CBS Faculty Guide to Generative AI Integration Checklist

The CBS Faculty Guide to Generative AI Integration provides a streamlined approach to thoughtfully incorporating generative AI into teaching. This checklist includes steps to plan, implement, and evaluate generative AI use, ensuring alignment with course objectives while fostering student learning and engagement. For more guidance, contact the Samberg Institute for Teaching Excellence.

Download the Checklist Document

 

Step 1: Planning

Decide how generative AI will help your students learn and which tools you'll use in your course. Set clear expectations about AI use, including policies and guidelines.

  • Set clear learning outcomes for generative AI use in your class. What should students be able to do after using AI tools? For example,
    • Do you want them to learn how to double-check generative AI answers?
    • Should they know when generative AI is and isn't helpful?
    • Do you want them to use generative AI to brainstorm ideas?
    • Do you want them to learn how to critically evaluate generative AI outputs?
    • Should they understand generative AI's limitations in your field?
  • Establish and document your generative AI policies and expectations in your syllabus.
    • Review CBS's generative AI policies: Students must disclose if and how they use generative AI.
    • Create guidelines for appropriate and inappropriate generative AI use.
    • Establish citation requirements for AI-generated content. 
  • Select appropriate generative AI tools based on the following:
    • Course learning objectives and content type.
    • Ease of use and accessibility for students.
    • Privacy and data security features.

Step 2: Preparation

Test generative AI tools with your course materials. This hands-on phase helps identify and address potential challenges before they affect students.

  • Test each generative AI tool with your course materials. 
    • Practice and refine example prompts for your in-class or at-home assignments.
    • Document common generative AI errors or limitations specific to your subject matter.
  • Provide guidance to students on how to use generative AI in your course.
  • Prepare backup plans in case generative AI tools are unavailable or produce unreliable results.

Step 3: Student Assessment

Design methods to evaluate student understanding and original thinking, while leveraging generative AI.

  • Design assignments that leverage generative AI's strengths while requiring human thinking, such as
    • Create generative AI-based assignments that require submitting thoughtful human prompts.
    • Ask students to critique and improve generative AI output from an existing assignment.
    • Require students to connect their analysis to class discussions and readings.
    • Ask for personal examples from students’ experiences or learning processes.
    • Incorporate generative AI or peer review in which students must defend their reasoning.
  • Develop assessment criteria for generative AI-assisted work, including how AI use will be weighted.
    • Create rubrics like this that specifically address generative AI integration quality.

Step 4: Implementation

Introduce generative AI tools through structured activities and monitor their impact on student learning. Start with low-stakes assignments to build student confidence and competence.

  • Demonstrate generative AI tool use with course-specific examples.
    • Select a low-stakes activity for the first generative AI assignment.
  • Consider assigning student roles for group assignments, for example for a data science project, generative AI could be a data engineer, Student 1 could be a data analyst, Student 2 could be a business analyst, and Student 3 could be the team manager who communicates and presents results.  
  • Document common challenges and solutions. 
  • Create a system for students to share effective prompts and approaches.

Step 5: Integration Evaluation

Gather feedback and assess how generative AI integration affects learning outcomes. Use these insights to refine your approach.

  • Assess the impact on learning outcomes. 
  • Collect student feedback through surveys and facilitated discussions engagement using quantitative and qualitative measures.
  • Compare performance metrics with previous non-generative AI approaches.
  • Document successful strategies and develop recommendations for future course iterations.

Final Steps

Summarize and share your experiences to contribute to CBS’s knowledge about generative AI in teaching.

For guidance at any stage, contact the Samberg Institute for Teaching Excellence.