Enhancing Classroom Experiences with Generative AI: A Workshop for Personalized Learning with Open Source Tools

April 1, 2025 - 11:00 AM-12:00 PM

Location: This hybrid event will be held in person in 117 Dwinelle Hall (Academic Innovation Studio) and also on Zoom. Please RSVP to get the Zoom invite.  

Intended Audience: Academic Support Staff, Faculty, Graduate Student Instructors, Instructors

This session will present several case studies of how generative AI is increasingly being implemented into STEM classrooms in higher education via an open-source mastery learning tool, Open Adaptive Tutor (OATutor), including its applications at UC Berkeley. We will document the use of automated curriculum alignment tools to weigh creating new content with GenAI against using or adapting existing open educational resources (OERs). An interactive part of the session will demonstrate how teachers can use a collaborative authoring tool for OATutor that connects domain experts to prompt engineering, enabling rapid iteration and refinement of educational materials using AI. Faculty will leave the session equipped with actionable strategies to integrate the generative AI tools presented into their teaching practices, fostering student success at UC Berkeley.

Goals:

  1. Present case studies demonstrating the use of generative AI methodologies and OATutor to enhance teaching practices in STEM classrooms at UC Berkeley.

  2. Facilitate a hands-on demonstration of how to use a collaborative authoring tool to generate educational content with generative AI, ensuring domain experts remain central to the process.

This session will run for 45 minutes, with an additional 15 minutes reserved for questions. 

➡️Register for this event here!⬅️

Registrants will be sent a Zoom link and bCal invite as the workshop date draws near.

***Registration for this session will close one hour before the session***

This event is part of the "Navigating Gen AI: Implications for Teaching and Learning" learning path. Be sure to check out this learning path and explore its other components!

Facilitators:

Picture of the facilitator, Zach Pardos

Zachary A. Pardos is an Associate Professor of Education at UC Berkeley studying adaptive learning and AI. He has 17 years of research experience with intelligent tutoring systems and leads the Computational Approaches to Human Learning research lab, developing tools like OATutor and AskOski, a course recommendation and multi-institution student success initiative. His work designing Human-AI collaborations to pave pathways to and within systems of higher education has been published in venues such as SIGCHI, NeurIPS, Computers & Education, and Science. At Berkeley, he teaches in the data science undergraduate program and is an affiliated faculty member in Cognitive Science.

Picture of the facilitator, Shreya Bhandari

Shreya Bhandari is a recent graduate of Electrical Engineering and Computer Science from UC Berkeley.  She is the lead research developer for the OATutor project. She has been working with the team since 2022, running experiments and continuously expanding OATutor’s capabilities by incorporating the latest advancements in LLMs. Her research interests include leveraging AI for practical educational impact, computer tutoring, reinforcement learning, and personalized learning.

Picture of the facilitator, Ioannis Anastasopoulos

Ioannis Anastasopoulos is a second-year doctoral student, studying learning sciences in the Berkeley School of Education. His interests lie in iterating the pedagogy and usability of digital learning environments to enhance student learning. Ioannis has been involved with OATutor since its inception, leading the content creation effort of the project for over four years, as well as working with teachers and instructors to ease integrations of the system into their classrooms.

Picture of the facilitator, Yerin Kwak

Yerin Kwak is a first-year PhD student in Education at UC Berkeley. She has been working on leveraging AI in educational research, including skill mapping, deployment, and instructional design for the OATutor project, as well as course equivalency recommendations in higher education. Her research interests focus on AI applications in education, educational data science, computer tutoring systems, and personalized learning.