Learning Tracks
Bringing together the people and ideas shaping what's next for higher education.
October 14-16, 2026
Luskin Conference Center, UCLA
An invitation-only convening
Bringing together the people and ideas
shaping what's next for higher education.
October 14-16, 2026
Luskin Conference Center, UCLA
An invitation-only convening
PROGRAM
Conversations and ideas reshaping higher education
Explore five mainstage panels, sixteen breakout sessions across five Learning Tracks, a Poster Gallery Walk, and more. The program brings together ideas, expertise, and innovative work from Learning Lab’s grantee network and leaders across California’s three public higher education systems.
Learning Tracks
Across five Learning Tracks, dozens of faculty and other presenters will share ideas, emerging practices, and lessons learned through presentations, panels, and hands-on workshops designed to invite discussion and participation.
Tracks
Breaking Down Disciplinary Silos
Designing Teaching, Learning, and Assessment for an AI-Driven World
Educating for the Public Good in a Digital Society
Reinventing Pathways & Workforce Futures
THRIVING AMID DISRUPTION: BUILDING FACULTY & INSTITUTIONAL CAPACITY
Session 1
Thursday, OCT. 15 | 11:35 am – 12:20 pm
Computational Curriculum Co-Creation: An Intersegmental, Interdisiplinary Faculty-Student Initative
From Chemistry and Biology to Music and AI Ethics, how can faculty and students co-create engaging interdiscipinary learning experiences founded in data science principles? This session highlights El Camino Modules, a UC Berkeley-El Camino College partnership that pairs student developers with faculty to create interactive, Jupyter notebook-based course materials. Attendees will explore student-built notebooks, including interactive analyses of incarceration and public health data, and see a live demo of a browser-based textbook that runs code directly from the page. We’ll also showcase CSCI 9, a data science course designed for community college adoption, and share lessons on scaling student-faculty collaboration, centering learner perspectives, and sustaining cross-institutional innovation.
Breaking Down Disciplinary Silos
Educating for the Public Good in a Digital Society
Reinventing Pathways & Workforce Futures
COHORTS
Data Science • Partnership Grants
PROJECTS
Enhancing Data Science Teaching Capacity • Partnership for Establishing a California Interactive Computing Open Resource (Cal-ICOR)
PRESENTERS
Solomon Russell, El Camino College
Edwin Vargas Navarro , UC Berkeley
Eric Van Dusen, UC Berkeley
PromptHive and OATutor: Scaling Adaptive Tutoring with Faculty Expertise and Generative AI
How can generative AI help scale high-quality adaptive tutoring without sacrificing instructional quality? This presentation introduces a new AI-powered extension of OATutor, UC Berkeley’s open-source, mastery-learning based adaptive tutoring platform, and PromptHive, a collaborative authoring tool that enables subject matter experts and AI to create tutoring content more efficiently. We share results from a chemistry deployment at UC Berkeley, including student outcomes and feedback, and examine how varying levels of teaching staff involvement in chemistry and calculus courses influence implementation success. Our findings highlight both the promise of AI-accelerated content development and the essential role of instructor expertise in ensuring effective, trustworthy learning experiences.
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORT
AI FAST
PROJECT
Cost-effective, Bespoke Adaptive Tutoring using Open Source Tools and GenAI
PRESENTERS
Ioannis Anastasopoulos, UC Berkeley
Zachary Pardos, UC Berkeley
Measuring What Matters in AI-Mediated Math Learning: Interaction Quality and AI Literacy
Drawing on mathematics education literature emphasizing the centrality of discourse and dialogue to mathematical learning, this work examines what happens when those conversational dynamics are transposed onto a digital, AI-mediated context. The shift in power dynamic inherent in human-AI interaction, coupled with students’ predominantly transactional perception of AI tutors, produces use patterns that may facilitate answer-retrieval without meaningfully advancing mathematical reasoning or the development of durable learner identities.
Designing Teaching, Learning, and Assessment for an AI-Driven World
Educating for the Public Good in a Digital Society
COHORT
AI FAST
PROJECT
Acquiring Math Prerequisites Efficiently and Scalably with AI
PRESENTERS
Amy Eguchi, UC San Diego
Portia Restuccia, Vocareum
Maura White, UC San Diego
Regional AI Readiness: Partnerships, Practice, and Possibilities for Scaling Across Segments and Beyond
How can higher education build AI capacity at scale while meeting local needs? This session showcases the Equitable AI Alliance–a regional, intersegmental collaboration between San Diego State University, San Diego Community College District, and UC San Diego–sharing lessons from the front lines. Presenters will explore how survey research, AI micro-credentials, and cross-sector partnerships are shaping scalable pathways for faculty, staff, students, and lifelong learners. Attendees will learn how evidence-based strategies and data-informed decision-making have guided the development of AI literacy programs, responsible AI practices, and professional learning opportunities. The session will also examine the challenges and opportunities of expanding these efforts statewide while balancing innovation, consistency, and equitable access in a rapidly evolving AI landscape.
