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Building tomorrow’s workforce starts with more than just technical skills—it requires access, mentorship, and leaders willing to invest in students long before they enter the job market.
In this episode of The TechEd Podcast, Mary Ellen Stanek, Co-Founder and CIO Emeritus of Baird Asset Management, shares how one of the nation’s most respected investment firms thinks about talent, education, and inclusion. She reflects on being the first woman to chair a major civic leadership group, the creation of the award that now bears her name for advancing diversity in corporate governance, and how internships are shaping the next generation of professionals.
Mary Ellen also unpacks how AI is changing finance while elevating the need for human judgment, and why Baird invests millions into education initiatives that expand opportunity—programs like Cristo Rey’s work-study model, All-In Milwaukee’s 90% college graduation rate, Aug Prep’s innovative K-12 approach, and major scholarship funds at Marquette.
For educators, employers, and community leaders, this conversation is a roadmap for how business and education can work together to prepare students for meaningful careers and stronger communities anywhere.
Listen to learn:
3 Big Takeaways from this Episode:
1. Internships are one of the most effective ways to build a talent pipeline. Baird received over 32,000 applications for internships this year and hired just 1%, bringing in 300 students across the firm. About 40% of those rising seniors secure full-time roles, proving the long-term workforce impact of investing in student opportunities.
2. Inclusion in leadership transforms organizations and opens doors for others. Mary Ellen began her career as one of the only women in the room, later becoming the first woman to chair the Greater Milwaukee Committee. Today, Baird counts nearly 100 female managing directors, and the Mary Ellen Stanek Award continues to honor leaders driving diversity in corporate governance.
3. Education investments create measurable results for students and communities. All-In Milwaukee reports a 90% six-year college graduation rate, with 84% of scholars leaving school debt-free and 91% employed or in graduate programs. Similar investments in Cristo Rey, Aug Prep, and Marquette scholarships demonstrate how targeted support leads to stronger career pathways and local economic growth.
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Distributed manufacturing allows goods to be produced closer to where they’re needed — but enabling that future requires a complete rethink of infrastructure, systems, and workforce development.
In this episode of The TechEd Podcast, Dr. Charles Johnson-Bey joins host Matt Kirchner for a deep dive into Engineering the Future of Distributed Manufacturing — the new national report from the Engineering Research Visioning Alliance (ERVA). Charles, a former professor and recently retired Senior Vice President at Booz Allen Hamilton, brings decades of experience in defense, systems engineering, and academia to this conversation.
Together, they break down ERVA’s five priority areas for enabling distributed manufacturing: modular and reconfigurable infrastructure, digital design tools, edge-to-cloud data systems, workforce education, and new performance metrics. Charles also shares how these priorities came from input across industry, academia, and government — and how they’ll guide research, funding, and education in the years ahead.
Listen to learn:
3 Big Takeaways from this Episode:
1. Distributed manufacturing is a modular approach to resilient, tech-enabled production. Charles defines distributed manufacturing as a system where production assets can be easily moved, reconfigured, and localized closer to the point of need. He describes how smaller, agile, and digitally connected systems—like reconfigurable machines and regional testbeds—enable manufacturing to respond to disruptions, like the ones exposed during COVID-19.
2. The workforce of the future needs digital fluency—and systems thinking. Students must be prepared not only to operate new technologies, but to understand how those technologies interact within broader systems. Charles highlights the importance of human-machine teaming, digital twins, and cyber-physical testbeds, and calls for education that helps learners “fall in love with the rigor” of complex technical work.
3. America’s manufacturing strategy must include small and mid-sized firms. Charles points out that most manufacturers in the U.S. are small to mid-sized, yet lack access to advanced infrastructure and scalable tools. He argues that national strategies must focus on democratizing technology—making AI, automation, and data systems affordable and available to all levels of the manufacturing sector.
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Workforce systems are often fragmented—built around short-term funding, disconnected programs, and a lack of coordination between industry, education, and community.
But a different model is taking shape - one that’s not only working in practice, but has the potential to scale across states and regions. In this episode of The TechEd Podcast, host Matt Kirchner sits down with Lindsay Blumer, President & CEO of WRTP | BIG STEP, to explore how her organization is building a future-ready, industry-led, and worker-centered workforce ecosystem.
Backed by a $10 million grant, Lindsay and her team are launching the Apprenticeship Pathway Coalition Initiative (APCI)—a five-year effort to expand apprenticeship pathways into emerging industries, strengthen regional partnerships, and create a scalable blueprint for workforce development in both urban and rural communities. From infrastructure and manufacturing to healthcare and IT, this episode explores how WRTP is aligning training, policy, and industry needs to meet the challenges of today’s labor market—and what other states can learn from it.
