Using AI to Assist With Course Design

Elements of Good Course Design

Thoughtful course design lays the foundation for a successful learning experience, ensuring that students not only engage with course material but also develop a deeper understanding of key concepts. A well-structured course not only supports students in achieving their learning goals but also reduces confusion, increases motivation, and fosters a sense of progression. When learning objectives, instructional activities, and assessments are clearly aligned, students can see the connections between what they are learning, how they are applying that knowledge, and how their progress will be evaluated.

Key elements of a well-designed course include:

• Clear and Measurable Learning Objectives – Clearly defined objectives help students understand what they are expected to achieve. Using action verbs that describe observable outcomes ensures that objectives can be effectively assessed.
• Course Alignment – Instructional materials, learning activities, and assessments should all work together to support learning objectives. Alignment creates a cohesive learning experience where every component of the course has a purpose.
• Logical Course Structure – Organizing content in a clear and sequential manner helps students gradually build knowledge and skills. A well-paced course prevents information overload and ensures that students can connect new concepts to prior learning.

Best practices rooted in well-studied educational theory and instructional design principles can help guide the course design process. Bloom’s Taxonomy is an example of a widely used framework that categorizes cognitive skills into six levels: remembering, understanding, applying, analyzing, evaluating, and creating. Each level is associated with specific action verbs, which guide instructors in crafting measurable and precise learning outcomes. The research-backed standards of the Quality Matters (QM) Rubric reinforce the importance of writing clear, measurable objectives that align with instructional content, learning activities, and assessment strategies.

Using Generative AI in Course Design

Generative AI tools can assist at every stage of course development, whether starting from scratch or improving existing course content. Instructors and instructional designers can leverage the power of AI to incorporate research-based best practices in a number of ways:

• Developing Course-Level Learning Objectives – AI can generate clear, measurable learning objectives aligned with Bloom’s Taxonomy, ensuring that they target appropriate cognitive skills and provide a strong foundation for assessments and instructional activities.
• Creating Module-Level Objectives – AI can break down broad course objectives into specific, actionable module-level objectives that support student progression from foundational to advanced skills.
• Building a Basic Course Outline – AI can help structure course content by dividing it into logical units or modules, ensuring topics are introduced in a coherent sequence that facilitates learning retention.
• Mapping Course Structure – AI can assist in designing a course map that aligns learning objectives with instructional materials, assessments, and activities, ensuring consistency and clarity throughout the course.
• Suggesting Assessments and Activities – AI can recommend formative and summative assessments, interactive learning activities, discussion prompts, and project-based assignments that align with learning objectives and promote student engagement.

Components of an AI prompt

To get the most useful AI output, it helps to write specific prompts that provide details about the task you are trying to accomplish. A well-structured AI prompt includes several key components to ensure relevant, structured, and high-quality responses, as listed in the table below.

AI Prompt Component	Description	Example
AI Role and Context	Clearly define the role the AI should take.	“You are an instructional designer developing a syllabus for an introductory psychology course.”
Content/Knowledge	Provide background information relevant to the task.	“The course is a 3-credit-hour undergraduate class focused on cognitive development and learning theories.”
Task/Objective	Clearly state what you want the AI to generate.	“Write five course-level learning objectives that are measurable and aligned with Bloom’s Taxonomy.”
Output/Format	Specify the format and structure of the response.	“List each learning objective using a numbered format, starting with a measurable action verb.”
Constraints/Parameters	Add necessary rules or parameters.	“Ensure that at least two objectives target higher-order thinking skills from the Analyze or Evaluate levels of Bloom’s Taxonomy.”
Examples (Optional but Helpful)	Provide sample responses or models to guide the AI output.	“Example of a measurable objective: ‘Apply major psychological theories to real-world learning scenarios.'”

Here is the above example prompt in paragraph format that could be pasted into a generative AI tool:

“AI Role and Context: You are an instructional designer developing a syllabus for an introductory psychology course.
Knowledge: The course is a 3-credit-hour undergraduate class focused on cognitive development and learning theories.
Task: Write five course-level learning objectives that are measurable and aligned with Bloom’s Taxonomy.
Format: List each learning objective using a numbered format, starting with a measurable action verb.
Parameters: Ensure that at least two objectives target higher-order thinking skills from the Analyze or Evaluate levels of Bloom’s Taxonomy.
Example of a measurable learning objective: Apply major psychological theories to real-world learning scenarios.”

