Practical Pedagogy: The Art of Teaching for the Future of Work

Anika Jackson
  • 5.0 (1)
  • Education
  • Updated Weekly

Preparing students and working professionals for the future of work means teaching with AI, not just about it. Practical Pedagogy brings together educators, researchers, and industry leaders reimagining what it means to teach and learn in an AI-integrated world. Each week, we explore real conversations happening in classrooms, boardrooms, graduate seminars, and workplaces: How do we guide learners toward thoughtful, strategic AI collaboration? What does pedagogy look like when AI tools evolve faster than curriculum? And what skills actually matter when generative AI can handle the rest? You'll hear from professors redesigning courses around AI literacy, students learning responsible AI use, working professionals navigating upskilling and career transitions, researchers uncovering what works, and industry leaders hiring for skills that don't exist in textbooks yet. Whether you're in K-12 education, higher education, corporate learning and development, or figuring out your next chapter, this show is about preparing for—and thriving in—work being redefined in real time. Our approach is practical and relaxed. We're as interested in failures and lessons learned as we are in wins. Because the question isn't whether to embrace AI or resist it. It's how we prepare learners of all kinds to evolve alongside it. For educators, students, working professionals, researchers, and anyone curious about the future of learning and work.

Episodes

  1. 6d ago

    Offline-First Learning: Ryan Ross on the AI Infrastructure Crisis

    Offline-First Learning: Ryan Ross on the AI Infrastructure Crisis   Anika sat down with Ryan Ross to explore a critical, often-overlooked question in the education technology debate: Can your school's infrastructure actually run AI? The conversation revealed a sobering reality regarding the global digital divide and the massive data requirements of modern AI. Ryan’s background in edge computing and fintech at Visa offered a practical blueprint for offline-first learning, highlighting how Small Language Models (SLMs) and edge networks are the true key to bringing digital resources to the students the internet forgot.   In This Episode Transitioning from fintech at Visa to edtech and what education can learn from global payment networks The creation of the Olivia Education Edge Network and the power of offline-first learning Early deployment in East Texas and Hawaii, and the surprising "walled garden" benefit for classroom focus The impending AI infrastructure crisis: how token consumption and broadband limits will break school budgets Why Small Language Models (SLMs) solve the data sovereignty and policy compliance issues for districts Partnering with Utah Tech to deliver associate degrees to incarcerated youth inside secure juvenile facilities Scaling digital access across Africa and fixing internet-less computer labs Key takeaways from the UN's "AI for Good" summit in Geneva regarding global infrastructure disparities Practical, low-budget steps for educators to begin adopting AI this semester The guiding philosophy of putting "teachers first" in any technology rollout   Timestamps 00:00 Introduction: Can your school's infrastructure even run AI? 01:18 The Visa connection: Applying payment terminal edge networks to classrooms 04:18 Early use cases: Bridging the home broadband gap in East Texas and Hawaii 08:10 Scaling to enterprise and realizing the impending AI data crisis 10:27 Token consumption and why policy means nothing without infrastructure 14:49 Why Small Language Models (SLMs) are the safest path for school districts 16:57 The Utah Tech partnership: Bringing digital education into secure juvenile facilities 20:39 Deploying in Africa: The reality of scaling digital resources with minimal bandwidth 26:39 Why AI will never replace teachers and the realities of K-12 adoption 29:42 Insights from the UN "AI for Good" summit: The massive global infrastructure deficit 34:36 Practical steps for educators feeling behind on the AI curve 38:05 The guiding principle: Why successful edtech must put teachers first   Key Insights & Takeaways   Insight 1: Infrastructure Precedes Policy  School districts and legislators can draft all the AI policies they want regarding data sovereignty and usage, but without the broadband to support it, the policies are useless. Global estimates discussed at the UN summit show that 80% of schools worldwide lack the infrastructure for viable AI, meaning the real frontier of educational technology is access, not algorithms.   Insight 2: Edge Computing is the Education Solution  Drawing from Visa's global payment terminal model, offline-first networks allow schools to sync data locally. This middleware approach allows a school of 500 students to access digital resources, videos, and learning management systems on a localized network without crippling the school's limited live bandwidth.   Insight 3: The Hidden Threat of Token Consumption  Adding generative AI to schools isn't just a broadband issue—it's a massive, unpredictable budget issue. A single school of 500 students could burn through up to 5 billion tokens in a year. Traditional OpenAI models are financially and logistically unscalable for the average, under-resourced public school district.   Insight 4: Small Language Models (SLMs) Offer Total Control  Large language models pose massive data privacy and intellectual property risks for universities and K-12 schools alike. By utilizing Small Language Models managed at the district or state level, schools can strictly control the ingested content, perfectly align it with state standards, and safeguard student data in a closed environment.   Insight 5: EdTech Must Put Teachers First  AI will not replace educators, because teaching is fundamentally rooted in human interaction. True AI adoption in the classroom will only happen when tools are explicitly designed to reduce educator workload, assist in curriculum alignment, and increase teacher productivity before being pushed to the students.   Resources & Links Mentioned   Olivia Technologies (Olivia Education Edge Network) Utah Tech University (Juvenile justice education partnership) UN "AI for Good" Summit in Geneva   About Ryan Ross   Ryan Ross is the founder and CEO of Olivia Technologies and the creator of the Olivia Education Edge Network. With a deep background in edge computing, fintech, and biometric authentication at Visa, he transitioned into edtech to solve the digital divide. His offline-first platforms bring critical digital learning and AI capabilities to students in under-connected environments—from rural American school districts and secure juvenile justice facilities to schools across Africa.   His core mission, Ryan notes:  "Two projects I am particularly passionate about are Olivia's work with Utah Tech University supporting justice-impacted and incarcerated youth, and our efforts across Africa to improve access to digital learning resources for schools with limited connectivity. Both initiatives reinforce a core belief: technology should expand educational opportunity, not create new barriers. Whether supporting students in secure learning environments or schools that lack reliable internet access, our focus is on delivering equitable access to learning, empowering teachers, and ensuring that every student has the opportunity to succeed regardless of their circumstances or location."   Connect with Ryan LinkedIn: https://www.linkedin.com/in/rossrr3/ Olivia Technologies Website: https://www.olivia.school/

