AI Prompt Guide for SMEs

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Generative AI tools like Claude.ai, ChatGPT, and Gemini can significantly enhance the course development process when used as collaborative partners that support human expertise rather than replace it. At CCO, we embrace a “Human-in-the-Loop” approach where AI assists with drafting and organizing content while SMEs and instructional designers ensure accuracy, rigor, and alignment with learning outcomes.

When using AI tools, remember that AI outputs should always be treated as drafts requiring rigorous subject matter review. No AI model can reliably guarantee factual accuracy or up-to-date information, particularly in fields where disciplinary knowledge evolves rapidly. Your subject matter expertise remains the critical safeguard against these limitations. This toolkit provides strategies for leveraging AI effectively throughout the course development process.

Prompt Engineering Essentials

Effective prompts follow these principles:

  • Be specific about your goals and context – The more clearly you define what you want, the better the AI can focus its response. Include the course level (undergraduate/graduate), modality (online/asynchronous), and expected depth of knowledge.
  • Assign a role to the AI – Asking the AI to “assume a role” (e.g., “learning designer,” “subject matter expert,” “marketing instructor”) helps align the tone, level of detail, and perspective to better fit academic needs. Specifying a role primes the AI to draw from relevant patterns and frameworks. When assigning the role, start by asking the AI, “If you were an [SME in marketing] what knowledge, skills and abilities would you have?” Then, ask the AI to use these KSAs to help with the task.
  • Specify format, length, and tone requirements – Clarify whether you want a bulleted list, narrative paragraph, module overview, assignment description, etc. Setting expectations early reduces unnecessary revision.
  • Provide background information – Whenever possible, include relevant context, such as a course description, learning outcomes, weekly topics, or existing materials. The more background the AI has, the more accurately it can tailor its response.
  • Break complex tasks into smaller prompts – For multi-step content (e.g., developing a project description and rubrics), it is more effective to scaffold the AI’s work by prompting one component at a time rather than asking for everything at once.
  • Use AI tools to validate each other’s outputs – Leverage multiple AI platforms as quality control mechanisms. Ask one AI to review, critique, or enhance content generated by another. For example, have Claude evaluate the accuracy of assessment questions created by ChatGPT, or ask Gemini to suggest improvements to learning objectives drafted by another tool.
  • Iterate through revisions – AI-generated drafts often improve significantly when refined through multiple rounds. Request clarifications, expansions, or alternative phrasing rather than starting over entirely.
  • Cross-pollinate between tools – Use outputs from one AI tool to fuel work in another. For example, generating a case study draft in one platform and using another to create discussion questions based on it. This layered approach can deepen quality and creativity.

AI Prompts for Course Planning

The planning phase includes developing the Course Design Document (CDD). In the CDD for the course you’re developing, the Program Director (PD) will include a list of the course learning outcomes that must be met throughout the course. The PD may also include a weekly topical outline to help guide the design process.

Course Design Document (CDD) Planning

Sample Prompt for Weekly Outline: 

Assume the role of a learning designer. Create a 7-week draft course outline for an [undergrad/grad] online, asynchronous course on [SUBJECT].
For each week: Suggest a main topic and 2–3 logically sequenced subtopics appropriate for beginners. Ensure the weekly topics align with the course learning outcomes. Balance content scope with an expected weekly student workload of [17 hours for undergrad / 20 hours for grad], including all readings, assessments, and lesson activities
Write in a clear and academic tone, with a focus on instructional progression and coherence across the course.

To improve results, consider including:

  • Course Learning Outcomes (CLOs)
  • A course description
  • A weekly topical outline or anchor topics from the Program Director (if available)
  • Prerequisites or assumed prior knowledge
  • Targeted skills or knowledge areas to build over time
  • Whether the course is more conceptual, applied, or skills-based
  • Any required scaffolding (e.g., content dependencies, regulatory constraints, tool training)
  • Instructional preferences (e.g., case-based learning, project-driven, media-heavy)

Assessment Ideas

Note: Each week typically includes 1–2 assignments and 1 discussion as part of the assessments.

Assignments and discussions should be selected to balance student workload within the expected time commitment (17 hours/week for undergrad, 20 hours/week for grad).

