Educast 3000

InstructureCast
  • 5.0 (1)
  • Education
  • Updated Biweekly

Ah, education…a world filled with mysterious marvels. From K12 to Higher Ed, educational change and innovation are everywhere. And with that comes a few lessons, too. Each episode, EduCast3000 hosts, Melissa Loble and Ryan Lufkin, will break down the fourth wall and reflect on what’s happening in education – the good, the bad, and, in some cases, the just plain chaotic. This is the most transformative time in the history of education, so if you’re passionate about the educational system and want some timely and honest commentary on what’s happening in the industry, this is your show. Subscribe wherever you listen to your podcasts and join the conversation! If you have a question, comment, or topic to add, drop us a line using your favorite social media platform.

  1. 3d ago

    I, Agent: What Happens to Edtech When the User Isn't Human

    Ryan Lufkin and Melissa Loble step back this episode and hand the conversation to two technologists who interview each other. Mike Mast, Principal Group Program Manager for Microsoft Education and a 1EdTech board member, and Zach Pendleton, Chief Architect at Instructure, trade questions about what interoperability means once AI agents start acting inside the tools educators and students already use. The starting point: when the client is an agent rather than a person, agents can learn new vocabularies and reason over different systems on their own, so the hard part shifts from rigid data schemas to giving agents a real semantic understanding of a course. Mast points to Canvas by Instructure and its Smart Search beta as one of the few early examples of that idea in practice. Pendleton makes the case that none of this replaces the open standards ed tech already runs on. He frames MCP, LTI, OneRoster, and Caliper as an "and," not an "or."From there the two get into the part that keeps Pendleton up at night: as actions move further from the human who set the goal, how do we keep people in authority? They cover delegated authorization and consent, audit trails, the gap between what AI can do and what we want it to do, and who carries the cost when an automated tool gets it wrong.  In this episode:  Agentic AI changes what interoperability optimizes for, moving the priority toward semantic understanding of course content rather than identical schemas across systems.New protocols build on existing standards instead of replacing them, so prior investments in open APIs and LTI still matter.Keeping a human in control sometimes costs a little speed, and both guests argue that maximum speed should not be the goal of an educational AI system.Transparency is non-negotiable: if AI touches a grade, students should know, and they should be able to question the result.

  2. Jun 30

    Good Will Tutoring: Why the Best AI Behaves Like a Great Human Tutor

    James Genone has spent his career at the meeting point of two fields most people keep apart: philosophy and cognitive science on one side, education technology on the other. In this episode, Northeastern University's Senior Vice Chancellor for Learning Strategy joins Ryan Lufkin and Melissa Loble to argue that the design behind a tool decides whether AI deepens learning or just does the thinking for students. His test is simple: does the AI behave the way a good human tutor would? Drawing on his founding work at Minerva University, his product role at Atypical AI, and his current advising with the Digital Education Council, Collage AI, and SkillBench, James lays out what learning science actually asks of these tools and where institutions keep going wrong. In this episode: The tutor test James applies to any AI assistant: a good tutor never writes the student's essay, and the AI shouldn't eitherWhy engagement is the real engine of learning, and how connecting a subject to what a student cares about drives the attention that learning depends onHis case against grades, built on an investor analogy: you can't tell two companies apart if all you see is a letter grade, and a transcript does the same thing to studentsThe two ways institutions keep getting AI adoption wrong, either leaving faculty to fend for themselves or handing down blanket mandates, and the scaffolded, faculty-led approach he'd put in their place

  3. Jun 16

    Lost in Translation: Getting Employers and Educators to Speak the Same Language

    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 outWhy the next 15 years will be about lifelong recognition, not just lifelong learningFor further reading:  A Skills-First Labour Market

  4. Jun 2

    Catch Me If You Can: Why This Biology Professor's AI Tutors Lie on Purpose

    "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 explainedWhy deliberate AI errors teach better AI literacy than warnings about hallucinationsThe 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-investigatorsWhat Pope Leo XIV's first encyclical said about AI and education the day before this recording Pedagogy Under the Microscope: https://substack.com/@glagnaStructured AI Integration for Equitable STEM Writing: A Pilot Study of the DISCO Framework: https://www.tandfonline.com/doi/abs/10.1080/0047231X.2026.2625111UCSF profile: https://profiles.ucsf.edu/giorgio.lagnaFurther 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

  5. May 19

    Everything Everywhere All at Once: Making Sense of Data Overload in Education

    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 rigorThe difference between a compliance culture and a true culture of evidenceEvidence literacy — what it is and why we're failing to build itHow rapid cycle evaluation helps institutions iterate fast and learn fasterPractical first steps for leaders who want to make evidence-driven decisions

  6. May 5

    The AI-list: A Clips Episode on AI Across the Classroom

    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 GlobalKelly Shiohira, director of the Global Science of Learning Education NetworkJoe Potvin, a adjuncy history professor at Simmons University and Senior Portfolio manager at CengageMatt Winters, AI Education Specialist at the Utah State Board of EducationSanjay Srivastava, CEO of Vocareum

  7. Apr 21

    Raiders of the Lost Apprenticeship: How Student Leadership and Experiential Learning are Driving Workforce Success

    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 educationDriving factors behind the renewed focus on experiential modelsThe impact of AI on entry-level jobs and skill developmentTransition from knowledge-based to skills-based educationHow to scale experiential learning effectively within institutionsDeveloping and validating durable skills like critical thinking, resilience, and leadershipMeasuring success: assessment methods for experiential programsBuilding equitable pathways to participation in experiential learningEvolving faculty roles from lecturers to learning architectsFuture of experiential learning in higher education and system-level changeShow Notes: Labor market impacts of AI: A new measure and early evidence - https://www.anthropic.com/research/labor-market-impactsShrinking 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_ngKf3LPSfT0481% 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-itCEOs 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%3DGallup 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.comSaxbys 2024-2025 Impact Report: https://21774654.fs1.hubspotusercontent-na1.net/hubfs/21774654/Saxbys%20Impact%20Report%20-%202024-2025.pdf

  8. Apr 7

    Code-ablanca: Rethinking Computer Science Education and the Future of Learning Code

    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%20qualityVocareum @ Better Together: California Convening on AI in Higher Education: https://www.youtube.com/watch?si=HMfACp4h06PaFvFt&v=hZBYfvG7N7k&feature=youtu.be

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About

Ah, education…a world filled with mysterious marvels. From K12 to Higher Ed, educational change and innovation are everywhere. And with that comes a few lessons, too. Each episode, EduCast3000 hosts, Melissa Loble and Ryan Lufkin, will break down the fourth wall and reflect on what’s happening in education – the good, the bad, and, in some cases, the just plain chaotic. This is the most transformative time in the history of education, so if you’re passionate about the educational system and want some timely and honest commentary on what’s happening in the industry, this is your show. Subscribe wherever you listen to your podcasts and join the conversation! If you have a question, comment, or topic to add, drop us a line using your favorite social media platform.

Information

  • Creator
    InstructureCast
  • Years Active
    2024 - 2026
  • Episodes
    50
  • Rating
    Clean
  • Copyright
    © 2008-2024 Instructure, Inc.
  • Show Website
    Educast 3000