Educast 3000

What makes a skill count, and how does it travel from a classroom or a kitchen table into a job? Ryan Lufkin puts that question to Glenda Quintini, who runs the OECD's Skills and Future Readiness Division in Paris, with Simone Ravaioli sitting in for Melissa. Glenda's answer starts with a confession: a few months ago she couldn't tell critical minerals from rare earths, taught herself by reading and talking to people, and never enrolled in anything. That's how most adults actually learn, and almost none of it shows up on a resume.

The conversation works through what it takes to fix that. Degrees aren't dead, Glenda argues, they're bundles of skills nobody has unpacked. The harder problem is language: employers and educators describe the same skills in completely different words, a gap she says blocks worker mobility as much as visa rules do. From there the three of them get into micro-credentials, individual learning accounts, the data behind dropped degree requirements, and why governments have to move faster than a two-year accreditation cycle.

In this episode:

• Why eliminating degree requirements barely moves non-degree hiring on its own 
• The difference between regulating credentials like New Zealand and letting the market sort it out
• Why the next 15 years will be about lifelong recognition, not just lifelong learning

For further reading: 

• A Skills-First Labour Market

"Hallucinations are not a bug in my classroom. They are the assignment." That's Giorgio Lagna's framing for one of the 13 AI tutors he's built into his biology course at Santa Clara University. In this episode of Educast 3000, the UCSF research scientist and college lecturer joins Ryan Lufkin and Zach Pendleton to walk through what happens when you design AI not to answer questions but to refuse them, not to be right but to argue back. The conversation covers his "Crucible" course design, the DISCO framework research he published this year showing measurable equity outcomes, and why he believes higher ed is making a strategic mistake by treating AI as an integrity problem instead of an assessment problem.

In this episode:

• Toll booth gems, boss battle gems, and certification gems explained
• Why deliberate AI errors teach better AI literacy than warnings about hallucinations
• The cost math on AI-powered oral exams (NYU's run came to 42 cents per student)
• How community college students are now running CRISPR research with AI co-investigators
• What Pope Leo XIV's first encyclical said about AI and education the day before this recording

• Pedagogy Under the Microscope: https://substack.com/@glagna
• Structured AI Integration for Equitable STEM Writing: A Pilot Study of the DISCO Framework: https://www.tandfonline.com/doi/abs/10.1080/0047231X.2026.2625111
• UCSF profile: https://profiles.ucsf.edu/giorgio.lagna

Further readingPope Leo’s ‘Magnifica humanitas’: AI must serve humanity not concentrate power: https://www.vaticannews.va/en/pope/news/2026-05/pope-leo-xiv-encyclical-magnifica-humanitas-ai.html

What does it actually mean to be "evidence-based"? Melissa Loble and Ryan Lufkin sit down with Mary Styers, Director of Evidence and Learning Strategy at Instructure, to find out. With 20 years in program evaluation, Mary breaks down why education's relationship with data is broken and what it takes to fix it.

The conversation covers why rigorous research means nothing if teachers aren't on board, how compliance-driven data cultures stifle real learning, and why a study with only positive results should raise red flags, not applause.
Mary also tackles the paradox of data overload: institutions have more data than ever and still can't act on it. Her answer? Start with one question. Work backward. Build psychological safety. And treat evidence as a journey, not a finish line.

Key topics:

• Why teacher buy-in matters as much as research rigor
• The difference between a compliance culture and a true culture of evidence
• Evidence literacy — what it is and why we're failing to build it
• How rapid cycle evaluation helps institutions iterate fast and learn faster
• Practical first steps for leaders who want to make evidence-driven decisions

In this special clips episode of Educast 3000, hosts Ryan Lufkin and Melissa Loble revisit some of the sharpest conversations on artificial intelligence from recent episodes. Featuring highlights from chats with Sanjay Srivastava (CEO of Vocareum), Joe Potvin (Simmons University and Cengage), Kelly Shiohira (Global Science of Learning Education Network), Matt Winters, (AI Education Specialist at the Utah State Board of Education), and Dr. Joseph Youngblood II (Chancellor of Kean Global), this episode pulls together four distinct perspectives on how AI is reshaping teaching, learning, and the institutions that deliver them. From computer science classrooms to liberal arts seminars, from neuroscience-informed frameworks to transformational learning models, our guests tackle the questions every educator is wrestling with: What should we teach? How do we assess real learning? What's the educator's role now? And what does it mean to prepare students to be responsible citizens in an AI-powered world?

Takeaways:

• AI is forcing education to answer questions it's been avoiding for decades.
• Personalization at scale is one of AI's most promising contributions to learning.
• Authentic assessment matters more than ever when AI can do the work for students.
• The educator's role is evolving, not disappearing.
• AI citizenship is as important as AI literacy.
• Liberal arts skills like critical thinking and communication are more valuable, not less, in an AI era.
• Cultural context, humility, and listening are essential to transformation.
• Frameworks like UNESCO's AI competency guides can help educators navigate the shift.
• Lifelong learning is no longer optional; it's foundational.
• The future of education depends on faculty engagement and institutional flexibility.