Sample Prompt for Assessment Idea Suggestions: 

Provide 4–6 varied and authentic assessment ideas related to [TOPIC] for [undergrad/grad] students in an online, asynchronous [SUBJECT] course.
For each suggestion: Include a brief 2–3 sentence description of the task and a concise, bulleted list of assignment steps. Ensure each assessment aligns with at least one course learning objective (CLO).
Design tasks appropriate for a typical online course workload (17 hours per week for undergrad / 20 hours per week for grad), considering that students will balance assessments, readings, and lesson activities within this time frame.
Include a mix of assignment types (e.g., application tasks, projects, reflections).
At least one suggestion must be a discussion prompt that encourages critical thinking at the analysis and evaluation levels (Bloom's Taxonomy). The discussion prompt should engage students with course concepts and require application to real-world or hypothetical situations. Instruct students to post a thoughtful initial response and meaningfully reply to two peers. Avoid yes/no or purely factual questions.
Write all suggestions in a tone appropriate for college-level online instruction, ensuring academic rigor and realistic student workload expectations.

To improve results, consider including:

  • Course Learning Outcomes (CLOs)
  • Weekly topics or learning objectives from the Course Design Document (CDD)
  • Key lesson content or concepts students should apply
  • Prior knowledge or assumed student skill level
  • Real-world professional contexts or challenges relevant to the topic
  • Expected deliverable formats (e.g., short paper, infographic, case response, presentation)
  • Whether assignments should connect to a larger final project
  • Typical online course workload expectations (17 hours per week undergrad / 20 hours grad)
  • Any discipline-specific tone or style preferences (e.g., technical writing, reflective tone)

Weekly Learning Objectives

Bloom’s Taxonomy (revised 2001) provides a hierarchical framework for categorizing educational goals. When creating learning objectives, selecting appropriate verbs that align with the desired cognitive level helps ensure students engage in the right depth of thinking:

  • Remember (Knowledge): Recall facts and basic concepts
    Example verbs: define, list, recognize, recall, identify
  • Understand (Comprehension): Explain ideas or concepts
    Example verbs: explain, describe, classify, summarize, interpret
  • Apply (Application): Use information in new situations
    Example verbs: implement, execute, solve, demonstrate, use
  • Analyze (Analysis): Draw connections among ideas
    Example verbs: differentiate, organize, compare, contrast, examine
  • Evaluate (Evaluation): Justify a stance or decision
    Example verbs: critique, judge, defend, appraise, assess
  • Create (Synthesis): Produce new or original work
    Example verbs: design, construct, develop, formulate, author

For college-level courses, particularly at the upper undergraduate and graduate levels, aim to craft objectives that target the higher levels of Bloom’s Taxonomy (Apply, Analyze, Evaluate, Create) to promote deeper learning and critical thinking skills.

Sample Prompt for Weekly Learning Objectives: 

Generate 1–2 measurable learning objectives for each of the selected assessments.
Each learning objective should: Clearly describe what students will be able to do after completing the assessment. Use action verbs from Bloom's Taxonomy. Align directly with at least one Course Learning Outcome (CLO).
Write the objectives in clear, student-centered language, emphasizing observable skills or actions rather than knowledge recall.

To improve results, consider including:

  • Assessment descriptions or instructions (for context)
  • Course Learning Outcomes (CLOs)

AI Prompts for Course Development

After the CDD is complete, it’s time to create the lesson content and detailed assessment instructions.

Lesson Content

Lesson content is the pages in the Canvas LMS that students read before completing their weekly assessments. This is a good place to once again prompt the AI with what are the KSAs that a student should gain from a course on [topic]. Then, “using these KSAs, let’s create a lesson on [topic].

Sample Prompt for Lesson Content:

Create instructional content explaining [CONCEPT] for [undergrad/grad] students in an online, asynchronous course.
The content should include: A clear, concise definition of the concept. 2–3 real-world and/or generic examples that illustrate the concept in practice. Common misconceptions or errors related to the concept and how to address them.
Connections to related concepts or broader themes in [SUBJECT].
Write in a clear, conversational tone appropriate for college-level instruction. Focus on clarity, depth, and relevance to the weekly topics and assignments.

Be sure to double-check the accuracy of the real-world examples. 

