Course Design

Alignment in course design

  • Ensure alignment across your intended learning outcomes (ILOs), assessments, and learning activities. ILOs identify what knowledge, skills, and values students should demonstrate by the end of your course. Assessments evaluate how well students achieve those ILOs, and learning activities are meant to prepare students to do the assessments. When you alter any of these three components, re-assess the alignment and update the remaining components as needed. 
  • Inquire about your program’s curricular approach to AI. Your courses should fit into the broader context of a program, so talk to your chair, director, or curriculum committee members about the overall intended approach (e.g., ensuring students learn foundational knowledge and skills before teaching them how AI can best assist their learning; ensuring students are equipped with discipline-specific AI skills).

Reviewing your intended learning outcomes (ILOs)

  • Determine which learning outcomes require students to demonstrate knowledge or skills without using AI, and ensure your assessments and activities are structured in a way that supports this goal. Preserve opportunities for students to engage in the challenge of learning, particularly when developing foundational knowledge, critical thinking, problem-solving, communication, and other core disciplinary skills.
  • Identify learning outcomes that could be strengthened through appropriate student use of AI. AI can support learning by helping students practice, apply, analyze, create, or reflect on disciplinary knowledge and skills. Consider how AI is being used in relevant disciplinary, professional, or vocational contexts. If you add a new assessment or alter an existing one to integrate AI use, ensure any associated ILOs reflect the change.
  • Determine whether student AI use supports or obscures the evidence of learning needed to demonstrate achievement of the learning outcome. If it obscures, you will need to update any associated assessments.
    • To learn more: Read Assessment Redesign

Accessibility and inclusion

  • Recognize that AI may support accessibility for some students, but not all. It is also not a substitute for accessible course design, accommodations, or other supports.
  • Consider accessibility design when choosing AI tools to ensure that they do not introduce barriers for students.
  • Use AI tools to support accessibility and student learning such as transcription, captioning, summarizing, brainstorming, language support, or content adaptation when appropriate.
Examples

Examples:

  • Using AI to assist with writing alternative text. Use or adapt these prompts to draft concise or complex alternative text. (Screen readers use alternative text, or alt text, to read aloud a description of an image.)

  • Use ClipChamp via UW's Microsoft 365 Copilot to generate transcriptions (only works with Microsoft Edge browser).

  • Consider impacts to accessibility when limiting technology use for students who rely on digital tools or accommodations involving technology.

  • AI tools may produce inaccuracies or biased or discriminatory outputs, including stereotypical representations of individuals from equity-denied, marginalized groups. A human needs to review what AI produces and make corrections.

  • Always consider equity when requiring use of AI tools, as required use may create or exacerbate inequities some students already experience (e.g., some students pay for models that result in higher quality outputs than free models; some students object to AI use on ethical grounds).

Examples

Example: Design your activity/assessment around students using institutionally provided platforms and tools (e.g., Microsoft CoPilot).

AI in teaching and learning activities

  • Select and implement tools thoughtfully. Prioritize institutionally approved AI tools when possible to help ensure accessibility, privacy, security, and technical support.
Important

Important note: Learn about constraints in using unlicensed AI tools with students in Unlicensed AI Tools in Getting Started

  • Acknowledge different viewpoints on using AI, and unless AI is tied to course learning outcomes or is required in your course to address program outcomes, consider whether it is feasible to offer students with objections an option to complete assignments and activities without using AI (e.g., by using different tools or by generating an AI output yourself for students to analyze). 

Harnessing AI to create meaningful learning opportunities

  • Align AI-integrated learning opportunities with intended learning outcomes and assessments. How can you leverage AI to prepare students for engagement in class activities, homework, and assessments? As a disciplinary expert, model how students can use AI within the discipline.
  • Use AI purposefully to support student learning or reflect authentic practices, like disciplinary, professional, or workplace practices. Ensure students have the skills needed to use approved AI tools and engage meaningfully with the outputs.
Examples

Examples:

  • Using GenAI to help students improve their writing through feedback. Use or adapt these prompts to show students how GenAI can help them reflect on and improve their writing without writing for them. (Situate this learning opportunity within your context; consider whether students should submit an explanation or reflection on the changes they made after using GenAI.) 
  • Using GenAI in coding activities. Use or adapt these sample activity instructions to show students how GenAI can support coding activities by helping students brainstorm solutions, debug code, test implementations, and review designs while maintaining accountability for evaluating outputs and informed decision-making.
  • Using GenAI in problem-solving activities. Use or adapt these sample activity instructions to show students how GenAI can support conceptualizing problems, evaluating approaches and trade-offs, and reflecting on their reasoning and decision making. These activities emphasize understanding, judgement, and metacognition over simply generating a correct solution.
  • AI can help students personalize their learning, such as in large classes where it might be difficult to reach every learner.   
Examples

Example: Using GenAI to help students personalize their learning of complex concepts. Use or adapt these prompts to show students how GenAI can explain and break down complex topics according to their level and needs. 

  • AI enables students to practice real-world scenarios that are difficult to find and/or scale.

Examples

Example: Using GenAI to help students practice real-world scenarios. Use or adapt these prompts to show students how to use GenAI to simulate conducting a medical assessment or an interview with a prospective employer.

Preserving meaningful human interaction

Examples

Example: If using AI to develop case studies, include follow-up discussion questions for group exploration. AI can be directed to create the questions, but students need to have the discussion. Source: “Case Studies and Scenarios” in GenAI and Teaching Materials workshop (Teaching Support and Innovation).

Using AI in the course design process

  • AI can help with various aspects of the course design process, especially when employed in the brainstorming and drafting stages. Always critically examine and adapt AI outputs to reflect unique course goals, learning experiences, and student needs. Initial outputs should not substitute for humans engaging in this creative and iterative process.
Examples

Examples:

  • Leverage AI to complete general, high-level research that can inform your course design.
Examples

Examples: 

  • Conduct environmental scans of comparator universities’ course descriptions and syllabi.
  • Brainstorm activity ideas for different class sizes and types of learning spaces, including in-person and online.
  • Identify trends in how the current generation of students prefer to engage with learning.

Modeling responsible GenAI use

  • Foster a culture of honesty and openness, which helps students develop an awareness of how AI is shaping their learning environments and their own AI literacy. 
  • Be appropriately transparent about when and how AI has been used to support the creation of teaching materials.
Examples

Examples:

  • Demonstrate the critical evaluation practices you expect of students. Talk to students about your AI transparency statement and invite them to ask questions. Tell them why you decided to use AI for various course materials (what criteria did you use to decide?) so they can become more discerning in their own decision-making. 

Using AI to draft teaching materials

  • Leverage AI to support design tasks such as brainstorming ideas, creating draft content, generating examples, developing scenarios, or identifying alternative explanations of complex concepts. AI can also quickly create multiple formats, explanations, examples, or representations of content.
Examples

Examples:

  • Review and refine AI-generated materials to ensure they are accurate, relevant, accessible, inclusive, and aligned with course goals. Remain accountable for the final content shared with students. 
  • Avoid offloading the entire design process to AI. Your expertise, disciplinary knowledge, professional judgement, and knowledge of students and context remain essential for creating effective learning experiences. 

References

Massachusetts Institute of Technology, Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training. (2026, August 13). Report. MIT AI and Education. https://aiandeducation.mit.edu/report/