Practical, ready-to-use assignment ideas from higher education professionals, organized by assignment type and yours to use, remix, or build on.
Generative AI (GenAI) is rapidly evolving, and teaching practices will continue to evolve alongside it. Included here are professional and scholarly resources that illustrate practical uses of GenAI in course assignments, activities, and lectures.
Curated Assignment Ideas
We have carefully selected these assignments for you to use, adapt, or inspire new ideas.
Critically Analyze AI Outputs Using an AI Chatbot
A ready-to-use prompt set that guides students through evaluating AI-generated responses. Learners paste prompts into a chatbot to assess accuracy, bias, logic, and completeness, then reflect on evidence and reasoning to strengthen critical analysis and AI literacy.
Generative AI Critical Analysis Activities
A practical collection of classroom activities that build students’ ability to evaluate and improve GenAI outputs. Students compare multiple responses, score work with rubrics, contrast AI vs. human writing, fact-check claims, revise drafts, and explain their reasoning in writing or discussion.
A Case Study in Mindfully Integrating AI Tools into Writing Classes
A research-based case study examining how AI tools can be integrated into writing instruction with intention. Highlights mindful course design, student learning considerations, and classroom practices that support reflection, transparency, and effective use of AI in writing activities.
A study of social annotation in a flipped physics course showing how collaborative commenting can improve pre-class reading engagement. Students annotate texts together, respond to peers, and arrive better prepared for discussion—supporting comprehension, participation, and active learning.
Generative AI in First-Year Writing: Affordances, Limitations, and a Framework for the Future
An analysis of how GenAI intersects with first-year writing, emphasizing both opportunities and constraints. Offers a forward-looking framework that connects AI use to the writing process, student learning goals, and structured reflection to support metacognition and responsible practice.
Setting Generative AI Expectations in Writing Assignment Guidelines
A sample guideline and mini paper framework that helps clarify when and how students may use GenAI during different stages of a writing assignment. Designed to reduce confusion by making expectations explicit and supporting consistent, teachable standards for AI-assisted writing.
Do Something Impossible with AI
A multi-part assignment that uses GenAI to help students attempt a challenging persuasive task. Students propose an approach, document process decisions, present outcomes, and design a rubric—emphasizing argument strategy, transparency, and critical reflection on AI’s role.
Debate Preparation with AI on the Sapir-Whorf Hypothesis
An activity that supports debate preparation using generative AI as a research and organization aid. Students gather evidence, refine claims, structure arguments, and reflect on the strengths and limits of AI-generated support while building debate readiness and critical judgment.
Explore, Identify, and Align: Utilizing Generative AI as a Career Coach
A scholarly article exploring how GenAI can function as a career-coaching tool. Focuses on helping learners explore options, clarify goals, and align skills with opportunities while emphasizing thoughtful prompts, evaluation of advice quality, and instructor guidance for responsible use.
Assigning AI: Seven Approaches for Students, with Prompts
A widely cited framework describing seven ways students can work with AI (e.g., tutor, coach, teammate, simulator). Includes prompts and assignment ideas that help instructors design structured, purposeful AI interactions while reinforcing learning goals and reflective practice.
Guidelines for the Evolving Role of GenAI in Intro Programming Based on Emerging Practice
Guidance for incorporating GenAI into introductory programming responsibly. Discusses emerging practices, potential benefits and risks, and instructional strategies for helping students use tools like code assistants without undermining skill development, academic integrity, or conceptual understanding.
Beyond the Hype: Trends in GenAI Research, Teaching Practices, and Tools
A comprehensive review of GenAI in computing education, synthesizing research and classroom practices. Covers common tools, instructional approaches, student impacts, and open questions, helping instructors move beyond hype toward evidence-informed decisions and realistic implementation strategies.
Data Visualization (with and without AI)
An in-class activity that asks students to compare AI-generated code and human-written code for creating visualizations. Students build a chart (including an advanced option), evaluate correctness and efficiency, and discuss when AI accelerates work—and when writing code directly is better.
Appreciation for the Human Perspective
A structured writing-and-revision assignment where students draft an essay, generate an AI version from the same prompt, and analyze differences. Students reflect on voice, reasoning, and quality, strengthening critical evaluation skills and awareness of authorship and AI limitations.
Writing Methodology (with AI) in French
A revision-focused activity in which students use generative AI feedback to improve French-language writing. Emphasizes iterative editing, interpreting feedback critically, and making purposeful revisions while reinforcing language-learning goals and responsible use of AI support.
A set of peer-review mini-games that use AI to prompt revision and discussion. Activities (e.g., Devil’s Advocate, Sentence Surgery, Elevator Pitch) help students critique drafts, test clarity and persuasion, and reflect with partners on what AI suggestions improve—or weaken.