Reinventing Pathways & Workforce Futures
THRIVING AMID DISRUPTION: BUILDING FACULTY & INSTITUTIONAL CAPACITY
COHORT
AI Grand
PROJECT
Equitable AI Alliance: Empowering Students through Equitable AI Education
PRESENTERS
David Goldberg, San Diego State
Alison Gurganus, San Diego Community College District
Dan Suchy, UC San Diego
Data Ethics Everywhere: Building Faculty Capacity Across the Curriculum
As AI and data shape decision-making across disciplines, faculty need practical ways to teach ethical data use. This interactive session introduces CONFIDE (Community of Networking Faculty Investigating Data Ethics), a faculty learning model for integrating data ethics into existing courses. Participants will engage with a real-world ethical dilemma, experience a condensed CONFIDE activity, and explore strategies for turning complex ethical questions into meaningful learning opportunities. Presenters will share lessons on cross-disciplinary collaboration, faculty engagement, and sustainable capacity building. Attendees will leave with practical resources and a replicable framework for expanding data ethics education across their institutions.
THRIVING AMID DISRUPTION: BUILDING FACULTY & INSTITUTIONAL CAPACITY
COHORT
Data Science
PROJECT
CONFIDE: Community of Networking Faculty Investigating Data Ethics
PRESENTERS
Ariel Setniker, Cal Poly Maritime
Li Huang, Cal Poly Maritime
Steve Kielar, Cal Poly Maritime
Robin Yancey, Solano Community College
Session 2
Thursday, OCT. 15 | 3:15 – 4:15 pm
AI Literacy Is Contextual: Insights from Implementing AI Education Within and Across Disciplines and Communities
AI literacy does not develop in a vacuum. This panel examines how educators translate AI literacy goals into meaningful learning experiences shaped by disciplinary practices, student communities, and ethical considerations. Panelists will share lessons from developing and adapting AI literacy courses intersegmentally, embedding AI ethics within disciplinary education, supporting faculty across fields, and engaging with concerns about responsible AI use. Together, they will explore how institutions can design AI literacy approaches that are both broadly relevant and responsive to the contexts in which students learn.
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORTS
AI FAST · AI Grand
PROJECTS
GenAI Preparedness for Teaching & Learning at SF State · Improving student engagement and outcomes equitably with course-specific open-sourced AI-tutors · Peer & AI Review + Reflection (PAIRR) in Writing Instruction
MODERATOR
Shahrukh Humayoun, San Francisco State
PANELISTS
Anoshua Chaudhuri, San Francisco State
Simon Fan, Cal State San Marcos
Marit J. MacArthur, UC Davis
Designing AI-Enhanced Calculus to Engage Students in Deeper Mathematical Thinking
How can AI help students learn calculus more deeply, not just faster? This session shares lessons from an AI-enhanced Calculus I pilot that integrated machine learning applications, AI-supported learning activities, Python labs, and structured practice via the MathGPT.ai homework platform. Through an iterative design process informed by classroom observations and a faculty Community of Practice, the project evolved from AI-driven concept exploration toward activities that emphasize reflection, explanation, and connection-making. Participants will see concrete examples of instructional strategies, student learning experiences, and course refinements, and gain practical insights into using AI to strengthen conceptual understanding, mathematical reasoning, and engagement in calculus and other STEM courses.
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORT
AI FAST
PROJECT
AI-Enhanced Curriculum: Transforming Calculus and Statistics Education
PRESENTERS
Jay Cho, Pasadena City College
Roger Yang, Pasadena City College
AI as a Cognitive Partner in Calculus Instruction: Task Design and Student Mathematical Reasoning
As generative AI becomes a regular part of students’ learning environments, mathematics educators must find ways to leverage its potential without weakening students’ reasoning skills. This session presents an AI-integrated approach to Calculus I that treats generative AI as a cognitive partner in learning. Developed in collaboration with experienced calculus instructors, the project engaged students in identifying errors, analyzing mathematical explanations, generating new problems from common mistakes, and reflecting on their thinking through iterative interactions with AI. Rather than passively accepting AI-generated answers, students used AI to deepen conceptual understanding, strengthen critical thinking, and develop metacognitive awareness. We share examples of these learning activities, evidence of their impact on student understanding, and lessons learned about designing AI-supported instruction that promotes productive engagement while preserving students’ responsibility for mathematical reasoning.
