AI and the Feedback Process

Providing Feedback on Student Learning

Generative AI tools may provide opportunities for faculty to deliver timely, formative, and personalized feedback to students on their learning, while providing options for students to engage in self-assessment. Whether used by students to assess their own work or by faculty to evaluate student learning, faculty and students must engage in intentional decision-making about when and how AI should support the feedback process. These questions often relate to issues of transparency, privacy, and appropriate and ethical use of AI.

This webpage provides a curated list of resources organized by key decision points faculty may face as they evaluate student learning in the age of AI.

Key Decision Points and Resources

Student Use of AI Tools for Feedback
How might my students use AI tools to generate feedback on their own work?
- USG Student Guide to Generative AI Literacy (Topic: Self-Study Techniques)
- Additional Considerations when Allowing or Requiring AI Use (KSU Digital Learning Innovations).
- PAIRR Feedback Guide (University of Georgia)
Evaluating Student-AI Collaborative Work
What is the best approach for assessing student work if my course policy permits student-AI collaboration?
- Assessing Student-AI Collaboration: Innovative Grading & Rubric Strategies (University of Virginia)
Using AI to Provide Students Feedback
In what situations might it be appropriate or inappropriate for me to use generative AI tools to provide personalized feedback to my students to support their learning?
- Guidelines for AI Use at KSU (Kennesaw State University)
- “Grading and (re-) defining quality” in Teaching with AI: A practical guide to a new era of human learning
- Using Generative AI for Feedback (Columbia University)
- The Digital Red Pen: Efficiency, Ethics, and AI-assisted grading (Northern Illinois University)
Communicating AI Use to Students
How should I communicate my decisions to use (or not use) AI tools in grading and providing feedback to my students?
- Guidelines for AI Use at KSU (Kennesaw State University)
- Citing Artificial Intelligence (AI) (Kennesaw State University)

Sources

Allison, K. (2025, November). Assessing student-AI collaboration: Innovative grading & rubric strategies. UVA Teaching Hub, University of Virginia.
Bowen, J.A. and Watson, C.E. (2026). Grading and (re-) defining quality. InTeaching with AI: A practical guide to a new era of human learning 2nd Edition. (pp. 191 – 205). Johns Hopkins Press.
Hartung, F., & Poproski, R. (2026). PAIRR feedback guide. University of Georgia Center for Teaching and Learning.
Hirsch, A. (2024, October 29). The digital red pen: Efficiency, ethics, and AI-assisted grading. Center for Innovative Teaching and Learning, Northern Illinois University.
Kennesaw State University, Digital Learning Innovations. (2025, February 12). Additional considerations when allowing or requiring AI use [PDF].
Kennesaw State University, Digital Learning Innovations. (2025, February 12). KSU AI citation guidance [PDF].
Kennesaw State University, University Information Technology Services. (n.d.). Guidelines for AI use at KSU.
Teachers College, Columbia University, Digital Futures Institute. (n.d.). AI in education guide: Using AI for feedback.
USG Student Guide to GenAI Literacy (University System of Georgia Office of Teaching and Learning Excellence; request/download access)