Use this guide to find AI strategies and prompts that support tasks across the course development process. Think of it as a get-started kit for bringing AI into your own course design. From brainstorming to assessment and grading, this guide provides prompts to support your workflow.
Tips for using this guide:
- Skim the guardrails below first. It defines where AI belongs (and doesn’t) in course design.
- Jump to any strategy for copy-and-paste AI prompts. Replace bracketed text (e.g., [course title]) with your own details.
- Check the “Further reading” list at the end of each strategy when you want to go deeper on a topic.
Guardrails for AI use
AI is best used as an assistant rather than a substitute for human expertise. Students consistently report that they value instructor presence, human expertise, and authentic connection. Use this framework to decide when to use AI and when not to.
Faculty own
- What students should learn
- The course arc and emphasis
- Academic standards and rigor
- Relationships with learners
AI assists
- Generating ideas
- Iterating on existing work
- Repetitive or organizational tasks
- Speeding up first drafts
Think of AI as a capable graduate research assistant: useful for gathering information, generating ideas, and producing preliminary work, but not the one who sets the direction or makes the final call.
When using AI, keep in mind
- Hallucinations still happen. AI can confidently invent facts, citations, or examples. Verify anything you didn’t already know to be true.
- AI is often overly agreeable. Asking “Is this good?” usually gets a yes. Ask it to critique, find weaknesses, or argue against your assumptions instead.
- AI drifts toward the generic. It’s trained on aggregate data and defaults to the average response. Use your disciplinary expertise to identify and reject generic output.
- Context is the biggest blind spot. AI doesn’t know your institution’s policies, accreditation standards, or curriculum map unless you explicitly provide all of that information, and even then, it often misses the full context.
- Guard student data and privacy. Never upload student records, grades, or other identifiable information into consumer AI tools — doing so can violate FERPA. Use only institution-approved, enterprise-licensed platforms, and check any other tool’s data-retention and training policies first.
- Use AI to spark thinking rather than replace it. The moment AI output starts substituting for your creativity rather than feeding it, pull back.
- Assume uploads aren’t private by default. Many AI tools may use your inputs to train future models unless you disable that setting. Check and adjust each tool’s data-use or privacy settings before uploading anything sensitive.
Practical AI workflows for course design
AI can generate a wide field of possibilities for you to accept or discard based on your own expertise. It is especially useful for expanding the range of possibilities you consider and helping you move past a blank page. Ask for volume rather than depth, then apply your disciplinary judgment to reject any outputs that are generic or miss the mark.
AI does well
- Generating a high volume of ideas fast, so you’re choosing from options instead of starting from a blank page
- Surfacing ideas or angles you might not have reached alone
- Producing examples, analogies, and scenarios that make abstract concepts concrete
Watch for
- A good first idea can anchor your thinking. Ask for a batch of options before letting AI fully develop any one of them
- AI has no vision for your course. Weigh ideas against your own goals, not just their polish
- Treat AI-generated examples and scenarios as starting points rather than finished products
Template: Brainstorming
Act as an instructional design partner.
I teach [course title] to [student population].
Generate 10 ideas for [assignment/activity/example/discussion] that help students achieve the following learning outcome(s): [list learning outcome(s)].
Prioritize ideas that are engaging, practical, appropriate for online learning, and connected to authentic professional practice.
Further reading on AI-assisted brainstorming
AI can help you organize the broad structure of a course: its sequence, learning objectives, alignment, and so forth. This high-level view can reveal opportunities to scaffold difficult work, revisit important concepts, or distribute student workload more intentionally. AI will sometimes recommend revisions that amount to reorganization rather than improvement, so think carefully about any proposed changes before implementing them.
AI does well
- Spotting structural issues, like a project assigned before students have the prerequisite skills, or modules that overlap in content
- Drafting and sharpening learning objectives
- Checking alignment across objectives, activities, and assessments
Watch for
- Big structural rewrites can sound plausible without being better. Evaluate before adopting
- Ask: does this improve learning, or just reorganize it?
- Use AI to surface patterns, but keep planning decisions with faculty (and instructional designers)
Template: Learning objectives
Act as an instructional design partner.