    Offline-First Learning: Ryan Ross on the AI Infrastructure Crisis

  2. Jul 16

    Non-Negotiable Rules for AI in Education with Dave Oates

    Anika sat down with Dave Oates to explore a counterintuitive truth: in an era of AI disruption, critical thinking has become your most defensible asset. Dave shares his transformational journey from Navy public affairs officer to crisis PR expert to educator—revealing why asking the right questions is the only intellectual differentiator AI cannot replace. He introduces three non-negotiable conditions for AI in the classroom—citation, source validation, and the why behind every answer—and discusses why institutions that swing from banning AI to embracing it overnight are doing students a disservice. The conversation challenges how universities teach responsible technology use alongside critical thinking, and exposes why most educators remain trapped in memorization-based curricula built on fear instead of passion.   In This Episode   The origin of Dave's crisis PR expertise: 30 years navigating institutional reputational crises  Why institutions overestimate AI risk and the calculator debate of the 1960s   Making AI your employee, not your boss: a student's brilliant reframe  The San Diego State pivot: from banning AI mid-semester to embracing it   Why AI is a "dumb machine" that hallucinates and can't evaluate truth  The three non-negotiable conditions for AI in the classroom: citation, source validation, and the why   How assignments that demand reasoning expose AI misuse immediately   The "learn-do model": why application and mastery require more than AI-generated answers   Real-world engagement: interviews, surveys, and relationships that AI cannot replace  The experiential imperative: why showing up and being confidently vulnerable transforms learning   Why memorization-based education is dead and critical thinking is essential  Trust through accessibility: responding within one business day and personal connection  Your identity is your differentiator: the closing philosophy on what matters most     Timestamps   01:25-02:31 The calculator debate of the 1960s: what tech panic teaches us about today's AI fears 03:11-03:53 "Make it your employee, not your boss"—a student's brilliant reframe that changed everything 04:46-06:24 San Diego State's radical shift: banning AI to embracing it mid-semester and the confusion that followed 06:42-08:48 Why AI is fundamentally limited: it hallucinates and can't evaluate truth 12:12-12:51 The three non-negotiable conditions: citation, source validation, and explaining your reasoning 15:38-18:25 The learn-do model: why mastery requires application to what you're passionate about 19:21-20:31 Nothing beats real relationships: interviews, surveys, and human engagement that AI can't replace 21:51-22:47 Redefining failure: it's only when you don't show up and don't engage 36:25-37:06 Memorization is dead: when you have AI, critical thinking becomes the only differentiator 38:12-40:07 Trust is built through accessibility: one business day response time and genuine enthusiasm 41:25-42:17 "You still matter if you show up"—the mantra that transcends AI and education   Key Insights & Takeaways   Insight 1: We've Been Here Before—And We Survived The calculator debate of the 1960s mirrors today's AI panic. People feared calculators would make us dumb. Fifty years later, we know tools don't diminish us when we understand how they work. As Dave explains: "The calculator didn't make us dumb. It is a tool set...people who are operating the calculator have to know the fundamental workings and engine on that to back up the reasoning for the calculations." AI is the same. The question isn't whether to use it—it's whether we know what we're doing when we do.   Insight 2: AI Is a Dumb Machine That Looks Smart AI synthesizes information eloquently but doesn't rank it, evaluate truth, or catch its own hallucinations. It makes things up when it doesn't know answers. Dave warns: "It's not evaluating whether something is true or not...probably the biggest thing I think it does that we've all been talking about even more so is it just makes shit up. If it doesn't have something, it just hallucinates." An organization that hands an AI-generated crisis statement to executives without human review will create more damage than the original crisis.   