Listen to learn:
3 Big Takeaways from this Episode:
1. A scalable workforce model starts with alignment, not duplication. WRTP | BIG STEP acts as a “workforce intermediary,” connecting education, labor, employers, and community organizations to create coordinated talent pipelines across regions. Their funding model blends federal, state, philanthropic, and employer-based sources—like the cents-per-hour contribution from union contractors—to sustain long-term collaboration and flexibility.
2. Modern apprenticeships go far beyond the trades. Lindsay explains that apprenticeships now exist in fields like healthcare, IT, agriculture, marketing, and education, expanding far beyond traditional construction roles. She points out that 55% of new jobs in the next decade won’t require a college degree—making earn-and-learn models more relevant than ever.
3. If you want to replicate success, start by listening. WRTP’s statewide initiative begins with asset mapping and community conversations, not pre-built solutions—because what works in one region may not work in another. Lindsay emphasizes that local lived experience must inform system design, and that conveners should be flexible enough to lead, support, or step back depending on the context.
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What happens when a world-class mathematician meets ’80s college radio, Bill Gates’ top-10 favorite books, and a host with an algebra redemption arc? A surprisingly funny, fast-moving conversation. Dr. Jordan Ellenberg—John D. MacArthur Professor of Mathematics at UW–Madison and author of How Not to Be Wrong—swaps stories about The Housemartins, consulting on NUMB3RS (yes, one of his lines aired), and competing at the International Mathematical Olympiad. There’s a lot of laughter—and a fresh way to see math as culture, craft, and curiosity.
But we also get practical about math education. We discuss the love/hate split students have for math and what it implies for curriculum design; a century of “new” methods (and if anything is truly new); how movie tropes (Good Will Hunting, etc.) shape student identity in math; soccer-drills vs scrimmage as a frame for algebra practice and “honest” applications; grades as feedback vs record; AI shifting what counts as computation vs math; why benchmarks miss the point and the risk of lowering writing standards with LLMs; and a preview of Jordan’s pro-uncertainty thesis.
Listen to Learn:
3 Big Takeaways from this Episode:
1. Math mastery comes from practice plus meaning, not a “born genius.” Jordan puts it plainly: “genius is a thing that happens, not a kind of person,” and he uses the soccer drills vs scrimmage analogy to pair targeted practice with real tasks, with algebraic manipulation as a core high school skill. He urges teachers to “throw a lot of spaghetti at the wall” so different explanations land for different students, because real innovation is iterative and cooperative.
2. Students fall off at fractions and Algebra I. How do we pull them back? Jordan names those two moments as the big off-ramps and points to multiple representations, honest applications, and frequent low‑stakes practice to keep kids in. Matt’s own algebra story shows how a replacement policy turned failure into effort and persistence, reframing grades as motivation rather than just record‑keeping.
3. AI will shift our capabilities and limits in math, but math is still a human task. Calculators and Wolfram already do student‑level work, and Jordan argues benchmarks like DeepMind vs the International Mathematical Olympiad matter less than whether tools help create new mathematics. He also warns against letting LLMs lower writing standards and says the real test is whether these systems add substantive math, not just win contests.
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If you still picture farming as dusty tractors and endless manual labor, think again. Today’s agriculture runs on GPS-guided equipment, drones, real-time soil sensors, and data systems that look more like Wall Street trading floors than old barns. In this episode, lifelong farmer and innovator Dick Pavelski and Andy Diercks of the Food + Farm Exploration Center pull back the curtain on precision agriculture—the technology, data, and processes that are transforming how we grow and deliver food.
We break down the technologies making precision agriculture possible, from variable rate irrigation to “see and spray” weed control, and how data is being used to make decisions at the square-meter level. We also examine how these shifts are influencing agricultural careers, the skills now in demand, and why public understanding of modern farming is critical. Plus, discover the Food + Farm Exploration Center and its role in showing students, families, and policymakers what modern farming really involves.
Listen to learn:
3 Big Takeaways from this Episode:
1. Modern agriculture is driven by technology and precision. GPS-guided equipment, variable rate irrigation, and “see and spray” weed control have replaced much of the manual labor and guesswork of past decades. These tools work together to improve yields, reduce inputs, and create a more sustainable and efficient farming process.
2. Data is the backbone of today’s farm operations. Farmers track weather, soil conditions, and crop needs in real time—often down to individual square meters—using hundreds of sensors and automated systems. This constant stream of information enables faster decision-making and more targeted resource use than was possible a generation ago.
