Resource Library
Resource Library
For students: AI in your coursework
Your instructor sets the AI policy for each course, and it lives in the syllabus. When the syllabus leaves it open, ask first and lean toward disclosing.
PRAIRIE supports a college-wide six-level AI use taxonomy that instructors use to set expectations: Level 0 (No AI), Level 1 (Tool), Level 2 (Tutor), Level 3 (Collaborator), Level 4 (Co-Creator), and Level 5 (Agent). Your instructor picks the level; the taxonomy gives you both a shared vocabulary.
When you do use AI, disclose it: a short note naming the tool, what you used it for, and how you verified the output.
Contact: prairie@unl.edu
For faculty: AI in your course
Each instructor sets the AI policy for their own course. PRAIRIE makes that straightforward with three things: the six-level taxonomy as shared vocabulary, sample syllabus statements for common postures (AI-free, Tutor-only, Collaborator), and a standard student disclosure paragraph that makes grading easier.
Contact: prairie@unl.edu
Enterprise AI access
Microsoft 365 Copilot licenses are available to College of Engineering staff and teaching faculty to support productivity and instructional needs.
For the full set of enterprise AI tools across the University of Nebraska, including eligibility and how to request access, visit central ITS.
Data security and AI
Before you paste anything into an AI tool, ask: what kind of data is this, and is the tool licensed for it?
Public or non-sensitive data
Any UNL-licensed tool is fine.
FERPA-protected student data
Keep it inside UNL-licensed enterprise tools only.
IRB or human-subjects data
Get IRB review of the workflow before using any AI tool.
Sponsor-confidential research data
Check sponsor terms first; some restrict AI use.
Anything with secrets or credentials
Strip them before pasting.
For more detail on which tools fit which kind of data, see the University of Nebraska ITS guidance on AI tool categories.
AI Maker Space
Opened in 2025 in partnership with Scott Data Center, the AI Maker Space gives COE students access to NVIDIA H100 GPU compute backed by the Holland Computing Center. Undergraduates can join through the Husker AI student organization or through a faculty research advisor.
Get started
Email prairie@unl.edu with the subject "Add me to Husker AI list."
First steps with AI (for staff)
Each of these takes about 30 minutes:
- Draft an email
You have been putting off using Claude in Copilot, then edit and send. - Summarize a long document
By pasting it into Copilot and asking for a one-paragraph summary plus action items. - Clean up messy data
By asking Copilot to turn an ugly list into a tidy table. - Drop in to a PRAIRIE coffee hour
Bring a question, and leave with a path forward.
Contact prairie@unl.edu
Communities of Practice
Faculty-led groups that cross departments and build momentum for shared interests. Active groups include the Teaching and Learning Community of Practice, which co-created our Responsible AI framework. A seed-grant cycle opens in fall 2026.
Contact: Mubarak Abu Zouriq
Partner with PRAIRIE
Three ways for industry and community partners to engage: bring a problem to the reverse-pitch competition in the Applied AI course, support signature programming such as Husker AI Days and the Build-a-thon, or join the Industry Advisory Board for strategic input and early access to talent.
Contact: Mark Stone
Responsible AI framework
ur Shared Language framework for responsible AI integration pairs six graduated levels of AI use (from Human Only to AI as an Agent) with Bloom's Revised Taxonomy to cultivate five durable human capacities: informed judgment, leadership and collaboration, communication, systems thinking, and adaptive capacity. It was co-created by our student, faculty, and industry advisory groups.
Publications
Two open-access white papers ground our Responsible AI work:
Shared Language for Responsible AI Integration (Stone, Stone, et al., June 2026). The PRAIRIE Framework for AI Integration: six levels of AI use crossed with Bloom's taxonomy to cultivate five durable human capacities. Read on Digital Commons
Responsible AI in Teaching and Learning (Stone, Stone, Heeren, Pitla, February 2026). Six guiding principles for responsible AI in higher education: purposefulness, transparency, integrity and attribution, critical AI literacy, equity and access, and privacy and data protection. Read on Digital Commons
Stay Connected
Subscribe to the PRAIRIE mailing list for a weekly preview, the monthly PRAIRIE Pulse, and event announcements. Email prairie@unl.edu with "subscribe" in the subject line.
Upcoming this fall: the Husker AI Days kickoff week in late August, the October Build-a-thon, and the return of the PRAIRIE Seminar Series.