Featuring:

• Dr. Joseph Youngblood II, Chancellor of Kean Global
• Kelly Shiohira, director of the Global Science of Learning Education Network
• Joe Potvin, a adjuncy history professor at Simmons University and Senior Portfolio manager at Cengage
• Matt Winters, AI Education Specialist at the Utah State Board of Education
• Sanjay Srivastava, CEO of Vocareum

This episode delves into the transformative potential of experiential and apprenticeship learning models in higher education and their critical role in preparing students for the future workforce, especially amidst rapid advancements in AI. Join us as Emily Foote, Chief Growth and Strategy Officer at Saxby's, shares her insights on how institutions can systemically integrate these models for greater impact.

Main Topics:

• The resurgence of experiential and apprenticeship learning in higher education
• Driving factors behind the renewed focus on experiential models
• The impact of AI on entry-level jobs and skill development
• Transition from knowledge-based to skills-based education
• How to scale experiential learning effectively within institutions
• Developing and validating durable skills like critical thinking, resilience, and leadership
• Measuring success: assessment methods for experiential programs
• Building equitable pathways to participation in experiential learning
• Evolving faculty roles from lecturers to learning architects
• Future of experiential learning in higher education and system-level change

Show Notes:

• Labor market impacts of AI: A new measure and early evidence - https://www.anthropic.com/research/labor-market-impacts
• Shrinking Entry-Level Roles: A Stanford University analysis - https://d2zhjl04.na1.hs-sales-engage.com/Ctc/I8+23284/d2zhjl04/JlF2-6qcW8wLKSR6lZ3pZW5CRPvg52GtDSW26Y9kw5vtDdSW3lfnx11nB5kyW970xhj74Q4H0N5QP790pnqKLW2tMprh6NL3bYW5tKB851lpbDZN699P7cWv1RhW6qTl291_Lx7gW8tjYt54Gw0XPW69HzgF6qMQyZW9gkl1T14Sv-nW64m9pG2G_qrWN6q_63gvbF9HW5VLTdp4-nFFvW58gw-832lhZvW3NgDJw7BsgV9W1QZz5G6qD783W3PMdCJ4rL9WwVwBwj928NdM2W1Whd093G2GwFVrzxYr8fjrG2W1ZYkHC2BFDpyM-kMsm81BkPW8q5y5Z5hWKqBW2wgWW63M45JGW1Tyvt893Gw9nW20M7RR7J_ngKf3LPSfT04
• 81% of graduates believe they are proficient in critical thinking, but only 56% of employers agree - https://www.naceweb.org/career-readiness/competencies/the-gap-in-perceptions-of-new-grads-competency-proficiency-and-resources-to-shrink-it
• CEOs say AI isn't just a tool to help juniors; it is a tool that may eventually replace them - https://www.wsj.com/tech/ai/ai-white-collar-job-loss-b9856259?gaa_at=eafs&gaa_n=AWEtsqeq2qCrXEm-pgwHBybLZX2vTpvCg1mRRu24ZP0dGCFb8GGKvzD5fT8v3vLAOZc%3D&gaa_ts=69c1f94e&gaa_sig=1PfpR7rR1s7nRCxfYDc7HrsIQHRY2CtyOo9VVMdyxLcucxOVLtS-5s1n-tZueQC-iFkWtCsyNocF0Ts1eME9Gw%3D%3D
• Gallup study: Only 11% of business leaders believe higher ed effectively prepares graduates for work - https://www.gallup.com/education/231740/ways-realign-higher-education-today-workforce.aspx?utm_source=chatgpt.com
• Saxbys 2024-2025 Impact Report: https://21774654.fs1.hubspotusercontent-na1.net/hubfs/21774654/Saxbys%20Impact%20Report%20-%202024-2025.pdf 

In this episode, Ryan and Melissa Loble chat with Sanjay Srivastava, CEO of Vocareum, to explore the intersection of technology and education. They discuss Sanjay's journey in the tech industry, the importance of experiential learning, the impact of AI on computer science education, and the evolving role of educators in an AI-driven landscape. The conversation highlights the skills needed for future computer science graduates, the significance of authentic assessment, and the ethical considerations surrounding AI usage in education.

Takeaways:

• Experiential learning environments enhance student engagement.
• Future computer scientists must understand AI's capabilities and limitations.
• Personalization in education is a key benefit of AI.
• Authentic assessment is crucial for measuring student mastery.
• Teachers play a vital role in integrating AI into the classroom.
• AI can help reduce failure rates in education significantly.
• Ethical considerations in AI usage are paramount.