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORT
AI FAST
PROJECT
Collaborative AI Integration in STEM Education
PRESENTER
Hyunkyoung Yoon, Cal Poly Pomona
The Future of Assessment: What We Know from Scaling New Approaches
Assessment is at an inflection point. As educators rethink how students learn, demonstrate mastery, and engage with coursework, institutions are exploring new approaches that challenge longstanding assumptions about assessment. This panel brings together leaders who are implementing and studying new models in practice, including mastery-based assessment, technology-supported learning environments, and data-informed approaches to understanding student engagement. Panelists will share lessons from building and expanding these efforts, including the opportunities and challenges of supporting multiple pathways to learning, maintaining rigor and academic integrity, using AI and analytics thoughtfully, and creating sustainable approaches across courses and institutions. The discussion will consider what these experiences reveal about the future of assessment and how higher education can design assessment systems that better support meaningful student learning.
THRIVING AMID DISRUPTION: BUILDING FACULTY & INSTITUTIONAL CAPACITY
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORTS
Innovation • Scaling Success
PROJECTS
Improving Learning Outcomes for All General Chemistry Students through Adaptive Hybrid Courses • A’s-for-All (A4A): Scaling Mastery Learning Through Technology, Advocacy, Policy, and Partnerships
MODERATOR
Solomon Russell, El Camino College
PANELISTS
Mark Blaser, Carnegie Mellon
Armando Fox, UC Berkeley
Rolin Moe, UC Office of the President
Building Momentum for Faculty Leadership in Career-Connected Learning In California and Beyond
How are faculty playing a more intentional role in connecting students’ academic experiences to meaningful career pathways? Drawing on lessons from Lumina Foundation’s From Campus to Career initiative, the California State University’s Learning Innovation for Future-Forward Teaching (LIFT) initiative, and the City University of New York’s CUNY Beyond initiative, this session will explore how faculty are embedding career-connected learning throughout the student experience. Participants will be invited to examine the forces making this work timely and necessary, and the systems and supports that can make this work effective and sustainable.
Reinventing Pathways & Workforce Futures
PRESENTERS
Rob Shorette, Lumina Foundation
Jason Hendrickson, LaGuardia Community College/CUNY
Emily Magruder, CSU Chancellor’s Office
*Not a Learning Lab-funded Project
Can a Chatbot Help Guide Transfer and Career Pathways? An Intersegmental Experimental Evaluation
AI is transforming higher education, but can it improve career advising and student success? This session presents the development and evaluation of Build Your Career Pathway (BYCP), an AI-powered advising chatbot created through a partnership between CSU Dominguez Hills, East Los Angeles College, workforce organizations, and technology partners. Unlike general-purpose AI tools, BYCP provides personalized guidance grounded in academic programs, transfer pathways, internships, and regional labor market data. We will describe how the chatbot was designed to support first-generation, transfer, and historically underserved students while addressing common concerns surrounding AI, including hallucinations, outdated information, and institutional relevance. Presenters will share findings from a randomized classroom study and insights from more than 4,000 student-AI interactions. Attendees will gain practical strategies for building trustworthy, institution-specific AI systems, integrating AI into advising and instruction, and leveraging AI to strengthen career readiness and student success.
Reinventing Pathways & Workforce Futures
COHORT
AI FAST
PROJECT
Developing and Testing the “Build Your Career Pathway” AI Chatbot at CSU Dominguez Hills and East Los Angeles College
PRESENTERS
Fynnwin Prager, CSU Dominguez Hills
Jennifer Brodmann, CSU Dominguez Hills
Session 3
Friday, Oct. 16 | 10:00 – 11:00 am
Rethinking Engineering Workforce Preparation
This panel brings together leaders from three initiatives across California’s higher education systems to discuss effective practices, challenges, and lessons learned in engineering and semiconductor workforce development. Panelists will compare strategies for strengthening pathways from education to employment through industry partnerships, research experiences, workforce-aligned curriculum, and student support. The conversation will also explore how AI and emerging technologies are shaping engineering education and workforce preparation. Attendees will gain insights into collaborative approaches that support student success and help build California’s future engineering workforce.
