Assessments and Artificial Intelligence (AI)

Communicate Expectations with AI Statements

Clearly communicating expectations helps students understand when and how AI can be used in your course and on individual assignments.

With the update to Policy 331.1, syllabi are required to include a generative AI statement explaining how students may use AI in your course and how the instructor will use AI. Your syllabus can provide general guidance, while individual assignments can include more specific expectations when needed.

When developing your AI use expectations:

• Be specific. Explain whether AI may be used and for what purposes.
• Connect expectations to learning goals. Consider whether AI use supports or interferes with what students are expected to learn and demonstrate.
• Explain transparency. Let students know whether and how they should disclose or cite AI use.
• Clarify assignment-specific expectations. AI use that is appropriate for one assignment may not be appropriate for another.
• Invite questions. Give students an opportunity to clarify expectations before submitting their work.

Examples of AI Use Statements

AI Use Guidelines by Dr. Catheryn Reardon provides examples of different levels of AI use, along with sample syllabus language.

These examples are starting points rather than one-size-fits-all statements. Your expectations should reflect the purpose of the course, the assignment, and the learning students are expected to demonstrate.

Intentionally Incorporate AI into Assignments

When appropriate for the learning goals, AI can become part of the learning process rather than simply something students are permitted or prohibited from using.

Consider how AI might help students:

• Generate ideas, examples, or possible approaches
• Critique an AI-generated response for accuracy, bias, quality, or completeness
• Apply course concepts to evaluate or improve an AI-generated response
• Compare AI-generated content with course materials or other sources
• Reflect on how AI influenced their thinking or final product.

The key is to give AI use a purpose connected to the learning goal.

For example, an assignment might ask students to generate an AI response, evaluate it using course concepts, identify inaccuracies or weaknesses, and revise it. In this case, the learning comes from evaluating and applying knowledge, not simply generating text.

If students are expected to use AI, provide clear instructions about the tools they may use, permitted uses, what they are responsible for verifying or revising, and whether they should document or disclose their AI use.

Responding to Suspected Unauthorized AI Use

Even with clear expectations, student work may raise questions about whether assignment requirements were followed. When concerns arise, consider the assignment expectations, the work submitted, and the evidence available. Give students an opportunity to explain their work and follow NDSU Academic Honesty and Integrity Policy when appropriate.

Consider:

• What specifically raised the concern?
• What AI expectations were communicated for this assignment?
• Does the work contain fabricated information, sources, or citations?
• Can the student explain their ideas, sources, or process?
• What other information may help provide context?

AI use cannot be reliably determined simply by examining a student’s writing. Instead, gather relevant information and consider whether the submitted work meets the expectations and learning requirements established for the assignment.

For additional guidance, see:

• 5 Ways to Verify Student Learning in the Age of AI – Faculty Focus (can be accessed with a free account) article provides sample language for talking with a student to verify their learning.
• What to Say When You Suspect Students Are Misusing AI – Harvard Business Impact article with four clues to look for and how to respond to a student.
• When You Suspect AI Misuse: A Decision Framework for Faculty and Administrators – Inside Higher Ed (IHE) article on the distinction between course-level expectations and violations of institutional policy.

Related Resources

• Bertram Gallant, T., & Rettinger, D.A. (2025). The Opposite of Cheating: teaching for integrity in the age of AI. University of Oklahoma Press.
• Bowen, J.A., & Watson, C.E. (2026). Teaching with AI: a practical guide to a new era of human learning. Johns Hopkins University Press.
• Citing Generative AI - Purdue University reference for citing AI use in APA and MLA formats.
• From Prompt to Practice: A Framework for Transparent GenAI Use in Higher Education - EDUCAUSE article about a four-level framework to disclose AI use.
• I Used AI (But Not Really?): The Curious Case of AI Disclosures - OLC article with recommendations and sample of an AI disclosure statement.
• Instructor Resources - The Office of Teaching and Learning guidebooks for instructor and students to incorporate AI into the classroom responsibly.
• Listening to Skepticism: What Faculty Concerns About Generative AI Reveal - EDUCAUSE article about.
• The Assessment Debate in an AI World - EDUCAUSE podcast on how AI is reshaping conversations about learning assessment in higher education.