Insight 3: Assignments That Ask "Why" Expose AI Misuse Immediately If your assignment asks students to regurgitate facts, AI wins and you won't know. If your assignment demands reasoning, conviction, and original thought backed by research, cheating becomes obvious. Dave illustrates: "If we have as instructors, assignments that basically want students to just regurgitate facts...AI is going to be fine...But the common theme with all of those is I'm teaching critical thinking, I'm teaching why, and I'm teaching them to take chances." The problem isn't AI—it's how we design learning.   Insight 4: Citation and Rationale Transform AI From Crutch to Tool Students must cite when they use AI and explain why they chose to use it. Dave's framework: "A, you have to cite that you used it...B, you have to tell me why I think it's okay for you to use AI." This teaches professional accountability: in the real world, you'll need to defend every choice you made, including which tools you used to make it.   Insight 5: Mastery Requires Application Beyond Information  AI can provide information instantly. But retention, understanding, and mastery come through the "learn-do model"—learning something and then applying it to what you're passionate about. Dave requires students to conduct real interviews, do surveys, and engage with actual professionals. This real-world data often contradicts what AI suggests—and that's the learning moment.   Insight 6: Nothing Beats the Art of Relationships  AI can't conduct interviews. It can't do surveys. It can't build the trust that comes from showing up in person and being vulnerable. Dave emphasizes: "Nothing still beats the art of relationships...You got to get out there and actually talk to people." That human data often contradicts what AI suggests—and that's where real learning happens.   Insight 7: Redefining Failure Transforms Student Engagement  Dave's philosophy: "The second thing that we teach above all else is the imperative art of showing up...Failure is only when you decide not to show up and not engage, because now you didn't even try." Students engage because they see an instructor who cares. Trust isn't built through policy—it's built through showing up, being accessible, and demonstrating genuine enthusiasm.   Insight 8: Memorization Is Dead; Critical Thinking Is Essential The old model of teaching facts is obsolete. Dave declares: "I don't need memorization anymore. When I have at my FingerTips a generative LLM model and even a Boolean search model...I'm teaching critical thinking, and my assignments are architected accordingly." This shift isn't optional—it's survival.   Insight 9: Trust Is Built Through Presence and Passion  Dave's secret to building trust with 116 students: "I am accessible to you outside of class...I promise you I will respond within one business day, no later...If I'm not passionate about what I'm teaching, the kids are going to follow suit...I have name cards for every one of the kids...I'm trying to break that distance, that barrier between the instructor and the students." This transforms large classes into intimate learning communities.   Resources & Links San Diego State University School of Journalism & Media Studies: https://journalism.sdsu.edu/ Dave's Teaching Focus Areas: Advertising Media Studies Public Relations   About Dave Oates   Dave Oates is a crisis PR expert with 30 years of experience across military, corporate, nonprofit, and education sectors. He served as a U.S. Navy public affairs officer before building a career helping institutions navigate reputational crises through transparency and accountability. For the past three years, he has been a part-time lecturer at San Diego State University, teaching advertising, media studies, and PR to undergraduate and graduate students.   His guiding principle—"Respect tradition, embrace tomorrow"—defines his strategic, thoughtful approach to emerging technologies like AI, viewing them not as threats but as tools that amplify great teaching.   His mission: Help students and professionals understand that AI is a tool to enhance thinking, not replace it—and that showing up with passion and conviction is the only economic differentiator that matters.   Connect with Dave Oates   San Diego State University: https://www.sdsu.edu/  LinkedIn: https://www.linkedin.com/in/davidoates/

