Resources & Job Aids
Practical Tools, Resources, & Job Aids
This page provides practical tools and quick-reference guides to support your use of AI in course design.
These resources are intended to help you apply what you have learned across the site, from writing effective prompts to evaluating outputs and designing aligned assessments.
Using These Job Aids
Rather than starting from scratch each time, these job aids offer structured approaches you can reuse and adapt. They are especially useful when you are experimenting with AI tools or refining your workflow.
Use these resources as flexible supports. Adapt them to your discipline, course level, and instructional goals.
Prompt Writing Guide
Use this structure to create more effective and targeted AI prompts:
Prompt Framework
- Context: Course, level, topic.
- Task: What you want the AI to generate.
- Constraints: Format, length, tone, criteria.
- Purpose: How the output will be used.
Example Prompt: Create a case study for an undergraduate business course on ethical decision-making. The case should be realistic, 2–3 paragraphs in length, and include a scenario that requires students to evaluate competing priorities.
Prompt Refinement Strategies
If your results are too vague or not aligned, adjust your prompt:
- Add more context about your course or students.
- Specify the level of cognitive complexity.
- Provide examples of what you want.
- Break the task into smaller steps.
- Ask for revisions instead of starting over.
AI output improves through iteration. Refinement is part of the process.
AI Output Evaluation Checklist
Use this checklist when reviewing AI-generated content:
- Accuracy: Is the information correct and reliable?
- Alignment: Does it match your learning objectives?
- Clarity: Are instructions and expectations clear?
- Rigor: Is the level appropriate for your course?
- Relevance: Does it directly support the task or goal?
If any of these areas are weak, revise the prompt or edit the output.
Assessment Design Quick Guide
When using AI to support assessments, ensure alignment and quality:
- Start with clearly defined learning objectives.
- Specify the type of assessment, such as formative, summative, or performance-based.
- Indicate the expected level of thinking, such as application or analysis.
- Review and refine for clarity and rigor.
- Ensure criteria for success are explicit.
AI can generate ideas quickly, but alignment must be intentional.
Example AI Prompts for Course Design
Learning Objectives: Write three measurable learning objectives for a graduate-level course on instructional design. Each objective should align with higher-order thinking skills.
Discussion Questions: Create two discussion questions that encourage students to apply course concepts to real-world situations in a healthcare setting.
Rubric Development: Generate a rubric with four criteria for evaluating a student project on course design. Include performance levels and clear descriptions.
Content Simplification: Rewrite the following explanation to make it more concise and accessible for undergraduate students.
Faculty Considerations for AI Use
- Maintain ownership of instructional decisions.
- Review all outputs before sharing with students.
- Be transparent about AI use when appropriate.
- Consider how AI impacts assessment design and academic integrity.
- Focus on improving learning, not just saving time.
Additional Resources
Using These Resources
These job aids are designed to support ongoing use, not one-time reference. As you continue working with AI, revisit and adapt these tools to fit your needs.
Effective use of AI develops over time through practice, reflection, and refinement.