Use these curated resources to make intentional decisions about AI in courses, assignments, course policies, student learning, and privacy.
Start Here: LMU Guidance and Tools
Begin with LMU guidance on academic honesty, available tools, data security, privacy, and training.
- LMU Academic Honesty and AI Guidance - Review LMU policy, faculty and student FAQs, procedures for handling evidence, and the student guide to AI and academic honesty.
- LMU ITS: AI Tools & Services - Review AI tools available at LMU, including supported tools and access considerations.
- LMU ITS: Data Security and Privacy - Review what should not be entered into AI systems, including student, personnel, confidential, and proprietary information.
- LMU ITS: AI Training Resources - Find LMU-supported training options and related learning resources.
Before requiring students to use an AI tool: Consider account requirements, cost, accessibility, privacy, and a reasonable alternative. Do not require students to upload protected or confidential information.
Course Policies and Student Communication
Use these resources to clarify when AI may be used, when it should not be used, how students should disclose AI use, and how course expectations connect to learning goals.
- Georgetown CNDLS: Developing Course Policies - Examples of AI policy approaches and adaptable language. These are external examples, not LMU policy.
- The Scholarly Teacher: Strategies for Navigating Ethical AI Use in College Courses - Practical approaches for setting expectations and asking students to document AI use.
AI-Aware Course, Assignment, and Assessment Design
Use these resources to design courses, assignments, and assessments that either limit AI use intentionally or integrate AI in ways that support learning.
- AI-Free and AI-Integrated Teaching: Practical Options and Strategies - LMU resource with practical options for deciding when to restrict, permit, or integrate AI.
- AI Assessment Scale - Framework for communicating permitted levels of AI use in assignments and assessments.
- Chronicle of Higher Ed: Make AI Part of the Assignment - Guide to an AI-assisted learning template that asks students to reflect on and document AI use.
- Quality Matters: Strategic AI Integration - Research-supported recommendations for integrating AI into course design with attention to learning outcomes.
AI Literacy, Ethics, and Student Learning
Use these resources to help students understand AI's strengths, limitations, risks, and ethical responsibilities.
- Student Guide to Artificial Intelligence - Current student-facing guidance on using AI academically, professionally, and ethically, with accompanying educator materials.
- EDUCAUSE: AI Literacy in Teaching and Learning - Higher-ed framework for technical understanding, evaluation, practical application, and ethical considerations.
- Every Learner Everywhere: Artificial Intelligence for Student Success - Student-centered resources on responsible AI use, equitable access, accessibility, and student success.
- UNESCO: Guidance for Generative AI in Education and Research - Broader human-centered guidance on benefits, risks, privacy, inclusion, and ethical use.
Selected LMU Faculty Examples
Selected examples from LMU faculty:
- Co-Constructed AI Policies in the Classroom - Elizabeth Drummond (History) on involving students in discussing and revising course expectations around AI.
- Academic & Scholarly Use of Gen AI - LMU Computer Science faculty resource on academic and scholarly AI use.