    Non-Negotiable Rules for AI in Education with Dave Oates

  3. Jul 9

    Vocating Your Way Through AI with Florian Kemmerich

    Anika sat down with Florian Kemmerich to explore a counterintuitive truth: in an era of AI disruption, your identity has become your most defensible asset. Florian shares his transformational journey from bullied child to judo champion, paratrooper, and impact investor—revealing why self-knowledge is the only economic differentiator AI cannot replace. He introduces "vocating," a framework for aligning professional life with authentic identity, and discusses the Vocating AI platform designed to help students and professionals discover their true calling in minutes rather than years. The conversation challenges how universities teach purpose alongside technology, and exposes why most people remain trapped in careers built on fear instead of love.   In This Episode   The connective tissue: How a childhood imprint at age 5 shaped every major life decision   Confronting fear: Why Florian chose judo, then paratroopers, then impact investing—always putting himself at risk   Leaving the golden handcuffs: The moment at age 33 when inner child work revealed he was living someone else's life  The vocating framework: How ikigai became livable through four components—identity, meaning, impact, and livelihood  The Vocating AI platform: Using agentic AI with agents trained on psychology, transactional analysis, and Enneagram to compress years of self-discovery into minutes   Real-time testing: 100 students from 20 universities currently testing the app, providing feedback for scientific validation  The cost of misalignment: How organizations lose money and talent when people aren't aligned with their work   Three exercises to start: Cut out the noise, remember your earliest childhood memory, imagine your deathbed, then bring it to today   The AI disruption moment: When Florian automated 70% of jobs and realized millions would face the same displacement The second book: Vocating Organizations coming September/October, focused on how business leaders can leverage vocating for competitiveness     Key Insights & Takeaways   Insight 1: Your Imprint Shapes Your Life's Meaning Between ages 2-6, something happens to you that gives your life meaning and stays with you forever. For Florian, bullying at age 5 became his imprint: not fear, but a question: "Why are they mean to me?" That single moment connected every major decision that followed—from judo to paratroopers to impact investing. The connective tissue isn't luck. It's confronting the fear that defines you.   Insight 2: Vocating Is a Verb—Do Both Things at Once Most people think "job," "career," or "calling." Florian reframes it entirely. Vocating means dedicating yourself professionally to your vocate—your identity, personality, and inner calling—while making a living. Education teaches the opposite: succeed first (fame, fortune, power), then give back. But that path feeds only your ego and leads to burnout. When you vocate, you do both things simultaneously.   Insight 3: Self-Knowledge Is the Economic Differentiator in the AI Era AI disrupts knowledge work, entry-level jobs, and linear careers. The one thing AI cannot replace is your identity. When you don't know who you are, you ask the machine. When the machine decides your fate, an algorithm—not you—controls your life. Your identity has become a key economic value driver. That's why vocating education is now essential.   Insight 4: Burnout Signals Misalignment Between Fear and Love You make decisions based on fear (ego, fame, fortune, power) or based on love (intuition, authenticity, contribution). A doctor who became one because their parent was a doctor will burn out. A musician chasing rock star status will end up in drugs. The same job, done from love instead of fear, becomes fulfilling. Burnout isn't a productivity problem—it's a signal you're living someone else's life.   Insight 5: Misalignment in Organizations Costs Real Money When people aren't aligned with their work, organizations suffer. Shifting from shareholder value to stakeholder value—where egos come down and empathy goes up, where diverse teams matter, where intrinsic motivation drives performance—changes everything. Net promoter scores go up. Business performance improves. It doesn't matter what sector you're in.   Insight 6: The Future Belongs to Purpose-Driven People Only two groups will succeed economically in the AI era: neurodivergent people (who always knew they were different) and purpose-driven people (who know what they want). Everyone else will ask technology to solve their problem. Technology becomes either a tool or a crutch. The differentiator is knowing your vocate first.   Resources & Links Vocating AI Platform: Testing phase with 100 students from 20 universities First Book: Published by Routledge (available on Amazon, Apple Books) Second Book: Vocating Organizations (September/October 2026)   About Florian Kemmerich   Florian is a Swiss-based impact investor, author, and founder of the Vocating AI platform. Over 25+ years, he has deployed close to a billion dollars in impact capital across Africa, Asia, and Latin America, served on multiple boards across four continents, and guided 200+ people toward discovering their vocate. He's authored the first book on vocating and is completing a second on vocating organizations. He's also a father of five, multilingual, and operates across four continents.   His mission: Help millions discover who they are and how to make a living aligned with their authentic identity—before AI makes that choice for them.   Connect with Florian LinkedIn: https://www.linkedin.com/in/floriankemmerich/ Vocating Platform: https://vocating.ai/ Books: https://on-vocation.com/

