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AI Meets Education at Stanford

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AI Meets Education at Stanford (AImES) is a VPUE effort to catalyze and support critical engagement with generative AI in Stanford teaching and learning contexts, coordinated by the Center for Teaching and Learning.

AImES fosters discussions among faculty, instructors, and students, and lower barriers for Stanford educators to engage productively and teach effectively in a world where generative AI appears to be here to stay. This effort is focused specifically on teaching and learning at Stanford University, complementing projects that advance AI research and policy in the broader world by bringing insights home to Stanford teaching and learning.

As a collection of activities and resources, AImES sparks engagement fueled by the kinds of deep critical thinking and discourse that are hallmarks of a Stanford education. As the homophone “aims” suggests, AImES takes academic goals as the starting point for considering, rejecting, integrating, or leveraging generative AI affordances in Stanford teaching and learning. The position of AImES is neither in favor of nor against generative AI. Rather, AImES amplifies a range of approaches and how they function ethically, pedagogically, practically, ecologically, and disciplinarily within the university context.

instructor and student working together with an open laptop

Teaching with AI Community Share-outs

Join a community of fellow instructors sharing and discussing their experiences navigating AI in their teaching practices. Several events will be hosted in-person at the Center for Teaching and Learning in Spring Quarter 2025. Each event includes lightning talks and open discussions featuring Stanford educators.

Call for Input: Thoughtful Approaches to AI in Education

Share examples of how Stanford instructors are engaging with generative AI in their course. Whether it's a creative use of AI tools, strategies to help diverse students navigate AI, or methods that encourage students to think critically about when and why not to use AI, we want to hear about it. Your input will help CTL facilitate community discussions and share diverse practices and perspectives.

diagram of AI literacy framework showing main categories of functional, ethical, rhetorical, and pedagogical questions connected

Teaching Commons Artificial Intelligence Teaching Guide

Learn about and gain tools to positively influence the dialogue around AI in education, in your own courses and at Stanford. Modules include AI literacy, pedagogical uses, implications for your course, creating your course policy, and integrating AI into assignments, as well as a DIY workshop kit.

Plan and design a course

Request a Consultation or Workshop

For one-to-one advice on creating your course AI policy or revising assignments in light of generative AI, to try out generative AI approaches at the CTL Academic Technology Solutions Lab, or to request a customized workshop on generative AI in your department or academic community at Stanford, contact us.

AImES Approaches

  • Enact proposed principles from the January 9, 2025 Report of the AI at Stanford Advisory Committee (AISAC):
    • human oversight
    • human alignment
    • human professionalism
    • ethical and safe use
    • privacy, security, and confidentiality
    • data quality and control
    • AI golden rule.
  • Build coherent and reusable resources when investing in the creation of new resources. Make them as evergreen and reusable as possible, while planning ahead for sustainable refresh cycles in this rapidly developing domain.
  • Emphasize a campus culture of reflection, curiosity, experimentation, and growth mindset so that students and instructors feel safe discussing and experimenting with AI, within boundaries that are openly discussed.

AImES Goals

  • Address education-specific needs and recommendations from the AISAC 2025 report, such as developing and sharing “frameworks and worked-out examples to help instructors think through… aspects of pedagogy impacted by AI” and facilitating “setting[s] where community members can experiment with AI tools.”
  • Support Stanford academic communities to more readily discover, create, and share discipline-specific AI approaches.
  • Integrate AI approaches with known evidence and with the university’s core mission related to teaching and learning: for example, metacognition, scaffolding, transparency, purposes of a liberal education, preparation for citizenship and discovery.
  • Connect across initiatives and groups working on AI and AI-adjacent issues in teaching and learning at Stanford.

Coming Soon

AImES team members at CTL, along with partners in VPUE, schools, and departments, are preparing the following new resources and opportunities for summer 2025 and beyond:

  • A new self-paced Canvas course on critical AI literacy for Stanford instructors
  • An expanded online library of examples, including course policies, assignments, and demonstrations
  • Discipline-based and departmental community conversations sharing and discussing specific examples and practices within relevant shared educational contexts
  • Forums for discussion about generative AI across instructor-TA-student roles

Additional Stanford Resources

The AImES team in CTL and VPUE is committed to coordinating and collaborating with colleagues across the university, each working on distinct and connected aspects of generative AI. This network of experts and endeavors provides a resource-rich environment for Stanford instructors, researchers, and learners, including the following:

Questions?

For questions and suggestions related to AImES, please contact Cassandra Volpe Horii, associate vice provost for education and director of the Center for Teaching and Learning, at cvhorii@stanford.edu.