To improve results, consider including:

  • Weekly topics or focus areas from the Course Design Document (CDD)
  • Notes and feedback from the CDD meeting
  • Course Learning Outcomes (CLOs) and Weekly Learning Objectives (LOs)
  • Expected prior student knowledge (prerequisites or assumed baseline skills)
  • Key concepts, terminology, or frameworks that must be introduced or reinforced
  • Preferred instructional style (e.g., applied focus, theoretical exploration, case-based)
  • Any discipline-specific examples or professional contexts that should be emphasized
  • Visual aids or examples if complex processes or models are involved (optional)

Sample Prompt for Incorporating Diverse Perspectives:

Review the lesson content on [TOPIC] and suggest ways to enrich the material by integrating a wider range of experiences and viewpoints.
Consider incorporating perspectives that may vary based on: cultural background, geographic location, socioeconomic status, educational or professional background, and lived experiences and identities relevant to the discipline.
Identify specific areas where introducing additional context, examples, or alternative framings could deepen students' understanding and foster broader, more inclusive engagement with the material.

To improve results, consider including:

  • Drafted lesson content
  • Required readings or case studies used during the week
  • Weekly topics or weekly learning objectives (for thematic focus)
  • Intended professional context or audience assumptions (e.g., U.S.-centric, global, interdisciplinary)
  • Common cultural assumptions or disciplinary biases to watch for

Weekly Overview Content

The weekly overview should introduce the week’s topic(s) and assessments to the learner in an engaging and relevant manner.

Sample Prompt for Weekly Overview: 

Here are the topic, weekly objectives and assessments for one week in a X level X online course. 
Write an engaging 150-word overview for a lesson on [TOPIC] in my [undergrad/grad] [SUBJECT] course. The overview should highlight key concepts students will explore, explain the real-world relevance of the material, and briefly preview the upcoming assignments.

Write in a clear, conversational tone appropriate for college-level instruction. Please avoid using common AI terms like delve, landscape, exciting world, etc.

To improve results, consider including:

  • Lesson content or topics covered
  • Drafts or summaries of weekly assignments

Assessment Creation

Sample Prompt for Assignment Instructions: 

Draft detailed instructions for an assignment in an online [undergrad/grad] course where students will [TASK DESCRIPTION] related to [TOPIC]. Make sure the assignment is relevant, and offers real-world application of the concepts to make the learning meaningful.
The instructions should include:
An overview of the assignment.
Step-by-step instructions for completing the task
Formatting expectations (e.g., file type, word count, citation style)
Submission instructions (e.g., file format)
An estimated time requirement (approximately [TIME] to complete)
Write in a clear, academic tone suitable for online instruction, and assume students have [BASIC SKILLS OR PRIOR KNOWLEDGE].

To improve results, consider asking for assignments that are varied in deliverables. Consider case studies, interview assignments, presentations to various audiences, creation of visuals.

Other things to include: 

  • Weekly topic(s) or focus area from the Course Design Document (CDD)
  • Initial assessment description from the CDD 
  • Lesson content and required readings
  • Applicable Course Learning Outcomes (CLOs) and Weekly Learning Objectives (LOs)
  • Any specific formatting or style guidelines (e.g., APA citation style)
  • Student background or assumed prior knowledge

Also consider prompting AI to “Act as a student in class [topic]. Read this assignment and then tell me what questions you have.” It is a great way to make sure the assignment is clear.

Sample Prompt for Discussion Instructions: 

Create a discussion activity for an online, asynchronous [undergrad/grad] course on [TOPIC]. The activity should include:

Overview: A 2–3 sentence introduction that frames the purpose of the discussion in relation to course concepts or real-world relevance.

Discussion Questions: 2-4 open-ended questions that encourage critical thinking, application, or evaluation. Avoiding yes/no or purely descriptive responses.

Peer Replies: Instructions for students to post two meaningful responses to peers. Include prompts for what to look for when replying (e.g., alternative perspectives, further examples, clarifying questions).

The goal is to promote deep engagement with the course material and with peers.

