AI for Teaching and Learning 2026

Originally published in AI at Yale Updates “AI for Teaching and Learning Fall 2026 - AI at Yale Special Edition”.

Table of Contents

AI Tools for Teaching and Learning

FERPA Reminder:  This newsletter highlights tools vetted by Yale for federally mandated data privacy requirements.  If you plan to use an unvetted tool, first review the updated FERPA guidelines regarding appropriate use and limits of AI use in courses, and then notify the Poorvu Center for Teaching and Learning’s Educational Technology team (pictured above).  Explore additional Poorvu resources at Canvas Instructional Tools at Yale.

Gemini LTI

The Gemini LTI provides access to Gemini Chat, Gems, and NotebookLM directly within Canvas. Instructors can create customized AI experiences aligned with course goals, while students access the tools using Yale accounts. 

Availability: Available by request. No Fall 2026 request deadline. 

BoodleBox

BoodleBox allows instructors and students to compare multiple AI models, collaborate in shared AI conversations, and build custom AI assistants, tutors, and simulations. It can support activities focused on responsible AI literacy and critical evaluation of AI-generated content. Learn more: BoodleBox. 

Deadline: August 24, 2026. 

Ed Discussions with Bots++

Ed Discussion supports asynchronous discussion and community building within Canvas. Bots++ adds an instructor-configurable AI chatbot grounded in course materials and instructor-provided resources. Learn more: Ed Discussions with Bots++ 

Speakology AI

Speakology AI provides AI-powered avatar conversations for language learning. Students receive immediate feedback on pronunciation, grammar, and fluency, while instructors can review transcripts and recordings. Learn more: Speakology AI

Availability: Fall requests have closed. Spring 2027 requests are open.

Clarity Platform - API, Custom Agents

Clarity is Yale’s custom AI platform, which includes general purpose chatbots,  API access, and custom agents.  Current featured models include Claude Sonnet 4.6, ChatGPT 5.2, GPT-5 mini, o3, Gemini 2.5 Pro, and Gemini 2.5 Flash.  See Use Case 3 below a description of Jaideep Talwalkar’s custom agent.   

Workshop Highlights

Below are August workshop highlights.  Go to AI at Yale Find AI Events and click on the Yale Connect link to explore more options. 

August 12 & August 14

What’s New in Canvas? Pilots, AI, and Upcoming Workshops - This session introduces recent Canvas features, Fall 2026 pilot opportunities, AI tools, and instructional technologies available to Yale instructors. Participants will learn about Gemini LTI, BoodleBox, Speakology AI, Ed Discussions with Bots++, and other supported tools.

Registration options:

August 20

Gemini LTI Workshop and Information Session - An online workshop demonstrating how Gemini LTI can be incorporated into teaching and learning activities within Canvas. Registration.

August 21

Canvas 102 - This in-person workshop focuses on course organization, accessibility, assessment, grading, and using AI for course design. Participants will also receive dedicated lab time to work in their Canvas sites. Registration.

September 1

AI-Resilient Assessments: Reworking a Vulnerable Assignment - Jointly offered by Yale Library and the Poorvu Center, this 90-minute hands-on workshop helps instructors identify assignments vulnerable to AI shortcuts and redesign them as more resilient learning experiences.  Registration.

Monthly Community Series - First Wednesdays beginning September 2

Yale AI Updates + Community Chat: Teaching & Learning - Held on the first Wednesday of each month, these sessions provide updates on Yale-supported AI tools, demonstrations, classroom policy discussions, and opportunities to connect with colleagues exploring AI in education.  Registration, September 2.

The Technology & Innovation in Medical Education (TIME) series

Yale School of Medicine will offer the TIME series again this Fall.  Last year’s topics included Ideathons, Citizens Developer Workshops, and panel discussions. Events will be posted at Educational Technology and Innovation. 

How are Yale Instructors Using AI? 

Faculty are pushing AI beyond writing email to innovate on disciplinary methods and enhance simulated learning.  The three Use Cases and resources below provide practical inspiration. 

The Poorvu Center’s Assignment Case Studies collection includes examples across STEM, humanities, social sciences, creative writing, computer science, and language instruction. Case studies include:

  • AI-resilient assignments
  • Assignments that use AI as a learning tool; and
  • Assignments that make AI itself the object of study.

Use Case 1: Close Reading Meets Computational Analysis

Student AI Liaison Sophia Calderon Monarrez developed an assignment combining traditional close reading with computational analysis, including topic modeling, word embeddings, and Gemini-assisted coding in Google Colab. 

Innovation Spotlight: AI in Medical Education

Yale School of Medicine faculty and staff are pioneering applications of AI in medical education.  Consult the Health Sciences AI Toolkit for the latest options.

Use Case 2: Interviewing Tutor Agent in Clarity

Jaideep Talwalkar and Gary Leydon developed an interviewing-tutor agent using Yale’s Clarity Custom Agents for the Clinical Skills Team.  The agent specializes in generating practice scripts that mirror those used in the curriculum for the standardized patient program.  Students, faculty, and staff can use the agent to generate new scripts or improve existing ones. 
  
Read more about recent projects: 

Consultations

Poorvu Student AI Liaisons (SAILS)

Get an authentic student point of view on using AI in your classroom with a SAIL consultation.  SAIL students are undergraduates with experience with GenAI platforms, products, and technology.  Use Cases #1 and #2 above were collaborations with SAILS.

Use Case 3: Data Literacy and AI-Assisted Coding

Student AI Liaison Avi Kabra redesigned coding labs for Emma Zang’s Quantitative Methods in Sociology to help students develop data literacy while learning how to work effectively with LLM-assisted debugging tools.