Grad-AI

What Grad-AI is (and is NOT)?

• It is applied: Grad-AI emphasizes real-world use of AI within specific fields, whether analyzing historical archives, modeling environmental systems, improving instructional design for teachers, or optimizing business processes.
• It is interdisciplinary: Grad-AI is designed for all graduate disciplines, including the humanities, social sciences, education, sciences, and professional programs. It is not limited to tech fields.
• It is structured and intentional: AI integration is guided by clearly defined standards. Courses earning the AI Signature Label meet committee approved criteria that ensure academic rigor, learning value, and coherence.
• It is ethical and responsible: Responsible AI use is foundational. Grad-AI foregrounds transparency, accountability, and critical evaluation of AI tools and impacts.

The AI-Signature Course Label: Making your skills visible.

What It Is? The “AI-Signature Course Label” is a course attribute awarded to graduate courses that meet clear criteria for meaningful AI integration. The label appears in the course catalog and schedule, signaling to both students and employers that the course includes verified, field-specific AI competency.

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Pathways to Adoption

We offer three distinct tracks for faculty to adopt the label, depending on the level of curriculum change required:

• Pathway 1: Enhance – Integrate AI tools or assignments into an existing course. This is designed for a shorter timeline and moderate syllabus updates.

• Pathway 2: Create – Develop a new, stand-alone course explicitly focused on discipline-specific AI applications.

• Pathway 3: Certify – Develop an Applied-AI Certificate.

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Faculty Support: The Grad-AI Collaborative

We don’t expect faculty to do this alone. The Grad-AI Collaborative is our series designed to inspire and equip you. Support is prioritized over compliance.

• Best-Practice Panels: Hear from peers sharing effective strategies and lessons learned.

• Expert Seminars: Hands-on training sessions on tools and pedagogical approaches.

• Success Stories: Real examples of AI implementation in MTSU courses.

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Past and Upcoming Events

Upcoming & Ongoing:

• Wednesday, April 8, 2:30-3:30 pm, LIB 348 or synchronously on Zoom, Title: From Hype to Habit: Practical AI Workflows for Professionals, Rajah Smart (in Collaboration with The Provost Office and CTM)
  

• February 2026 to May 2026 (ongoing), Title: Faculty Learning community – AI in STEM Curriculum, Moderators: Todd Moore, Joshua Phillips and Racha El Kadiri (See Flyer)

Past:

• Wednesday, March 25, 1:30-2:30 pm, LIB 348 or synchronously on Zoom, Title: Tips and Tricks for Using AI to Increase your Productivity, John Wallin (in Collaboration with The Provost Office and CTM)
  Click here for recording
• Wednesday, February 11, 2026, 11:00 am –12:00pm, AI Prompts and Frameworks for Curriculum Development, Todd O’Neill (in Collaboration with The Provost Office and CTM)
  Click here for recording
• Wednesday, November 19, 2025, 1:00-2:00 pm, Teaching Information Literacy in a World of Chatbots, Eric Detweiler (in Collaboration with The Provost Office and CTM)
  Click here for recording
• Tuesday, November 4, 2025, 2:30-3:30 pm, Running Open-Source AI on Your Device, Keith Gamble (in Collaboration with The Provost Office and CTM)
  Click here for recording
• Thursday, October 16, 2025, 1:30-2:30 pm, A Primer on Artificial Intelligence, Keith Gamble (in Collaboration with The Provost Office and CTM)
  Click here for recording
• Wednesday, September 17, 2025, 11:00 am – 12:00 pm, AI Chatbots in the Classroom, Carlos Coronel (in Collaboration with The Provost Office and CTM)
  Click here for recording

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Contact

Get Involved.

• For Faculty: Questions about the Signature Label or Stipends?

• For Students: Looking for AI courses?

• Contact: The Office of the Associate Dean, College of Graduate Studies.