Help me write learning objectives for my [level of instruction] [discipline] course, [course title].
Course description: [insert course description]
My goals: [what students should know, do, or value by course end]
Align with these program learning objectives: [list objectives]
Objectives should be clear, measurable, and appropriate for the course level.
Template: Aligning objectives, activities, and assessments
Act as an instructional design partner.
Review the learning objectives, learning activities, and assessments below for constructive alignment.
Learning objectives: [list objectives]
Learning activities: [list activities]
Assessments: [list assessments]
For each learning objective, identify which activities prepare students to achieve it and which assessments measure it. Flag objectives that are insufficiently taught or assessed. Flag activities or assessments that do not clearly support an objective.
AI can provide a second set of eyes after you have drafted a course or module, helping you identify unclear directions, alignment gaps, inconsistent terminology, accessibility concerns, or assumptions caused by expert blind spot. It’s most useful when you ask focused questions from a student perspective, such as where expectations may be ambiguous or what prerequisite knowledge appears to be missing. Because AI doesn’t know why you made a given design choice unless you explain it, evaluate its feedback before revising. Use AI review as a quality-control pass, with your judgment or an instructional designer’s expertise as the final word on what changes.
AI does well
- Spotting inconsistent terminology, confusing instructions, or uneven workload across modules
- Surfacing where students may disengage or miss an activity’s real-world relevance
- Flagging assessments that are vulnerable to being completed with AI
Watch for
- AI doesn’t know the full details of your reasoning and may mistakenly flag issues due to lack of context
- Ask whether a critique genuinely improves the learning experience or just reflects a different preference
- Humans should remain responsible for context-dependent judgment
Template: AI as an instructional designer-lite
Act as an instructional designer. Review the draft below and identify anything that may leave students unsure about what to do, how to do it, or how their work will be evaluated. For each issue, briefly explain the concern and recommend a specific revision.
Course draft: [insert course content]
Template: Evaluating the student experience
Evaluate the following course as an instructional design partner: [insert course map, outline, or draft].
Where are students likely to become disengaged?
Which activities clearly connect to students' future careers, and which may feel disconnected from real-world application?
Template: Identifying AI vulnerabilities in assessment design
Act as an instructional design partner. You are evaluating this assessment for AI vulnerability: [insert assessment]
Identify any aspects that a student could complete with minimal original thinking by using AI. Suggest revisions that encourage academic integrity while preserving the learning outcomes.
Further reading on AI-assisted course review
AI can help draft announcements, module introductions, weekly summaries, reminders, FAQs, and other routine course communications. This support can make it easier to communicate consistently and maintain a regular instructor presence in an online course. Avoid fully automating communications and maintain a human-centric approach, especially when responding to student needs or sensitive situations where personal knowledge, empathy, and authentic instructor engagement are extremely important.
AI does well
- Drafting first versions of announcements, intros, and wrap-ups fast
- Leaving placeholders for your own stories and observations
- Keeping recurring communications organized and consistent
Watch for
- Over-polished, uniform AI phrasing erodes instructor presence
- Fully automated or inauthentic communication can hurt trust
- Make sure students are primarily encountering you rather than AI
Template: Drafting announcements
Act as a professor who excels at maximizing student engagement. Draft a course announcement introducing this week's topic: [insert this week's topic]. Write in a warm, encouraging tone for [student population]. Briefly explain why the topic matters, connect it to last week's topic: [insert last week's topic], preview this week's activities: [insert activities], and encourage students to contact me with questions. Leave placeholders where I can personalize the message.
Template: Drafting module introductions
Act as a professor who excels at maximizing student engagement. Draft a brief introduction for a module covering [insert topic]. Explain why the topic matters, connect it to [insert previous learning], identify one real-world application, and prepare students for the work they'll complete this week. Keep the tone conversational and motivating.
Template: Video/lecture script
Act as a professor who excels at maximizing student engagement. Write a [length] video script for [audience] introducing [topic]. Start with a strong opening that makes learning feel relevant. Highlight [3–5 key ideas]. The tone should be [tone]. Keep it clear, engaging, and easy to follow.