Tips for Writing Effective AI Prompts

A well-structured prompt provides clear guidance, ensuring that AI outputs are relevant, structured, and aligned with best practices in course design. To get the best results from AI, keep these tips in mind:

• Be Specific – Provide clear details about the course, including the subject matter, course level, and intended audience. The more precise your prompt, the more relevant and useful the AI-generated content will be. Instead of “Generate learning objectives for a biology course,” refine it to “Generate five measurable learning objectives for an introductory undergraduate biology course that focus on foundational cellular biology concepts.”
• Provide Context – Help AI understand the instructional framework by mentioning relevant educational principles, such as Bloom’s Taxonomy, course alignment, or learning outcomes. Including information about the target audience, learning goals, and instructional setting ensures more tailored responses.
• Use Clear Formatting – Structure your prompt logically by dividing it into sections such as AI Role, Knowledge, Task, Parameters, and Output. Breaking down the request in an organized way makes it easier for AI to process the request and generate structured responses.
• Specify Bloom’s Taxonomy Levels – Indicate the cognitive skills you want to target in learning objectives. Whether you need objectives at the “remembering” level for foundational knowledge or “evaluating” for critical thinking skills, specifying the desired cognitive level improves the relevance of AI-generated content.
• Ask for Refinements – If the first output isn’t perfect, tweak the prompt and try again. AI-generated content may need refinement, and you can improve results by specifying additional constraints, modifying wording, or requesting revisions based on previous responses.
• Include Examples – AI performs better when given clear examples. If you want AI to generate learning objectives or assessments, provide a sample format or existing objective to guide its output. For example, “Example: ‘Evaluate major psychological theories and apply them to real-world learning scenarios.'” This helps AI generate content that matches your preferred style and structure.

Refining AI-Generated Content

While AI-generated content can serve as a useful starting point, refining the output is essential to ensure that it meets the specific needs of your course and enhances student learning. The refinement process involves several key steps to improve clarity, alignment, and engagement.

1. Customize for Your Course – AI-generated objectives and topics should be tailored to fit the specific goals, subject matter, and level of your course. Adjust terminology, add discipline-specific language, and ensure that content aligns with your syllabus and instructional approach.
2. Ensure Alignment – Cross-check AI-generated learning objectives, instructional materials, and assessments to confirm they support each other. Strong alignment between these elements helps maintain instructional coherence and improves student comprehension and performance.
3. Improve Clarity – AI-generated text may be too broad or vague. Edit for precision by refining language, removing unnecessary jargon, and ensuring that learning objectives and instructions are clearly articulated. Content should be student-friendly and easy to understand.
4. Enhance Engagement – AI content may lack the human touch that makes learning dynamic. Adapt the material to include interactive elements such as discussions, multimedia resources, hands-on activities, and case studies that encourage active participation and deeper learning.
5. Incorporate Additional Perspectives – AI may not always capture a variety of viewpoints, so consider integrating various perspectives and real-world examples. Including global perspectives and different points of view enriches students’ learning experiences and fosters critical thinking.
6. Verify Accuracy – AI tools can sometimes generate outdated or incorrect information. Always fact-check references, key concepts, and instructional materials to ensure they align with the latest research, best practices, and industry standards. Ensuring credibility enhances the quality and reliability of your course content.

By leveraging AI-generated content and refining it as needed, instructors can focus more on student engagement and meaningful learning experiences. With the right prompts and some fine-tuning, AI can make course design more efficient, aligned, and engaging.

Example Prompts for Course Design

You might want to start by trying some example AI prompts to jump start your course design process. The following examples are from a DELTA workshop. In the example prompts, notice the details that can help guide the AI to create the desired output. Customize the bracketed and highlighted text to fit your course; also consider modifying additional information for more specificity. Remember to carefully review the AI-generated content and use follow-up prompts to further refine your results.

