AI Showcase Examples
In this AI assignment showcase, you will find examples of assignments that innovatively integrate Generative AI in the following ways:
- Provide opportunities for students to evaluate the limitations and capabilities of Generative AI tools
- Engage students in discussions about ethical AI use
- Perform a specific task using Generative AI within various fields
- Incorporate a specialized AI tool to carry out a course activity
- Create a custom course AI agent that simulates an interaction students may have in their future careers
The assignments are drawn from across disciplines, including mathematics, engineering, writing, nutrition, counseling, and business.
When looking over these assignments, some areas to take note of are how the assignment offers guidance to students on the use of AI (prompt engineering, citing AI, missteps to avoid etc.), how the use of AI is assessed, and how the students are prompted to reflect on and analyze their use of AI within the context of their disciplines and learning. These are key areas to consider when designing and implementing an AI-based assignment.
If you have an example of an assignment that incorporates Generative AI in an innovative way and would like to include it in this showcase, please send a copy of the assignment to Ken Silvestri, CFE Instructional Designer at kenneth.silvestri@montana.edu. Ken is also available for consultations on designing assignments or activities that incorporate the use of AI and on the creation of custom course AI agents.
Prompting & Evaluating AI for Math Problem Solving
This assignment has students use and compare multiple generative AI tools for solving math problems, focusing on how prompting affects accuracy, reasoning, and reliability while critically evaluating limitations and ethical use.
Instructor: Dr. Breshine Cummins
Course: M441
View assignments materials here
AI in Engineering Analysis: Limitations, Ethics and Learning
This assignment integrates generative AI as a support tool for code development, planning, and reflection, while machine learning models are trained on experimental heat-exchanger data to complement and critically compare traditional NTU-based engineering analysis through validation, limitations, and ethical use.
Instructor: Dr. Ryan Anderson
Course: ECHM 443
AI-Assisted Design Project in Graphic Design
In this semester-long project, students integrate Generative AI throughout a human-centered design process--using it for research synthesis, ideation, visual exploration, and interactive prototyping--while critically documenting, citing, and refining AI outputs to ensure ethical use and human-driven creative decision-making.
Instructor: Dr. William Culpepper
Course: GDSN377
Using AI to Practice Motivational Interviewing Skills
This assignment uses an AI-powered simulated client to let students practice motivational interviewing in a realistic, low-stakes counseling conversation, receive immediate, structured feedback on their language choices, and reflect on how AI can support skill development and metacognition in professional training contexts.
Instructor: Dr. Ed Dunbar
Discipline: Counseling
Using AI to Draft Feedback
In this assignment, students use an AI chatbot to critique the paragraph structure and transitions in their own draft, then revise their writing and reflect on how AI-supported feedback informed their decisions while preserving their authorial voice.
Instructor: Dr. Sarah Coletta-Flynn
Discipline: English
Making AI a Formal Part of the Writing Process
This assignment intentionally integrates AI at multiple stages of the writing process—brainstorming, drafting, revising, and reflecting—to teach students ethical, transparent AI use while preserving authorship, voice, and critical decision-making
Instructor: Kyndra Campbell
Discipline: Writing and Developmental Humanities
Using Generative AI for Project Ideation and Proposal Development
This team‑based EELE 308 lab project uses generative AI (via MSU’s CatChat or other LLMs) at the front end of the assignment to support project ideation and proposal development, while students retain responsibility for all technical design, implementation, integration, and assessment
Instructor: Dr. Bradley Whitaker
Course: EELE 308
AI Simulated Patients for Experiential Learning in Nutrition Education
This project uses generative AI to simulate realistic patient and preceptor interactions, allowing nutrition students to practice interviewing, assessment, and clinical reasoning in a low‑stakes, experiential learning environment before clinical rotations.
Instructor: Jessy Griffel
Discipline: Nutrition
AI Facilitated Online Discussion Assignments
This assignment uses a free AI‑mediated chat platform called SwayBeta.AI to pair students with peers holding different viewpoints and guide them through a structured, professional online discussion that emphasizes active listening, respectful dialogue, and accurate understanding of opposing perspectives.
Instructor: Desiree Dalke
Course: AHMS 295
Low Stakes Global Business Context Presentation
This low‑stakes presentation assignment integrates AI as a transparent research and organization aid, allowing students to use AI to generate ideas and structure information while requiring them to critically evaluate outputs, verify accuracy, reflect on AI use, and retain full ownership of the final communication
Instructor: Marina Calabrese
Course: BGMT 205
Advocacy Plan for School Library
This assignment has students create an advocacy plan for a school library by writing a SMARTIE goal tied to an ethical issue, analyzing context and audiences, developing talking points and allies, then uses an AI chatbot to role-play their advocacy “ask” and refine it based on the AI feedback.
Instructor: Dr. Deborah Rinio
Course: EDCI 550