AI & Assessment

AI Assessment

The widespread availability of generative AI tools has raised concerns about the integrity and validity of assessments used to evaluate student learning. At the same time, it also presents opportunities to restructure assessments to be more authentic, inclusive, and creative indicators of student learning (Corbin et al., 2025). The extent to which generative AI is permitted in completing summative assessments may depend on the course learning outcomes, i.e., the knowledge, skills, or experiences students are expected to acquire by the end of the course, instructor competency with and preference for using AI, as well as university policies. Regardless of the level at which generative AI use is permitted in assessments, the following principles are essential in encouraging meaningful learning in your courses while reducing the risk of AI-facilitated cheating. Additionally, explore CTL’s webpage on the AI assessment scale for ideas on when, why, and how to meaningfully incorporate AI use in assessments. 

Review your existing assessments (e.g., put the assessment instructions in private mode in ChatGPT or enterprise mode in CoPilot to prevent them from being used as training data) and consider re-designing or removing questions that elicit A or B-level answers 

Be transparent with students regarding your reasons for the level of AI usage permitted in the given assessment, your use of AI as an instructor to create assessments, grade, or tools used to detect unauthorized use of AI in the syllabus. Given that at least 77% of CU students prefer instructors to disclose their use of AI, as indicated in a survey investigating undergraduate perspectives on AI, this is likely to also build trust in the classroom. 

Redesign summative assessments to be authentic, equity-minded, and relevant to learning outcomes.

Create learning outcomes that emphasize various aspects of significant learning, including critical thinking, evaluative, analytical, and metacognitive skills, which are transferable to multiple contexts.  

Incorporate course activities and assessments that foster a growth mindset by emphasizing the process of learning, promoting learner motivation to engage in productive struggle through persistence through challenges, and providing opportunities to reflect on learning.

Cultivate and promote AI literacy around AI use in your class through structured activities, readings, and open dialogue with students to inform course policy on AI usage. Open dialogue may be critical given that a CU survey on undergraduate perspectives on AI found that over 90% respondents preferred flexible AI use in classes, i.e., neither required nor prohibited.

To promote ethical and informed use of AI, familiarize yourself and your students with the university policy on AI tools, data classification standards, privacy guidelines, as well as the honor code, given that a majority of the students want direct guidance from their professors on the acceptable use of AI

Provide students with sufficient support and opportunities for feedback by clearly outlining expectations using rubrics and incorporating student self- or peer assessments through scaffolding, thus promoting holistic student success. 

Additional Resources:

Want to Stay Up-to-Date on the Center for Teaching & Learning’s AI Events & Resources? 

Email Blair Young to be added to our Teaching & AI Listserver

If you prefer to self-enroll, login to Google Groups and search for Teaching & Learning with AI Community of Practice