Show Notes:

• How are developers using AI? Inside our 2025 DORA report: https://blog.google/innovation-and-ai/technology/developers-tools/dora-report-2025/#:~:text=Massive%20adoption%20meets%20major%20productivity,of%20AI%20on%20code%20quality
• Vocareum @ Better Together: California Convening on AI in Higher Education: https://www.youtube.com/watch?si=HMfACp4h06PaFvFt&v=hZBYfvG7N7k&feature=youtu.be

In this episode, Melissa and Ryan are joined by Katherine Burton-Jones. Katherine discusses the intersection of museum studies and technology, sharing her journey from archaeology to teaching at Harvard Extension School. She highlights the evolution of museums over the past few decades, emphasizing the importance of human-centered learning and the challenges museums face in modernizing. The group explores how technology, including AI, can enhance the museum experience and foster social connections. 

Takeaways:

• The role of museums has evolved to become more user-centric and inclusive.
• Data collection is crucial for understanding visitor needs and behaviors.
• Technology can enhance the museum experience and make it more accessible.
• AI has potential applications in museums, but ethical considerations are important.
• Personal stories behind objects can create deeper connections with visitors.
• Museums can serve as spaces for social connection and community building.
• Curators of the future need to be data-aware and conceptually prepared.
• The future of museums lies in embracing technology while remaining inclusive.

Show Notes: 

• Katherine’s Bio: https://www.katherineburtonjones.com/ 
• The Museum of Everyday Objects: https://www.museumofeverydayobjects.org/welcome-desk 

We’re kicking off a new season of Educast 3000! In this episode, hosts Ryan Lufkin and Melissa Loble welcome back Professor Martin Bean to discuss the future of education. They explore the importance of lifelong learning, the evolution of credentials, and the need for educational institutions to adapt to the changing workforce landscape. Martin shares his personal learning moments and emphasizes the significance of recognizing prior learning. Together they discuss the need for equity in education and the vision for a connected learning system by 2026.

Takeaways

• Lifelong learning is essential for success in the modern world.
• Credentials must evolve to reflect continuous learning and skills acquisition.
• Recognition of prior learning can enhance educational pathways.
• Equity in education is crucial for inclusivity and relevance.
• Educational institutions need to adapt to the needs of adult learners.
• The future of education requires dynamic and flexible pathways.
• Assuming competence rather than deficit can transform learning experiences.
• Collaboration between educators and employers is necessary for relevance.
• Shared skill descriptors can help align education with workforce needs.
• Investing in a connected learning system is vital for future success.

In this final episode of Educast 3000 before we take a holiday break, host Ryan Lufkin and guest co-host Jody Sailor engage in a dynamic conversation with educator and consultant Katie Novak. They explore the importance of Universal Design for Learning (UDL) in creating inclusive educational environments, the need for choice and voice in learning, and the disconnect between educators' perceptions and student outcomes. Katie emphasizes the role of leadership in driving change, the necessity of support systems for educators, and the importance of collaboration between K-12 and higher education. The discussion also highlights practical steps for educational leaders to implement effective practices and transform teaching for all learners.

Takeaways

• Universal Design for Learning (UDL) aims to create inclusive learning experiences for all students.
• Educators often believe they know their students, but students may feel differently.
• Metrics for success in education need to reflect inclusive and future-ready learning environments.
• Support systems for educators are crucial for implementing UDL effectively.
• There is a disconnect between what educators believe they are doing and actual student outcomes.
• Transforming teaching practices requires abandoning outdated methods and embracing new approaches.
• Educational leaders must create clear instructional visions to guide change.
• Collaboration between K-12 and higher education can enhance learning experiences.
• Practical steps for educational leaders include setting firm goals and providing adequate support.

Key Links

• Here is a link about concern-based adoption: https://www.air.org/resource/cbam-concerns-based-adoption-model?gad_source=1&gad_campaignid=22771353292&gbraid=0AAAAADuG9jWdq_5jFKc6op3SnaJ1VH5tZ&gclid=Cj0KCQjwvJHIBhCgARIsAEQnWlDJgkM0Klo0hOhXgGB6A199OvCc9wsSo2y5oZ672kdMxth7X-8nb_8aAsrVEALw_wcB
• UDL Focus Area tool to know what to look for in universally designed classrooms: https://www.novakeducation.com/hubfs/10%20UDL%20Observations%20in%20the%20Classroom_Novak%20Education.pdf
• MTSS Self-Assessment to help districts reflect on which system drivers they have already and which they need to better support educators and students: https://7288705.fs1.hubspotusercontent-na1.net/hubfs/7288705/Resources/MTSS%20Self-Assessment_Novak%20Education.pdf
• World Economic Forum Future of Jobs Report: https://www.weforum.org/publications/the-future-of-jobs-report-2025/

In this special episode of Educast 3000, Ryan Lufkin and guest host Zack Pendleton come to you live from EDUCAUSE 2025 in Nashville, Tennessee. They’re highlight the conversations they’re hearing surrounding AI, education technology, and more at this leading higher education conference.