Template: Drafting assignment context and instructions
Act as an instructional design partner. Create student-facing context and instructions for this assignment: [briefly describe the task]
The assignment is aligned with the following learning objective(s): [list learning objective(s)].
Include:
why the assignment matters
its connection to the course or module
step-by-step instructions
required deliverables
important constraints or expectations
Write in a clear, supportive, professional tone. Do not add unstated requirements. Flag any information you need from me before making assumptions.
Template: Drafting weekly wrap-ups and conclusions
Act as a professor who excels at maximizing student engagement. Draft a brief weekly summary highlighting the major concepts from this module: [list key concepts]. Reinforce the key takeaways, connect them to next week's topic: [insert topic], and end with an encouraging message. Leave room for instructor-specific observations.
Further reading on AI-assisted course communication
AI can help you develop or revise assessments that align with learning objectives and give students meaningful ways to demonstrate what they know and can do. It can generate authentic scenarios, suggest formative practice, identify opportunities to capture student reasoning, or examine how easily an assignment could be completed through superficial AI use. Check that the final assessment is appropriately challenging, feasible in an online environment, and focused on evidence of student learning.
AI does well
- Generating a pool of quiz items, prompts, or scenarios that you can evaluate
- Drafting assignment details and deliverables quickly
- Building realistic, professionally grounded scenarios for authentic assessment
Watch for
- Always start from the learning outcome, not the topic alone
- Avoid tasks completable through simple information retrieval
- Be wary of generic AI outputs. Prompt and revise for authenticity and specificity
Template: Designing quizzes
Act as a professor who excels at crafting assessments.
Create 10 quiz questions aligned with the following learning outcome(s): [list outcome(s)].
Include a mix of recall, application, and analysis questions. For each item, explain what knowledge or skill it is intended to measure.
Template: Drafting discussion prompts
Act as a professor who excels at crafting assessments.
Draft five discussion prompts aligned with the following learning outcome(s): [list outcome(s)].
Prioritize prompts that encourage application, multiple perspectives, and professional judgment rather than summary. All prompts should have multiple valid responses and be conducive to dialogue.
Template: Individual assignment prompts
Act as a professor who excels at crafting assessments.
Draft an assignment aligned with the following learning outcome(s): [list outcome(s)].
Include clear instructions, evaluation criteria, and opportunities for practical application. Avoid assignments that can be completed primarily through information retrieval.
Template: Designing authentic assessments
Act as a professor who excels at crafting assessments.
Design a project that allows students to demonstrate the following learning outcome(s): [list outcome(s)].
Demonstration should occur through an authentic workplace or real-world application.
The project should resemble professional practice, require judgment, and encourage students to apply course concepts in realistic situations.
AI can support grading design by helping you articulate evaluation criteria, draft rubric language, distinguish performance levels, and anticipate common variations in student work. Follow institutional standards and be careful not to allow AI to set standards independently. Review AI outputs for unintended bias, wordy explanations, excessive rigidity, or criteria that prioritize polish over demonstration of learning.
AI does well
- Organizing performance criteria into clear achievement levels
- Producing rubrics quickly from outcomes and task details
- Mapping grading to learning outcomes
Watch for
- Ask AI to justify why each criterion belongs to check for weak alignment
- AI can be verbose, but students benefit from concise, digestible directions
- Students react differently to “AI helped organize this rubric” versus “AI is grading me.” Keep it visible that faculty make the evaluation calls
Template: Creating rubrics
Act as an instructional design partner.
Create an analytic rubric for the following assignment and learning outcome(s): [list assignment details and learning outcome(s)].
Include clear performance criteria, four performance levels, and descriptors that distinguish between levels of achievement. Explain how each criterion aligns with the stated learning outcomes.
Further reading on AI-assisted grading design
The bottom line
AI provides efficiency, iteration, and support. Faculty provide expertise, judgment, and relationships. When used well, AI assistance can save time that you can reinvest into what students care about: being challenged, encouraged, and genuinely known by their instructor.