    Vocating Your Way Through AI with Florian Kemmerich

  4. Jul 2

    Kirk Spahn on AI and the Future of Learning

    Kirk Spahn has spent 25 years building schools around passion and character—long before AI became the conversation everyone's having. What struck me in talking with him is that he's not afraid of AI or naive about it. He's asking a different question than most educators: instead of "How do we protect students from AI?" he's asking "How do we prepare students to think critically while using it?" His framework—passion-based learning, character development, real-world application—actually gets stronger with AI, not weaker. If you're a parent, educator, or leader trying to figure out what education should actually look like right now, this is essential listening.   In This Episode The origin of ICL Academy in 2001 and passion-based learning Why traditional education was designed for a different era (and why that matters now) How personalization at scale becomes possible through technology—without replacing teachers The "learn-do model": why application and mastery require more than AI-generated answers Why he's building curriculum with "find the flaws" assignments instead of banning AI The immersive potential of VR/XR in education—and why it still needs a human guide His three-pillar framework: inspire, educate, impact Why "dare to dream" and "courage to risk" are non-negotiable for the next generation   Timestamps 00:00 Introduction: Education and AI in the modern era 02:12 The founding of ICL Academy in 2001 and passion-based learning 05:37 ICL Academy's educational approach and personalization 13:40 Early stage AI use in education and critical thinking 20:51 Balancing AI and human elements in learning 22:17 Building curriculum with "find the flaws" AI exercises 26:16 Emerging technologies: XR/VR for immersive learning 27:37 Exploring and piloting virtual labs and simulations 31:32 Core educational principles: "Respect tradition, embrace tomorrow" 34:15 Dare to dream, courage to risk, and leadership through action 38:25 Closing thoughts on preparing the next generation   Key Insights & Takeaways   Insight 1: AI Amplifies Great Teaching—It Doesn't Replace It   The fear that AI will make teachers irrelevant misses the point entirely. What AI actually does is free great teachers from administrative burden so they can spend time in meaningful one-on-one conversations with students. The human elements—mentorship, dialogue, knowing your students deeply—remain irreplaceable. Technology is a stage; the teacher is still the performer.   Insight 2: Engagement Is the Single Greatest Detriment (and Opportunity) in Modern Education   Students don't disengage because education is too hard. They disengage because it's disconnected from what they care about. When a tennis player learns physics through serving, when a musician explores math through acoustics, engagement transforms. Personalization isn't innovative—it's obvious. The barrier was always logistics, which technology can now solve.   Insight 3: We're in AI 1.0—Teaching Critical Thinking Matters More Than Banning It   Comparing AI to the early internet or the first calculators, Kirk argues we're at day one. Yes, students can use it to cheat. Yes, it gets things wrong. But the answer isn't restriction—it's teaching students to interrogate AI outputs, to find flaws, to understand both its power and its limitations. This generation will work with AI their entire careers; they need to learn how to use it as a tool, not a shortcut.   Insight 4: Mastery Requires Application Beyond Information   AI can provide information instantly. But retention, understanding, and mastery come through the "learn-do model"—learning something and then applying it to what you're passionate about. A student can get an AI-generated answer to a math problem; mastery happens when they apply that math to solve a real problem in their life.   