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Battle, K., Cherner, T., Duprey, M., Halpin, P., Henson, B., James-Springer, C., Jouad, Y., Kumari, R., Manfra, M., Nadir, H., Quigley, L., Reid, A., Strigel, C., & Willoughby, M. (2026). AI tools in course design: Framework and supporting materials. RTI International.
This report presents a conceptual framework and supporting materials to help college and university instructors determine whether and how to use AI tools in course and assignment design while preserving student learning. The framework comprises four steps: Decide, Commit, Design, and Evaluate. It addresses ethical commitments concerning data and privacy, equity and access, mutual transparency, and learning processes; independent dimensions of offloading, interactivity, and transparency; and evaluation of both products and documented thinking. Supporting materials include a decision-making guide, frequently asked questions, a glossary, and a literature review. The framework was developed through a five-institution collaboration involving RTI International, Durham Technical Community College, UNC-Chapel Hill, UNC Greensboro, and NC State University.
RTI shares its evidence-based research - through peer-reviewed publications and media - to ensure that it is accessible for others to build on, in line with our mission and scientific standards.