Assessing student learning is about about understanding how students engage with concepts, apply knowledge, and grow as learners. Thoughtful assessment design, supported by AI tools, allows faculty to create meaningful opportunities for learning while preparing students for an AI-enabled future.
Key Principles of Effective Assessment
Align with Learning Outcomes
Use AI to help design assessments that directly connect to course goals. For example, AI can generate draft quiz questions or case scenarios aligned with learning objectives, which you can refine to ensure rigor and accuracy.Balance Formative and Summative Assessments
AI-driven formative tools (such as chat-based tutors, or automated practice exercises) give students low-stakes opportunities to practice and receive feedback. Summative assessments remain faculty-designed but can be enhanced with AI-assisted grading rubrics, review student responses to help identify potential issues with question clarity or difficulty, and AI can help you analyze large datasets of student performance data to identify patterns and trends that can provide you with valuable insights into student learning, allowing you to make more informed decisions about assessment strategies in the future. Note: it is imperative that no identifying student data be uploaded into any AI. This includes student Panther ID, name, or student information of any kind that could be used to identify a student.Diversify Assessment Methods
Students learn and demonstrate knowledge in different ways. AI can support this diversity by offering personalized practice, generating varied problem sets, or providing scaffolds for students working on projects, presentations, or essays.Prioritize Authentic Assessment
With generative AI widely available, designing authentic assessments is essential. Assignments that require critical thinking, reflection, application to real-world contexts, or integration of personal experience are more resistant to AI “shortcuts.” Faculty can also invite students to use AI transparently (e.g., drafting outlines, generating data visualizations) and then reflect on or critique those outputs.Clarify Expectations and Feedback
Provide clear guidance on what AI use is acceptable in your class. Consider requiring students to submit an “AI usage statement” with assignments. AI can also help faculty generate draft rubrics or sample feedback, which you can tailor to student needs.Support Diverse Learners
AI tools can help bridge gaps for students who need additional practice, language support, or personalized explanations. Offering multiple assessment formats—written, oral, digital, creative—ensures equitable opportunities while teaching students how to responsibly use AI in diverse contexts.Leverage AI for Efficiency, Not Replacement
AI can streamline administrative tasks like generating quiz banks, providing draft feedback, or analyzing common errors in student work. This frees faculty time for deeper engagement—mentoring, dialogue, and individualized guidance.
AI-Enhanced Assessment Strategies to Try
AI-Assisted Low-Stakes Quizzing: Use AI tools to generate practice quizzes that adapt to student progress.
AI Tutors for Retrieval Practice: Encourage students to quiz themselves with a course-specific AI tutor that guides their reasoning rather than giving direct answers.
Critical AI Analysis Assignments: Ask students to generate an AI response to a question, then critique its accuracy, bias, and limitations. Additionally, ask the students to provide sources for the information and critique their legitimacy.
Portfolio with AI Reflection: Have students use AI tools to brainstorm or organize projects, but require reflective commentary on how AI shaped their process, prompts they used in this process, and how they refined their prompts to acquire a satisfactory result.
Peer Review + AI Feedback: Combine human peer review with AI-generated suggestions, allowing students to compare feedback and refine their work.
AI-Supported Concept Mapping: Use AI to suggest connections between key concepts, which students must edit, annotate, and justify.
- Role-Play: AI adopts the role of a persona—such as a historical figure, industry expert, or client—allowing students to engage in realistic dialogue, practice professional skills, and explore multiple perspectives in a low-stakes environment.
- Case Studies: Learners analyze authentic or AI-generated scenarios, applying theory to practice while demonstrating critical thinking, problem-solving, and evidence-based reasoning.
Here are two examples for Using AI in Assessment
Example: Biology Class
Assessment Goal: Check students’ ability to apply knowledge of cell biology to real-world problems.
With AI: The instructor uses an AI tool to generate a bank of practice quiz questions on cell functions. Students take these low-stakes quizzes outside of class, receiving immediate feedback.
Authentic Task: On the actual exam, students must analyze a case study about a patient with a mitochondrial disorder. They can use AI to brainstorm possible cellular impacts, but must explain in their own words which AI outputs they agreed or disagreed with and why.
Reflection: Students submit a short statement describing how AI shaped their thinking and where their own reasoning went further.
Why it works: Students gain retrieval practice from AI-generated quizzes, but the summative assessment ensures they apply biology concepts critically and authentically.
Example: Literature Class
Assessment Goal: Develop students’ ability to interpret texts and critique different perspectives.
With AI: The instructor asks students to use an AI tool to generate a sample analysis of a passage from Toni Morrison’s Beloved.
Authentic Task: Students then write their own literary analysis, critiquing the AI’s interpretation—pointing out where it missed nuance, introduced bias, or overlooked historical/cultural context.
Reflection: As part of the assignment, students submit an “AI critique paragraph” explaining what they learned by comparing their interpretation to the AI’s.
Why it works: Students practice close reading and interpretation, while also building digital literacy by evaluating AI’s limitations in humanistic analysis.
Quick Tips for Using AI in Assessment
✅ Be Transparent – Clearly state in your syllabus what kinds of AI use are acceptable (e.g., brainstorming vs. completing assignments), and how that will (or will not) impact a student's grade.
✅ Align with Learning Goals – Use AI to generate draft quizzes, rubrics, or practice questions, but refine them to fit your course outcomes.
✅ Mix Human + AI Feedback – Combine your feedback with AI-generated suggestions so students learn to evaluate multiple perspectives.
✅ Require Reflection – If students use AI, ask them to explain how they used it, what they learned, and what they would change.
✅ Promote Authentic Tasks – Design assignments that require critical thinking, personal application, or real-world problem solving—things AI cannot do alone.
✅ Leverage Efficiency – Use AI to automate repetitive tasks (e.g., generating practice questions, spotting common errors), freeing time for deeper teaching.
✅ Encourage AI Critique – Assign activities where students analyze AI outputs for accuracy, bias, and quality, strengthening digital literacy.
Remember, CAT staff are here to help you! For support creating something that works for you, schedule a consultation with a member of the CAT Team. You may also sign up one of CAT's many professional development opportunities which include AI programming and other workshops to broaden your pedagogical expertise, experiment with diverse teaching strategies, and implement these approaches to meaningfully enhance student learning and achievement.