Shared Language for Responsible AI Integration

Authors

• Asa B. Stone, University of Nebraska-LincolnFollow
• Mark C. Stone, University of Nebraska-LincolnFollow
• Alisha Bevins, University of Nebraska-LincolnFollow
• Jean Claude Niyomugabo, University of Nebraska-LincolnFollow
• Irene Magara, University of Nebraska - LincolnFollow
• Jacob Abaare, University of Nebraska-LincolnFollow
• Derek M. Heeren, University of Nebraska-LincolnFollow
• Mubarak Abu ZouriqFollow

Date of this Version

6-2026

Document Type

Article

Citation

Stone, A. B., Stone, M. C., Bevins, A., Niyomugabo, J. C., Magara, I., Abaare, J., Heeren, D. M., & Abu Zouriq, M. (2026). Shared language for responsible AI integration: A framework for responsible AI use in engineering education. White paper. Available at: https://digitalcommons.unl.edu/prairie-ai

Comments

Open access

License: CC BY-NC 4.0

Abstract

As AI rapidly reshapes how we work and learn, employers increasingly seek graduates who can think before they prompt, exercising judgment under pressure rather than merely producing output. Yet students are praised for AI use in one course and penalized for it in the next, and faculty are left to lead responsibly on shifting ground, with no shared language to guide them.

This paper introduces the PRAIRIE Framework for AI Integration, a shift from reactive gatekeeping toward proactive stewardship. It emerged from a qualitative sentiment analysis of three communities (students, faculty, and industry partners) whose concerns converged on one need: a shared, multilevel language for when, how, and to what end AI belongs in teaching and learning. The framework crosses two dimensions: six graduated levels of AI use (from Human Only to AI as an Agent), calibrated by what the student must still own, and the kind of cognitive work a task requires, drawing on Bloom's Revised Taxonomy (from Remember to Create).

These dimensions cultivate five human capacities drawn from industry partners' account: informed judgment, leadership and collaboration, communication, systems thinking, and adaptive capacity. Co-created with the communities it governs, the framework keeps human judgment non-delegable.