Example Prompt: Write and Align Learning Objectives

AI Role and Context: You are an instructor of a [#]-credit-hour [introductory/intermediate/advanced] level [undergraduate/graduate] course about [course title or topic]. You need to identify a set of course-level learning objectives to guide your course design and student learning.
Knowledge: You have extensive knowledge about instructional design, educational alignment, the new Bloom’s taxonomy by Anderson and Krathwohl, and the Quality Matters Rubric for Higher Education, seventh edition, [add more as needed]. Also use knowledge related to common course topics in [course topic].
[Optional: and the textbook [title] by [author] (or other main instructional material)].
Task: Write [#] course-level learning objectives that describe what the students should be able to do upon successful completion of this course.
[Optional: Revise the provided examples of existing course-level learning objectives.]
Format: Each learning objective should be written as one sentence using concise and easy to understand language. Begin each learning objective with a measurable action verb. Number each learning objective using the prefix “CO.”
Parameters: [Optional: Use only verbs associated with the following Bloom’s Taxonomy levels: [specify level(s)]
Examples: [Optional: Below are the existing course-level learning objectives to revise: [list current course-level LOs]]

Using Generative AI to Write and Align Learning Objectives (Google Doc workshop resource)

Example Prompt: Create a Basic Course Outline

AI Role and Context: You are an instructor of a [#]-credit-hour [introductory/intermediate/advanced] level [undergraduate/graduate] course about [course title/topic]. You need to create a course outline that breaks down the course content into major topics and subtopics that can be taught in a modular format.
Knowledge: The duration of the course is [#] weeks. Use knowledge related to common course topics in [course title/topic]. [Optional: and the textbook [title] by [author] (or other main instructional material)]. Use these course-level and their aligned module-level learning objectives as a foundation: [insert or upload course objectives with corresponding module objectives].
Task: Create a basic course outline including [3-5] major topics that represent the high-level structure of the course content. Identify subtopics under each major topic. Integrate the provided module objectives into the appropriate subtopics.
Output: Organize the topics, subtopics and module objectives into a bulleted list. Rename the subtopics as [modules/units/weeks/lessons] and number them. Begin each module objective with the prefix [“MO”] and number them beginning with the module number as in this example: [MO] 3.2. After each module objective, list the CO each module objective is aligned with. List the course objectives at the top of the course outline.
Parameters: [Optional: The number of modules can be less than the number of weeks. Any module may last more than one week.]
Examples: [Optional: Include examples of course topics and subtopics]

Using Generative AI to Create A Basic Course Outline (Google Doc workshop resource)

Example Prompt: Create a Course Alignment Map

AI Role and Context: You are an instructor of a [#]-credit-hour [introductory/intermediate/advanced] level [undergraduate/graduate] course about [course title/topic]. You need to create a course map to align the instructional materials, learning activities, and assessments in your course with your learning objectives.
Knowledge: You have extensive knowledge about instructional design, educational alignment, active learning, the new Bloom’s taxonomy by Anderson and Krathwohl, and the Quality Matters Rubric for Higher Education, Seventh edition. Use knowledge related to common course topics in [course title/topic].   [Optional: and the textbook [title] by [author] (or other main instructional material)]. Use these module titles and module learning objectives: [insert or upload module titles and module learning objectives from your course outline] 
Task: Create a table with these headings: Module, Module Learning Objectives, Instructional Materials, Learning Activities, Assessments.
Format: Fill in the Module and Module Learning Objectives columns with information from this course outline: [insert course outline as a list]. 
Parameters: Leave the following columns blank for now: Instructional Materials, Learning Activities, Assessments.
Examples: [Optional: Include an example table or existing course map]

Using Generative AI to Create a Course Alignment Map (Google Doc workshop resource)

Workshop Information

Streamline Course Design With Generative AI

• Register for a workshop
• Watch a recorded workshop

If there are no available workshops, please feel free to request an instructional consultation about this topic.

Resources

Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. Longman.

Fang, B., & Broussard, K. (2024). Augmented Course Design: Using AI to Boost Efficiency and Expand Capacity. EDUCAUSE Review.

Germanna Instructional Support Services. (2024). AI for Course Creation. Germanna Community College.

Quality Matters. (2023). Specific Review Standards From the Quality Matters Higher Education Rubric, Seventh Edition. Quality Matters.

Sharp, C., & Mojeiko, L. (2023). AI Prompt Cookbook: Generative AI Recipes Designed to Enhance Teaching & Learning [Google Doc]. University of Florida Center for Instructional Technology and Training.

Wharton School. (2023). Practical AI for Instructors and Students Part 3: Prompting AI [Video]. YouTube.