
Level 1: Minimal Use (Peripheral Brainstorming)
- The Routine: No action required.
- Why it fits the framework: Because the AI is only assisting with surface-level editing, syntax variance, or icebreaker inspiration, it does not alter the underlying disciplinary structure of the course. The authors do not recommend any student-facing disclosure or formal archiving here.
Level 2: Moderate Use (Component Input)
- The Internal Record: Before editing, copy the raw, unedited AI output and drop it into a text file or your master draft document in your course folder on Box or OneDrive (or wherever you save your files).
- The Student Disclosure: A single, brief sentence embedded directly into the specific Canvas assignment description, quiz header, or module page where that resource lives.
- Why it fits the framework: At this tier, the AI provides raw building blocks (e.g., initial draft quiz questions or an assignment scenario), but your human expertise does the heavy lifting of revising and aligning it. The record ensures you can verify your original quality control step if ever asked.
Level 3: Significant Use (The Core Backbone)
- The Internal Record: Move your generation workflow into a collaborative editor. Use Word for the Web’s version history to automatically log your extensive edits, restructuring, and validation work. Additionally, download a quick PDF of your raw chat log/prompts and drop it into your local course folder.
- The Student Disclosure: A prominent, detailed note in the specific Canvas module overview and explicitly referenced in the relevant assignment instructions.
- Why it fits the framework: This fulfills the article’s core requirement for Level 3: proving the human-in-the-loop validation process. By using built-in software version tracking, you satisfy the framework’s “edit log” rule automatically without adding manual clerical work.
Level 4: Comprehensive Use (AI-Driven Artifacts)
- The Internal Record: Export and save the full, absolute prompt-and-response history from your AI tool (as a text or PDF file) directly alongside your course materials in your stable cloud storage.
- The Student Disclosure: A dedicated, transparent policy section in your Canvas Syllabus page explaining the role of the AI system, its known limitations/biases, and your strict evaluation criteria, alongside a notice on the specific artifacts themselves.
- Why it fits the framework: Because the majority of the instructional artifact is generated under your systemic prompt engineering rather than manual text generation, your primary intellectual contribution is the prompt structure and the subsequent systemic audit. Archiving the exact prompt chains is essential for long-term institutional accountability and course continuity.
The Faculty Toolkit: Copy & Paste Statements
To make transparency completely frictionless, here are plug-and-play statements you can drop directly into your Syllabus, Canvas Modules, or Assignment Prompts. Simply fill in the brackets.
For Moderate Use (Level 2)
Notice on Course Materials: Portions of these [quiz questions / discussion prompts / case studies] were initially generated using [Tool, e.g., ChatGPT-5.5] to help brainstorm formats. They were subsequently reviewed, revised, and fact-checked by me to ensure absolute accuracy and alignment with our course learning objectives.
For Significant Use (Level 3)
AI Assistance Disclosure: The core framework and scenarios for this [simulation / interactive module] were developed with the assistance of [Tool, e.g., Claude Sonnet 5]. The pedagogical structure and final editing represent my original design, and all AI-generated content has been strictly vetted for academic integrity, factual accuracy, and disciplinary relevance.
For Comprehensive Use (Level 4)
Transparent AI Integration: This [adaptive module / self-study guide] was comprehensively generated using [Tool, e.g., Microsoft Copilot] as an experiment in AI-driven learning. While the instructor designed the prompts and strictly audited the final output for accuracy and bias, please note that AI tools can still present limitations. If you spot any anomalies or have questions about the material, please contact me immediately.
By scaling our transparency, we do more than just protect academic integrity—we actively model the exact type of critical reflection and accountability we expect from our students.
Want to dive deeper into the pedagogy? Read the full analysis in the EDUCAUSE Review article.