Reinventing Pathways & Workforce Futures
COHORTS
AI FAST • Partnership Grants • Resilient Workforce
PROJECTS
Titan Research Immersion: Empowering Diversity in Chip Design • Enhancing the Engineering Pipeline from Community College through to the California Workforce • Semiconductor Pathways for Advancing Regional Knowledge (Project SPARK)
MODERATOR
Ken Yang, UCLA
PANELISTS
Kevin Graham, UCLA
Rakesh Mahto, Cal State Fullerton
Rose-Margaret Itua, Ohlone College
What Faculty Need to Know About AI Tutors in STEM
In this panel, STEM faculty compare findings from rigorous classroom research on the implementation of AI tutors in biology, data science, and chemistry labs. Building on the panelists’ research—as well as the moderator’s research on AI tutors in mathematics classrooms—the facilitated discussion will explore what the evidence tells us about when, how, and under what conditions AI tutors can effectively support STEM learning.
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORTS
AI Grand • AI FAST
PROJECTS
Improving student engagement and outcomes equitably with course-specific open-sourced AI-tutors · AI-Assistance in Lower Division Chemistry Laboratory Course Curriculum
MODERATOR
Virginia de Sa, UC San Diego
PANELISTS
Kimberly D. Edwards, UC Irvine
Mohan Paturi, UC San Diego
Gena Sbeglia, San Diego State
Expanding Pathways: A SoCal Intersegmental Approach to Connecting Coursework, Career Exploration, and Transfer Success in Data Science
The Southern California Consortium for Data Science brings together eight institutions across California’s public higher education segments to create additional and more equitable pathways into data science careers. Spanning the region from San Diego to Santa Barbara, the consortium is working to align curriculum, expand career exploration, and improve transfer success for students from a variety of backgrounds, particularly those historically underrepresented in STEM. This session highlights lessons learned from developing articulated data science coursework, creating K-20 opportunities for students to explore data science careers, and strengthening support for transfer students as they transition into university programs. Attendees will gain insights into building cross-sector collaborations that expand access, improve student outcomes, and prepare learners for a rapidly evolving data-driven workforce.
THRIVING AMID DISRUPTION: BUILDING FACULTY & INSTITUTIONAL CAPACITY
COHORT
Data Science
PROJECT
Southern California Consortium for Data Science
PRESENTERS
Babette Benken, Cal State Long Beach
Ladera Barbee, Long Beach City College
Richard Levine, San Diego State
Michael Ludkovski, UC Santa Barbara
Scaling an AI Writing Coach Across Institutions: A Regional Model for Faculty Learning and Curriculum Transformation
What does it take to move an AI innovation from one campus into broader practice? This session explores how UC Irvine’s PapyrusAI, an AI-powered writing coach designed to support academic writing and digital literacy, is being scaled through an intersegmental partnership with Cal State Fullerton and North Orange County Community College District. The initiative goes beyond tool adoption by pairing technology with sustained faculty professional learning that helps instructors rethink curriculum, redesign assignments, and create meaningful AI-enhanced learning experiences. Presenters will share insights from building a regional model that connects UC, CSU, and community college educators to expand responsible AI integration and support students as writers, critical thinkers, and digital citizens.
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORT
AI Grand
PROJECT
Enhancing Academic Writing and Digital Literacy with an AI Coach
PRESENTERS
Tamara Tate, UC Irvine
Beth Harnick-Shapiro, Cal State Fullerton
Stephanie Tran, Cypress College
Flipped Classroom 2.0: Learning as a Public Endeavor
How can we respond to the impacts of generative AI on student engagement without overlooking the importance of accessibility and deeper, more meaningful learning? This session shares lessons learned from a research project exploring genAI-permissive assessment across fifteen courses and introduces a framework for learning as a public exercise. Building on the principles of the flipped-classroom model, the framework emphasizes communal thinking, ongoing feedback, and authentic connections beyond the classroom. Presenters will explore how making learning visible through works-in-progress, reflection, and real-world audiences can support meaningful learning and relational accountability, as opposed to policing of student behavior. Participants will engage in interactive, collaborative case studies to identify practical strategies and key takeaways for redesigning assessments in their own contexts while considering the opportunities and limitations posed by disciplinary and institutional norms.
Designing Teaching, Learning, and Assessment for an AI-Driven World
COHORT
AI FAST
PROJECT
Creating a Framework for Valued Learning Outcomes in 2030
PRESENTER
Melissa Ko, UC Berkeley
WITH SUPPORT FROM
