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Building AI literacy into a school system or a curriculum is a lot to carry. The tools keep changing, and every plan you write has to account for technology that will look different by next year. So it’s natural to wonder which parts of that plan will last, from the concepts students learn to the examples in each lesson and the policies behind them. Chuck Melley, Senior VP of Policy, Advocacy and Communities at Code AI, explains which parts of an AI literacy plan belong at the center and which need regular updates so that you can plan with more confidence.

How can core curriculum support personalized learning without creating more work for teachers? In this episode of Tech in EdTech, Olivia Lara-Gresty is joined by Kelly Philbin, PhD, Director of Core Adoptions at IXL Learning, to discuss how to connect instruction, assessment, differentiation, and practice. They explore how assessment can help teachers understand student needs and decide what to do next, while keeping students connected to grade-level learning. The conversation also examines support for multilingual learners, the balance between curriculum coherence and teacher flexibility, and what product teams can learn from educator feedback.

Textbooks have always been static, with the same page providing the explanation. It never takes into account who's reading. Dakshay Mehta, Head of Technical Staff, Stealth AI, joins Eric Stano to talk about what happens when a book becomes a conversation instead. They dig into how AI tutors can adapt to different learning styles and how sequential curricula need to take a step back in modern learning.

What should a healthcare simulation program build before investing in more technology? Francisco Castelblanco, DNP, RN, Chair, Continuing Professional Development & Area Health Education Center Director at MAHEC, explains why educator capability should shape modality choices, scenario design, simulation debriefing, and the measurement of patient outcomes.

Somewhere between the hype and the skepticism around XR lies a clear-eyed view of where it fits within workforce learning. Bharani Rajakumar, Founder, Transfr, joins Zahra to talk through where XR earns its place, where it doesn't, and what every workforce and education leader should consider before their next investment.

Before your next AI strategy conversation, ask yourself this: Are you starting with implementation, or readiness? Stephen Jull, Global Head of AI and EdTech at Teach For All, argues that schools may be starting in the wrong place. The real question is not just how to roll out AI, but whether the institution is ready for it. In this Tech in EdTech episode, Stephen joins Sean Strathy to discuss why AI readiness must come before rollout, and what schools need to get right before making their next major AI decision.

Enrollment trends may look like they’re improving, but the bigger challenges in higher ed haven’t changed. David Brunner speaks with Phil Hill about the realities behind enrollment shifts, evolving student expectations, and how institutions should rethink technology, strategy, and partnerships.

Some students log in, submit assignments, and still drop out. So what are we really measuring? In this episode, Shaunak Roy explains why most engagement metrics fail to predict retention and what institutions should be looking at instead. From early risk signals to faculty workload and AI hype, this conversation challenges how higher ed thinks about engagement and what it takes to keep students on track.

Most career readiness programs start in senior year. By then, it’s already late. Hiring is shifting toward demonstrated skills, work samples, and real evidence of capability, while schools still rely heavily on GPA and transcripts. So where is the disconnect? In this episode, Zahra sits down with Allison Danielsen, CEO of Tallo, to talk about skills-based hiring, early career exposure, and why making student talent visible to employers is becoming one of the biggest challenges in education.

Thomas Cavanagh, Vice Provost for Digital Learning at the University of Central Florida, breaks down how analytics should drive retention, graduation rates, and student success. He explains why adoption metrics miss the point and how LMS data can act as an early warning system for timely student support. This episode offers practical insight on using data and AI responsibly while keeping decisions student-first.

Clicks and completions are easy to report and mistake for an impact. In this Tech in EdTech episode, Sylvie Milverton, CEO & Co-founder of Lynx Educate, shares how companies use education to meet community and business goals and why the real scorecard must track the use of skills in work and life outcomes. The conversation covers: aligning measurements with the original objective, a simple commitment step that increases completion in longer programs, demoting metrics teams can’t act on, and avoiding bloated skill taxonomies by keeping indicators simple.

AI makes it dangerously easy to stop at one confident answer. For education publishers and learning platforms, that’s a product risk: teachers need sources they can trust, students need research support (not shortcuts), and credibility doesn’t survive black-box answers. In this episode, Jan van der Crabben of World History Encyclopedia explains how they built the platform on one core idea: history is a web of connections, not isolated timelines.  Jan also shares how their History AI evolved through teacher feedback, why shorter answers and visible citations matter, how academic journals help reduce hallucinations when proprietary content is limited, and why trustworthy publishing is at risk as AI becomes the default interface to knowledge.

Parents want to help their kids. Most don’t know where to start. In this episode of Tech in EdTech, Zahra speaks with Stephanie Parra, M. Ed., CEO of ALL In Education, about making proficiency, communication, and learning tools easier for families to understand and act on.

Dan Sandhu, CEO, EDT, lays out a practical, evidence‑first view of AI in education. He argues that AI must be anchored to shared educational outcomes, owned by local systems, and guided by living policies for ethics, safety, training, and leadership. Equity remains the strategic lens. AI can widen gaps when bandwidth, devices, and power are scarce, yet it can also narrow them by enabling access to national and sub‑national data on school quality, real‑time monitoring, and targeted support.

Dr. Andrea Gregg, Associate Research Professor and Director of Learning Experience Design at Penn State University, outlines a practical approach to building strong online learning in the AI era. She explains why simple, “don’t make me think” design protects real learning, and why every choice should tie back to outcomes and assessment. She covers what makes micro-credentials credible, how to avoid personalization and dashboard features that mislead instructors, and where AI can help without replacing essential thinking. The episode turns solid learning principles into concrete decisions for higher-ed leaders, LXDs, faculty, and product teams.