To improve results, consider including:

  • Weekly topic(s) or focus area from the Course Design Document (CDD)
  • Initial discussion description from the CDD 
  • Lesson content and required readings
  • Applicable Course Learning Outcomes (CLOs) and Weekly Learning Objectives (LOs)
  • Any specific formatting or style guidelines (e.g., APA citation style)
  • Student background or assumed prior knowledge

Sample Prompt for Quiz Questions: 

Generate 10 quiz questions that test comprehension and application of [CONCEPT] for an online [undergrad/grad] course.
Use a mix of the following question types: Multiple choice (single-answer), Multiple answer (select all that apply), and Fill-in-the-blank.
For multiple-choice (single-answer) questions: Provide one correct answer and three plausible distractors. Distractors should reflect common misconceptions or typical reasoning errors. Avoid "all of the above," "none of the above," "both A and B," and any options with internal logic that depend on other choices.
For multiple-answer questions: Clearly indicate that more than one answer may be correct. Provide a mix of 2–3 correct options and 1-2 plausible distractors. Ensure each correct answer stands alone as valid, even if others are removed.
For fill-in-the-blank questions: Place the blank near the end of the sentence to reduce cognitive load. Use only one blank per question.
For all questions: Provide a meaningful, one-sentence explanation of why the correct answer(s) is/are right. Avoid generic feedback like "That is correct." Write in a tone and terminology appropriate for [discipline or subject], and ensure that the questions reflect the rigor expected in an online [undergrad/grad] course.

To improve results, consider including:

  • Weekly topic(s) or focus area from the CDD
  • Lesson content and required readings
  • Applicable Course Learning Outcomes (CLOs) and Weekly Learning Objectives (LOs)
  • Student background or assumed prior knowledge
  • Common misconceptions to target in distractors (if known)

Instructional Materials

Sample Prompt for Case Studies: 

Develop a brief case study about [TOPIC] that presents students with a realistic scenario involving [SPECIFIC SITUATION]. Include sufficient background details, present a challenging problem that requires application of course concepts, and end with 3-4 analysis questions.

To improve results, consider including:

  • Weekly topic(s) or focus area from the CDD
  • Relevant course content or readings to align with (including key concepts students should apply)
  • Real-world constraints or variables students should consider (e.g., deadlines, regulations, conflicting priorities)
  • Target audience or student background assumptions (e.g., novice data analyst, marketing intern, junior cybersecurity professional)
  • Any relevant industry context, setting, or stakeholder roles (e.g., nonprofit org, client project, internal IT team)
  • Whether the case is intended to be used for discussion, written analysis, or a group project
  • Disciplinary tone or formatting preferences (e.g., clinical, technical, narrative)

FAQs

Q: How can I tell if AI-generated content needs revision? 

A: Review the draft by asking:

  • Accuracy: Are facts, terms, and examples correct? Watch for invented citations or errors in specialized content.
  • Depth: Does it match the complexity expected for your course level? If it stays descriptive without application or analysis, it needs strengthening.
  • Currency: Is the information up to date with current research, standards, or debates in your field?
  • Relevance: Does it directly support your course learning outcomes, weekly topics, and assessments?
  • Specificity: Are examples real-world and field-appropriate, or vague and generic?
  • Voice and Tone: Is the style professional and academic, not casual or overly broad?

Signs revision is needed:

  • Vague, broad, or surface-level explanations
  • Missing disciplinary terminology or frameworks

Q: When should I NOT use AI in course development? 

A: Limit or avoid AI use in these situations:

  • Citations and References: AI can fabricate sources. Always verify reading lists, citations, and resource suggestions.
  • Specialized or Rapidly Evolving Topics: In fields like cybersecurity, healthcare, or law, AI may oversimplify or miss critical updates.
  • Ethical, Equity, and Inclusion Content: Discussions about diversity, accessibility, or ethics require expert framing and lived-experience perspectives.

Q: How do I improve responses that seem superficial? 

A: 

  • Be more specific: Include key terminology, course level, expected depth, and real-world contexts in your prompt.
  • Request higher cognitive work: Ask for analysis, evaluation, or synthesis, not just summaries or descriptions.
  • Narrow the scope: Break broad prompts into smaller, focused tasks if the AI gives generalized answers.
  • Ask for multiple perspectives: Request alternative interpretations, case variations, or disciplinary debates to add depth.