Insight 5: Certain Subjects Require Limiting AI to Protect Authentic Learning   Just as some math classes prohibit calculators while others require them, some courses at ICL intentionally limit AI use. Leadership classes, for example, require deep personal reflection that can't be outsourced. The strategy isn't "no AI ever"—it's thoughtful decisions about when technology serves learning and when it gets in the way.   Insight 6: The Future of Education Is Hybrid, Not Either/Or   Traditional schools won't disappear. But the future includes more flexibility, more personalization, more opportunities for students to learn outside four walls. Athletes need training time. Musicians need practice schedules. Why force all learning into an 8am-3pm box? Technology makes hybrid models possible—but only if we design them around student identity, not efficiency.   Why This Matters Now Education is at an inflection point. We can double down on the industrial model—standardized tests, one-size-fits-all curriculum, AI as a replacement for teachers. Or we can use technology to finally do what we've always known works: meet students where they are, connect learning to their passions, and develop not just their minds but their character. Kirk's 25-year track record suggests the second path isn't just more humane—it's more effective.   Resources & Links Mentioned ICL Academy — Passion-based online learning for students with demanding schedules  ICL Foundation — Character development and educational innovation  Virtual Reality in Education — Meta Campus and XR/VR learning experiences International Baccalaureate (IB) — Global educational framework   About Kirk Spahn A fourth-generation educator and founder of ICL Academy and the ICL Foundation, Kirk Spahn has spent over 25 years pioneering passion-based learning models that prioritize student identity and character alongside academics. Growing up in an International Baccalaureate family, he recognized early that education must look at the person first—creating critical thinkers prepared for real-world challenges. As one of the earliest pioneers of online private education in the U.S., Kirk built ICL to serve high-performing students (junior athletes, musicians, performers) whose passions demand flexibility traditional schools cannot provide. His guiding principle—"Respect tradition, embrace tomorrow"—defines his strategic, thoughtful approach to emerging technologies like AI, VR, and XR, viewing them not as threats but as tools that amplify great teaching.   Connect with Kirk Spahn   ICL Academy  ICL Foundation  LinkedIn

    Kirk Spahn on AI and the Future of Learning

  5. Jun 27

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  • 5 Episodes

About

Preparing students and working professionals for the future of work means teaching with AI, not just about it. Practical Pedagogy brings together educators, researchers, and industry leaders reimagining what it means to teach and learn in an AI-integrated world. Each week, we explore real conversations happening in classrooms, boardrooms, graduate seminars, and workplaces: How do we guide learners toward thoughtful, strategic AI collaboration? What does pedagogy look like when AI tools evolve faster than curriculum? And what skills actually matter when generative AI can handle the rest? You'll hear from professors redesigning courses around AI literacy, students learning responsible AI use, working professionals navigating upskilling and career transitions, researchers uncovering what works, and industry leaders hiring for skills that don't exist in textbooks yet. Whether you're in K-12 education, higher education, corporate learning and development, or figuring out your next chapter, this show is about preparing for—and thriving in—work being redefined in real time. Our approach is practical and relaxed. We're as interested in failures and lessons learned as we are in wins. Because the question isn't whether to embrace AI or resist it. It's how we prepare learners of all kinds to evolve alongside it. For educators, students, working professionals, researchers, and anyone curious about the future of learning and work.

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