Resources

Teaching & Learning

Resources for faculty, instructors, and students to integrate AI responsibly into teaching, learning, and research across all University of Maine System campuses.

System Guidance

Faculty Guidance

The UMaine Generative AI Teaching and Learning Guidelines (March 2024) provide the primary framework for faculty. Key principle: faculty retain full autonomy to set their own AI use level for each course, from complete prohibition to required use.

Best Practices

Include a clear AI use statement in every syllabus
Specify which AI tools are permitted and for what purposes
Design assignments that leverage AI as a learning tool, not a shortcut
Teach students to critically evaluate AI outputs
Model responsible AI use in your own teaching practice
Consult CITL for instructional design support

AI Detection Tools Advisory

UMS does not officially endorse AI detection tools (e.g., Turnitin’s AI detection). These tools have documented accuracy issues and can produce false positives, particularly for non-native English speakers. Faculty are encouraged to focus on assignment design that makes AI misuse less advantageous rather than relying on detection.

Assignment Design & Prompt Library

Reusable prompt templates for faculty to integrate AI into coursework. Each template promotes critical thinking and responsible AI use.

Critical Thinking

Any discipline

Socratic Questioning Exercise

I’m going to share a student essay with you. Instead of providing feedback directly, generate a series of 5-7 Socratic questions that will help the student identify weaknesses in their argument, unsupported claims, and logical gaps. Focus on questions that promote deeper analysis rather than surface-level corrections.

Research

Research methods

Literature Review Scaffold

Help me create a structured literature review outline for [topic]. Organize the existing research into thematic categories, identify gaps in the current literature, and suggest how my research question fits within the existing scholarly conversation. Note: I will verify all citations independently.

Assessment

Any discipline

Rubric Generator

Create a detailed assessment rubric for [assignment type] in [course]. Include 4-5 criteria with descriptions for Exemplary, Proficient, Developing, and Beginning levels. Align criteria with the following learning outcomes: [list outcomes]. Include specific, observable indicators for each level.

Writing

Writing-intensive courses

Peer Review Simulation

Act as a peer reviewer for this [type of writing]. Provide constructive feedback organized into three categories: (1) Strengths — what works well, (2) Areas for Development — specific suggestions for improvement, (3) Questions — things that are unclear or need elaboration. Be specific and cite examples from the text.

STEM

STEM courses

Problem Set Variation Generator

Based on this [math/science] problem, generate 3 variations at increasing difficulty levels. For each variation: (1) modify the context while keeping the core concept, (2) provide the solution approach (not the answer), (3) identify the specific skill being tested. Ensure problems are original and not copied from existing textbooks.

Discussion

Any discipline

Discussion Prompt Designer

Design 3 discussion prompts for [topic] that require students to engage with AI as part of the discussion. Each prompt should: (1) ask students to generate an AI response to a question, (2) critically evaluate the AI’s response for accuracy, bias, and completeness, (3) contribute their own analysis that goes beyond what the AI provided.

Syllabus Statements

Copy-and-paste syllabus templates for each of the six AI use levels. Customize the bracketed sections for your specific course.

Level 1 — Forbidden

Forbidden

The use of generative AI tools (such as ChatGPT, Gemini, Claude, or similar) is not permitted in this course. All work submitted must be entirely your own. Use of AI-generated content will be treated as a violation of the Academic Integrity Policy (Board Section 314).

Level 2 — Restricted

Restricted

Generative AI tools may only be used for [specific tasks, e.g., brainstorming, grammar checking]. All other uses are prohibited. You must disclose any AI assistance and describe how it was used. Unauthorized use will be treated as a violation of the Academic Integrity Policy.

Level 3 — Disclosure Required

Disclosure Required

You may use generative AI tools in this course, but you must disclose all AI use. Include a citation for each instance: the service used, version, date, text of your prompt, and a link to the service. Failure to disclose AI use constitutes plagiarism under the Academic Integrity Policy.

Level 4 — Encouraged

Encouraged

The use of generative AI tools is encouraged in this course as a learning aid. You are expected to critically evaluate AI outputs and cite all AI assistance. Remember: AI tools can produce inaccurate or biased content. You are responsible for the accuracy and integrity of all submitted work.

Level 5 — Integrated

Integrated

Generative AI is integrated into this course’s learning design. Specific assignments will require AI use as part of the learning process. You will learn to craft effective prompts, evaluate AI outputs critically, and understand AI’s capabilities and limitations. All AI use must be documented.

Level 6 — Required

Required

This course requires the use of generative AI tools as part of your coursework. You will be provided access to [specific tool(s)]. Assignments are designed to develop your AI literacy and critical evaluation skills. If you have concerns about AI tool access, please contact the instructor for accommodations.

Student Resources

Using AI Ethically

Always check your syllabus for your instructor’s AI policy. When in doubt, ask. Cite all AI use. Remember: you are responsible for the accuracy of everything you submit.

Effective AI Use

Use AI as a thinking partner, not a replacement for thinking. Ask it to explain concepts, generate practice problems, or help you brainstorm — then build on its output with your own analysis.

Critical Evaluation

AI can be wrong, biased, or outdated. Always verify facts from AI against reliable sources. Learn to recognize hallucinations and understand AI’s limitations.

The USM Student AI Guide

USM’s guide offers practical advice: “If you wouldn’t post it on Reddit anonymously, don’t put it in an AI tool.” The guide covers privacy, citation, and responsible use in clear, student-friendly language.

How to Cite AI

Footnote: “ChatGPT (GPT-4), March 2026. Prompt: ‘Explain the significance of the Treaty of Westphalia.’ Link: chat.openai.com”

Blanket: “Portions of the text and ideas in this document were created or edited using ChatGPT (GPT-4).”

AI 101 & Glossary

Foundational concepts and terminology for understanding AI in the university context.

Computer systems designed to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, and language understanding.

AI systems that can create new content — text, images, code, audio — based on patterns learned from training data. Examples include ChatGPT, Claude, and Gemini.

A type of AI trained on vast amounts of text data that can understand and generate human-like text. The foundation of most generative AI chatbots.

The input text or instructions you provide to an AI system. The quality and specificity of your prompt significantly affects the quality of the output.

When an AI generates information that sounds plausible but is factually incorrect, fabricated, or misleading. Always verify AI-generated facts from authoritative sources.

The basic unit of text that AI models process. Roughly equivalent to a word or word fragment. Models have token limits that constrain how much text they can process at once.

The process of further training a pre-trained AI model on a specific dataset to improve its performance on particular tasks or domains.

A technique that combines AI generation with information retrieval, allowing the model to access external knowledge bases to produce more accurate and up-to-date responses.

Systematic errors in AI outputs that reflect and can amplify societal biases present in training data. Can affect fairness, accuracy, and representation across different groups.

The practice of designing and refining prompts to get better, more accurate, and more useful responses from AI systems.