AI’s Impact on the Environment: Classroom Guide + Discussion Questions
A discussion guide that helps students examine the environmental costs associated with AI, including energy and water use. Provides a structured way to engage with research sources, weigh tradeoffs, and connect AI adoption to sustainability, ethics, and responsible decision-making.
Examples of Student Activities for Building Ethical AI Literacy
A set of classroom-ready activities focused on ethical AI literacy, including discussions and individual assignments on AI-generated writing, bias, correlation vs. causation, and decision-making. Includes outcomes and prompts that help students practice ethical reasoning and critical evaluation.
How to Use AI Responsibly EVERY Time
A simple, repeatable framework for responsible AI use built around four actions: evaluate, verify, engage, and revise. Helps students slow down, check accuracy, reflect on implications, and improve outputs—positioning the user’s judgment as essential to safe, effective AI use.
Uncovering Deepfakes: Classroom Guide + Discussion Questions
A classroom guide designed to build student awareness of deepfakes and the ethics of synthetic media. Includes discussion questions that address trust, misinformation, consent, and impact, helping students develop habits for evaluating authenticity and communicating responsibly.
Instructors as Innovators: A Future-Focused Approach to AI Learning Opportunities, with Prompts
An instructor-facing resource that frames AI as a partner for experimentation and co-creation in learning design. Provides practical prompts and activity ideas that help students generate, critique, and refine work while emphasizing reflection, transparency, and alignment with course outcomes.
Enhancing Information Literacy through Generative AI in the Library Classroom
An article describing how GenAI can be used to strengthen information literacy instruction. Focuses on teaching students to interrogate outputs, verify claims, and practice source-based evaluation, positioning AI as a catalyst for deeper inquiry rather than an authority.
Creative Use of OpenAI in Education: Case Studies from Game Development
A set of case studies showing how GenAI can support learning through creative, project-based work in game development contexts. Highlights practical classroom use, student experimentation, and reflective practice—useful for designing activities that connect AI tools to metacognitive learning goals.
AI-Integrated Homework Assignments
A trio of homework designs that use AI to support study planning, case critique, and concept review. Activities emphasize metacognition, evaluating AI-generated content, and simplifying complex ideas, prompting students to reflect on how they learn and what supports understanding.
Future of Writing in the Disciplines and Professions
A discipline-focused white paper exploring how GenAI can support writing while keeping students engaged in higher-order thinking. Offers perspectives on using AI to enhance drafting and revision, with attention to critical thinking, evaluation, and maintaining meaningful cognitive effort.
A conference paper describing how GenAI can be used to build critical thinking in introductory programming. Students evaluate AI-generated code, identify errors and assumptions, and reflect on tool limits—strengthening debugging skills, reasoning, and responsible use of coding assistants.
Can You Spot the AI? Incorporating GenAI into Technical Writing Assignments
A short paper outlining an approach to integrating GenAI into technical writing coursework by having students detect and analyze AI-generated text. Supports critical reading, genre awareness, and revision by focusing on accuracy, clarity, and the identifiable patterns of AI writing.
Strategies to Adjust Assignments
Continually articulate why students are doing assignments. Support students being able to explain the relationship between AI and the assignment and how this supports learning goals for the course and life. This is essential for student buy-in and motivation.
The Writing Across the Curriculum team suggests the following strategies:
Strategy
Ask students to describe and reflect on their own processes of learning.
Ask yourself
How can I encourage students to document their thinking and increase learning how to learn and problem solve?
Strategy
Plan for transparently assessing assignments and the learning process.
Ask yourself
How can I incorporate different types of feedback? How are they prompted to get feedback from AI (if applicable)?
Strategy
Assign projects in which students apply personal or professional experiences to a specific, local context.
Ask yourself
How can this assignment be made specific, local, and related to recent events? How can AI be integrated to boost students’ AI literacy skills?
Strategy
Guide the process of research, including how to incorporate and cite a wide variety of academic and popular sources.
Ask yourself
Why do I ask students to research and what sources are valuable? What advice and resources are available from librarians?
Strategy
Think about leveraging assignment modality options such as visual, multimedia, audio, or collaborative assignments.
Ask yourself
Why am I assigning this assessment in this mode? What parameters do I need to set? What do I want students to learn from the process and the product?
Strategy
Understand what bias, misinformation, and hallucinations are and where they might occur in your assignments.
Ask yourself
How am I equipping students to think critically about the information they are receiving? What guidance do students have for determining whether the information is biased, inappropriate, or wrong?
Strategy
With students, review and talk about generative AI use for each assignment/assessment.
Ask yourself and your students
How can genAI be used? Will use benefit learning or not? Should AI be used?
Customized Consultations
Contact us if you are Interested in working with someone to create and integrate a GenAI assignment.
Adele Leon
Senior Instructional Designer
adele@arizona.edu