Quick Start Program & Course Checklist

Establish the first four points at the program level. Apply the last five elements to each course.

Examine AI in your field.
How has AI impacted disciplinary practice? What “starter job” skills have been replaced by AI? How can the program ensure students are prepared to perform effectively in the field? Resources: recent graduates, alumni, industry partners, accrediting bodies.
Name the human capabilities your graduates need.
These are the durable skills your program protects: problem framing, curiosity, ethical decision-making, systems thinking, written communication, fact checking, critical judgement, contextual understanding, iterative thinking, risk identification and mitigation, adaptive judgement, accountability.
Create consistency.
Across the program, establish a shared AI position statement, syllabus language, and disclosure requirements.
Map skills to course levels.
Foundations, Fluency, Application, Transfer.

Introductory Courses: Foundations.
Which courses introduce the discipline? Integrate AI fluency elements in the course, as a module or as a continuing study. Students should understand of how AI works; identify its capabilities and limitations; discern inaccurate and hallucinated information; and use tools for low-stakes tasks.
Intermediate Courses: Fluency.
What mid-level courses are an appropriate lens for AI context building within the discipline? Students should understand how AI is impacting the discipline; use AI purposefully in a disciplinary context; and critique output for accuracy, bias, context, and relevance.
Advanced Courses: Application.
Which upper-level courses will allow students to apply AI to known, discipline-specific workflows based on real scenarios?
Capstone and Clinical Courses Transfer.
Capstone and clinical courses are ideal spaces in which students can learn to apply AI to unfamiliar, real-world problems; track privacy and safety; and document AI use.
Assignment-level expectations
Clearly communicate to students when AI is off, assistive, or expected – and why.

Let's Stay in Touch.

The University Innovation team supports faculty, staff, and students with AI adoption and workflow questions.

Support is available 8:00 AM until 5:00 PM, Monday through Friday.

Kimberly Conner, J.D. | Director of University Innovation

For more information about our department and programs, please email us at universityinnovation@lamar.edu.