Discover how our center helps faculty navigate AI in education through various initiatives, including events, a library of learning objects, a critical AI literacy course, and a student AI guide. We will also highlight a Human Biology lecturer who implemented genAI in a project assignment iteratively over a three-year period.

The rapid advancement of artificial intelligence (AI) technology presents both opportunities and challenges for educators, requiring robust support systems for faculty and students. While various campus units address AI in IT infrastructure, security, policy, and research, our Center for Teaching and Learning (CTL) focuses on supporting teaching and learning by promoting evidence-based practices, continuous learning, equity-minded approaches, well-being, and the centering of our community members.

This session will showcase the following recent resources from our AI Meets Education (AIMES) initiative that support instructors and students in navigating generative AI responsibly and effectively.

• Teaching with AI Community Share-Out Events—These events bring together faculty members to share their experiences, challenges, and successes in integrating AI into their pedagogy. The community-oriented approach encourages collaborative problem-solving and the exchange of best practices, creating a supportive network for continuous improvement.
• Library of Example Learning Objects—We have curated a comprehensive library of example learning objects from instructors at the university. These resources serve as practical tools for instructors looking to incorporate AI into their curriculum, offering real-world examples and templates that can be easily adapted to different teaching contexts.
• Critical AI Literacy Canvas Course—Our self-paced Canvas resource on critical AI literacy covers essential topics, including the ethical implications of AI, plagiarism detection, academic integrity, adapting assessments to AI, evaluating AI outputs, and more.
• Student Guide on AI and Learning—This user-friendly guide on AI and learning provides students with essential knowledge about AI, its applications in education, and best practices for leveraging AI tools to enhance their learning experiences.

The session will then spotlight a lecturer in Kinesiology and their experience in iteratively developing an AI-integrated group project assignment. In this assignment, students develop AI literacy skills by using genAI tools to:
• Brainstorm a topic related to the anatomy of movement.
• Assist in a literature review of relevant literature.
• Review the generated content for accuracy and quality.
• Analyze articles and select a specific topic thesis for the group project.
• Critique AI-generated and non-AI-generated images for a slide deck.
• Prompt AI to generate feedback on first drafts of the written report and slide presentation.
• Collaboratively evaluate this feedback and implement appropriate changes.

The instructor demonstrated how to prompt AI and narrated her metacognition live with students in the classroom to investigate how students can use AI tools effectively and model critical and appropriate use. We will share lessons learned over multiple iterations and how improvements to LLMs have affected the course. In the latest iteration, the lecturer is experimenting with how to create an AI persona, trained on the course materials, who can act as a first responder to questions from students online.

By participating in this session, attendees will gain:
• Insights into our strategic approach to integrating AI technology in education, which takes a critical stance on its impact and ethical considerations.
• Lessons learned from our experiences in designing and developing these learning experiences, including the challenges and successes encountered along the way.
• An understanding of the current measurements of the impact and success of our initiatives provides insights for replicating similar efforts in their institutions.

To ensure an interactive and engaging session, we will use polls to prompt reflection and gather feedback from participants throughout the presentation. This will be followed by a Q&A session, where participants can ask questions and delve deeper into the topics discussed.

Our AIMES initiative demonstrates how a Center for Teaching and Learning can support faculty and students in the evolving landscapes of AI and education. Attendees will gain actionable insights, practical tools, and inspiration for integrating AI into teaching and learning. Join us to explore and shape the future of AI-enhanced teaching and learning.

Kenji Ikemoto

Associate Director for Academic Technology at Stanford University

Kenji's expertise is in integrating technology-enhanced pedagogic strategies into instruction, research, and learning. Kenji provides one-on-one consultations, workshop facilitation, course design partnerships, and technology operations services for faculty, staff, and students. In his free time he enjoys tabletop role-playing games and cheering on his favorite Bay Area sports teams.

Carlos Seligo

Academic Technology Specialist at Stanford University