3. The skills and careers in agriculture are rapidly changing. Large-scale farms now employ specialists in data analysis, equipment maintenance, and automation, while mid-sized operations require workers with diverse technical abilities. The Food + Farm Exploration Center is working to show students, families, and policymakers the realities of these careers and the opportunities they offer.
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In schools with limited resources, large class sizes, and wide differences in student ability, individualized learning has become a necessity. Artificial intelligence offers powerful tools to help meet those needs, especially in underserved communities. But the way we introduce those tools matters.
This week, Matt Kirchner talks with Sam Whitaker, Director of Social Impact at StudyFetch, about how AI can support literacy, comprehension, and real learning outcomes when used with purpose. Sam shares his experience bringing AI education to a rural school in Uganda, where nearly every student had already used AI without formal guidance. The results of a two-hour project surprised everyone and revealed just how much potential exists when students are given the right tools.
The conversation covers AI as a literacy tool, how to design platforms that encourage learning rather than shortcutting, and why student-facing AI should preserve creativity, curiosity, and joy. Sam also explains how responsible use of AI can reduce educational inequality rather than reinforce it.
This is a hopeful, practical look at how education can evolve—if we build with intention.
Listen to learn:
3 Big Takeaways:
1. Responsible AI use must be taught early to prevent misuse and promote real learning. Sam compares AI to handing over a car without driver’s ed—powerful but dangerous without structure. When AI is used to do the thinking for students, it stifles creativity and long-term retention instead of developing it.
2. AI can help close educational gaps in schools that lack the resources for individualized learning. In many underserved districts, large class sizes make one-on-one instruction nearly impossible. AI tools can adapt to students’ needs in real time, offering personalized learning that would otherwise be out of reach.
3. AI can play a key role in addressing the U.S. literacy crisis. Sam points out that 70% of U.S. inmates read at a fourth-grade level or below, and 85% of juvenile offenders can’t read. Adaptive AI tools are now being developed to assess, support, and gradually improve literacy for students who have been left behind.
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With technical education under pressure to deliver skilled talent faster, Lakeshore College is flipping the model—measuring learning by competency, meeting students where they are (even in high school), and using grants + national advocacy to scale the impact.
This week, Matt Kirchner talks with Dr. Paul Carlsen, President of Lakeshore College, about the different methods to rapidly upskill a technical workforce. Like Lakeshore's competency-based education (CBE) approach, which has now been adopted by half the college's programs and earned national attention and a White House conversation on scaling CBE.
In addition to CBE, we discuss Rocket Academy’s early manufacturing pathway for high school students, why industry certifications (SACA) matter (because employers say they matter), and how the college has leveraged $32M+ in competitive grants to fund innovation. Carlsen also explains his work on the AACC Board—including the coming impact of Workforce Pell on short-term training.
Listen to learn:
3 Big Takeaways:
1. Competency-based education measures student success by skill mastery, not seat time. Lakeshore’s shift to CBE began with an employer who couldn’t wait 16 weeks for students to complete a course. Today, students demonstrate mastery through real-world assessments, faculty build flexible learning pathways, and program delivery adapts to the individual needs of working adults, veterans, and learners balancing multiple responsibilities.
2. Through innovative partnerships, high school students are graduating with a college degree and workforce-ready credentials. Rocket Academy gives high school students access to a full integrated manufacturing pathway, often leading to a technical diploma before they even receive their high school diploma. The curriculum is designed to fit directly into the school day, removing scheduling barriers and building true college transcripts—not just college “experience.”
3. Grant funding follows big ideas and execution capacity. Lakeshore has secured over $32 million in competitive grants, including major awards from the National Science Foundation. Success comes from proposing bold, high-impact projects with measurable outcomes, and from having the internal systems and cross-functional teams in place to deliver those outcomes on time and at scale.
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What if audit wasn’t just a watchdog—but a catalyst for innovation, trust, and long-term growth? And what can education learn from it?
In this episode of The TechEd Podcast, Matt Kirchner sits down with Abim Kolawole, Chief Audit Executive at Northwestern Mutual, to explore how risk management, when done right, becomes a strategic advantage. Abim shares his remarkable journey—from growing up in Nigeria and watching Wall Street as a kid, to becoming a lawyer at the SEC, to now leading audit at one of America’s most respected financial institutions.
But this episode goes far beyond compliance. It’s about how innovation and integrity can—and must—coexist. Abim breaks down how technology can accelerate outcomes only when deployed safely, how AI is reshaping how organizations detect and act on risk, and why relevance is the new currency for both businesses and educators.
Listen to learn:
3 Big Takeaways from this Episode:
1. Audit is no longer just about compliance—it’s about enabling innovation. Abim Kolawole views audit as a strategic partner that delivers foresight, insights, and confidence to help a company grow safely. By using data, analytics, and a future-focused mindset, internal audit can help organizations place smarter bets, not just avoid bad ones.
