Getting Started with AI
What is AI in Course Design?
Artificial intelligence tools are rapidly becoming part of everyday teaching and course design workflows. For faculty, AI can support idea generation, content development, feedback, and efficiency, but only when used intentionally and critically. This page introduces the fundamentals you need to begin using AI effectively in your teaching practice.
AI is not a replacement for your expertise. It functions best as a collaborator that can help you brainstorm, draft, organize, and refine instructional materials. The quality of what you get from AI depends heavily on how you guide it and how carefully you review its outputs.
As you begin, focus on building comfort with prompting, understanding limitations, and aligning AI use with your instructional goals. Starting small and experimenting within low-stakes tasks is the most effective way to build confidence.
What AI Can Do for Course Design
AI tools can support multiple aspects of instructional design when used strategically. Common use cases include:
- Generating ideas for assignments, discussions, or activities
- Drafting learning objectives aligned to course goals
- Creating examples, explanations, or case studies
- Assisting with rubric development or feedback language
- Summarizing or restructuring content for clarity
The key is to treat AI outputs as drafts, not finished products.
How AI Works (At a High Level)
Most AI tools used in education are based on large language models. These systems generate responses by predicting patterns in language based on large datasets. They do not “know” information in the way humans do and can produce responses that sound accurate but are incomplete or incorrect.
This means your role shifts from content creator to evaluator and editor. You guide the tool, interpret the results, and ensure alignment with your course outcomes.
Writing Effective Prompts
The quality of AI output is directly tied to the quality of your prompt. Strong prompts provide clear direction, context, and constraints.
Effective prompts typically include:
- Context: What course, level, or topic is this for?
- Task: What do you want the AI to produce?
- Constraints: Length, format, tone, or criteria
- Purpose: How the output will be used
Example Prompt:
Create three discussion questions for an undergraduate psychology course on cognitive bias. Each question should promote critical thinking and connect to real-world decision-making.
Iterate on your prompts. Refinement is part of the process.
Limitations to Keep in Mind
AI tools are powerful but imperfect. Common limitations include:
- Generating inaccurate or outdated information
- Producing vague or overly generic responses
- Missing alignment with your specific learning objectives
- Introducing bias or incomplete perspectives
Because of this, all AI-generated content should be reviewed and revised before use in your course.
Getting Started: Practical Steps
If you are new to AI, begin with simple, low-risk applications:
- Use AI to brainstorm ideas for an assignment or activity
- Ask AI to draft a set of learning objectives, then revise them
- Generate examples or case studies to supplement your materials
- Experiment with improving prompts to see how outputs change
Focus on exploration rather than perfection.
Best Practices for Faculty
- Start small and build gradually
- Always review and revise AI-generated content
- Align outputs to your learning objectives and assessments
- Be transparent with students when appropriate
- Use AI to enhance, not replace, your instructional decisions