2. Technology only accelerates value when it’s implemented with trust and purpose. At Northwestern Mutual, cloud migration and emerging tech like AI are approached with a “safe by design” mindset that includes cross-functional vetting and intentional guardrails. Abim emphasizes that skipping this step puts long-term client trust—and company relevance—at risk.
3. Education leaders can learn from the client-centric models used in business. Just like Northwestern Mutual redesigned the advisor and client experience using design thinking, educators must reimagine the student and teacher experience before introducing new tools. Critical thinking, not technology alone, is the foundation of a truly transformative education.
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In this episode of The TechEd Podcast, Duncan Kane, Senior Vice President at Toshiba America, shares insights from nearly two decades of working at the intersection of industry and education. Drawing from his leadership in STEM outreach, Duncan explains why Toshiba sees early STEM engagement not just as a good cause—but as a strategic investment in the future of innovation and the workforce.
One way Toshiba brings this vision to life is through its long-standing partnership with the National Science Teaching Association on ExploraVision, a science competition that challenges K–12 students to design technologies 20 years into the future. But as Duncan explains, the program isn’t really about competition—it’s about creativity, purpose, and helping students see themselves as future innovators. The conversation explores what happens when kids take ownership of real-world problems, the importance of dreaming big (with or without big budgets), and how industry can play a more active role in developing STEM talent.
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3 Big Takeaways from this Episode:
1. Students come up with more creative solutions when they haven’t yet learned what’s “impossible.” Duncan explains that younger students are often more willing to dream big because they haven’t developed the cynicism or constraints that come with adulthood. In ExploraVision, fifth graders have proposed ideas like AI-powered glasses that interpret sign language and wearable devices to predict seizures—solutions rooted in bold thinking, not technical limitations.
2. When students choose problems that matter to them, STEM learning becomes personal and powerful. Many teams in ExploraVision choose issues they’ve encountered firsthand, like a relative’s epilepsy or local environmental concerns. That personal connection drives deeper engagement and creativity, whether it’s robotic honeybees to help pollinate crops or fire-resistant materials inspired by mushrooms.
3. Building a future STEM workforce doesn’t require a billion-dollar initiative—it starts locally. Duncan urges companies to start in their own communities, supporting local students and educators in ways that feel personal and authentic. Toshiba’s partnership with NSTA and the success of ExploraVision demonstrate how consistent, community-rooted efforts can scale to national impact—reaching 450,000 students over 33 years.
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In a world of digital overload, short-form media, and AI-powered personalization, staying focused has never been harder. Today, the average attention span on any screen is just 47 seconds. What's causing this decline in focus, and what should educators do about it?
Those are some of the questions we discuss with Dr. Gloria Mark, UC Irvine informatics professor and author of Attention Span: A Groundbreaking Way to Restore Balance, Happiness and Productivity.
Dr. Mark explains the psychology behind attention, including the difference between controlled and automatic processing, the role of self-regulation, and how sleep debt, stress and individual cognitive rhythms factor into a student's ability to concentrate. She also points to a growing trend in education: designing classroom content to accommodate short attention spans, which may be unintentionally reinforcing them.
The conversation also takes a timely turn into how AI tools—from TikTok’s recommender systems to ChatGPT—are changing the way students interact with information, and what that means for deep learning, retention, and even courage in the classroom.
Listen to learn:
3 Big Takeaways:
1. Short attention spans are not a personal failure—they’re shaped by both individual traits and digital environments.
Gloria distinguishes between controlled and automatic attention, noting that much of our behavior—like checking phones or clicking notifications—happens without conscious thought. These automatic habits are reinforced by our environment, particularly digital technologies that train us to switch rapidly and respond to constant stimuli.
2. Classroom strategies that cater to short attention spans may be doing more harm than good.
Gloria highlights a trend in education toward breaking lectures into smaller chunks or assigning only short passages instead of full books. While well-intentioned, these adaptations risk further weakening students’ ability to engage in long-form content and develop deep, reflective thinking.
3. AI tools like TikTok and ChatGPT are reshaping how students consume and process information—often at the cost of deeper learning.
Platforms driven by recommender algorithms use random reinforcement to keep users engaged, conditioning them for rapid content consumption. In the classroom, reliance on generative AI can create a disconnect between students and the material, undermining “depth of processing” and reducing the cognitive benefits of making mistakes.
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The TechEd Podcast sits at the intersection of technology, industry, innovation and the people who make progress possible. Hosted by Matt Kirchner, each episode features builders,…
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