Technology In Education

500 students share one computer in Niger. Yet they're conducting advanced physics experiments that students at elite schools can't access. The secret? WebAR turning basic smartphones into portable STEM labs. Think about that. In Sub-Saharan Africa, fewer than 10% of schools have internet. Student-to-computer ratios hit 500:1. Yet mobile subscriptions jumped from single digits to 80% in a decade. Students already carry the infrastructure—we just weren't using it right. Traditional EdTech Reality: ↳ VR headsets: $300+ per student ↳ Heavy apps requiring 5G speeds ↳ Labs costing millions to build ↳ Rural schools: permanently excluded The WebAR Revolution: ↳ Runs in any browser, optimized for 3G ↳ No app store, minimal storage ↳ Science scores improving 10-15% ↳ Every smartphone becomes a laboratory But here's what grabbed me: A physics teacher in rural South Africa has one broken oscilloscope. No budget. Her students scan printed markers, and electromagnetic fields pulse across their desks. They run experiments infinitely—no equipment damaged, no reagents consumed. One student told her: "Engineering is for people like me now. The lab fits in my pocket." What changes everything: ↳ Mobile-first matches actual connectivity ↳ Browser-based works offline ↳ Teachers need training, not new buildings ↳ Inequality becomes irrelevant The Multiplication Effect: 1 teacher with markers = 30 students experimenting 10 schools sharing content = communities transformed 100 districts adopting = educational equality emerging At scale = STEM education without infrastructure gaps We spent decades waiting for labs that won't arrive. Now any browser becomes one. Because when a student in rural Africa explores the same 3D molecules as someone at MIT—using the phone already in their pocket—you realize: WebAR isn't shiny technology. It's a quiet equaliser making world-class STEM education fit into 3G connections and $50 phones. Follow me, Dr. Martha Boeckenfeld for innovations where accessibility drives transformation. ♻️ Share if you believe quality education shouldn't require perfect infrastructure.

I just witnessed an excruciating exchange between a well-intentioned school leader and a shiny new edtech startup. They were promising—yet again—that some fancy AI-powered tool would “revolutionize learning.” It’s like we’re in the middle of an EdTech Groundhog Day. Billions of dollars poured in over the years, from MOOCs to Personalized Learning software, and the same outcome: students barely touch them. How have we not learned? This is EDTECH’S BIGGEST LIE. Every time we get a new wave of products and platforms, the buzzwords change, but the core pitch stays the same: “Just plug into our technology and watch students magically succeed.” Yet we keep forgetting the fundamental truth: If kids don’t want to learn, they won’t use your tools, no matter how “intuitive,” “adaptive,” or “AI-driven” they are. Think about the country’s fitness crisis. A room full of fancy weight machines with ergonomic seats, plush padding, and digital screens doesn’t automatically make people work out. Nobody’s going to bench-press because the bar grip is a little cushier now. They’ll do it because they feel inspired, they see the benefits, or they believe it matters for their health and lifestyle. If none of that resonates, the new machines just gather dust. Education is no different. Students who aren’t convinced learning is important will only see an online platform as something they’re forced to click through and cheat. Whether it's deep research tools, unlimited video tutorials, or interactive simulations, none of it shifts motivation if they don’t believe it has real value for them. Yes, edtech can absolutely support dedicated learners and curious minds. I have personally 3x'd my speed of learning thanks to these tools! But the industry keeps trotting out the same old solution to the wrong problem. The problem is not “insufficient access” or “lack of advanced features.” It’s the blatant refusal to address motivation and purpose. Until kids are shown why learning deeply matters—to them, not just to the adults in the room—no fancy new AI bot or million-dollar pilot will magically fix it. That’s where the real revolution needs to happen. Get students invested, connect learning to their world, and THEN bring in the powerful tools. Otherwise, we’re just building comfier gym equipment for people with zero interest in fitness.

Want your team to actually adopt AI? Pay them first, then train them. That's the counterintuitive approach Lauren Franklin, VP of Customer Experience at Zapier, took with her support team – and it's working. Rollouts of AI in customer service are often done outside the team: turn off the flow that goes to the humans, then lay people off. Not at Zapier. Lauren made clear to her team that they had to adapt, learn new skills, and hit new performance standards. She also: 🔸 Raised base pay for her entire customer support team 🔸 Invested heavily in hands-on training, experimentation time and cross-functional support 🔸 Rolled up her sleeves -- she was in the queue every Monday morning The results: Her team is now resolving significantly more customer issues while maintaining quality scores and customer happiness. Here's what I've learned from talking with Lauren and Brandon Sammut: ✅ Be specific about performance expectations. Franklin didn’t speak in generalities about “embracing change.” She set concrete standards for customer satisfaction and resolution rates, as well as efficiency metrics. ✅ Lead from the front lines. Working alongside employees using new tools provides insights about what's real, what's hype, and where teams are stuck. ✅ Invest in people before demanding results. Whether it's pay, training time, or both, demonstrate commitment upfront. Franklin's approach recognizes a fundamental truth: people won't fully embrace technology that feels like a threat to their livelihood. How are you helping your teams see AI as an opportunity rather than a risk? 🔗 Read the full story about Zapier's approach in TIME: https://lnkd.in/gyk2TpVb Huge thanks Jacob Clemente and Kevin Delaney at Charter -- if you're a Charter Pro subscriber, you saw this article already! #GenAI #ChangeManagement

India’s edtech space may be opening up a fresh opportunity for a new generation of players to innovate, as incumbents either die out or get consolidated. This time, I hope we do it right and avoid repeating past mistakes - including our own, and carry forward some hard-earned learnings: → There are only so many truly good teachers. → Some students simply don’t want to learn - don’t build for them or acquire them. → Many adults want outcomes without effort; adult learning/skilling is ngmi. → Certification is a bullshit business; even if people buy it, it doesn’t improve actual skills - otherwise we’d have seen the impact by now. → Not everyone wants to be an engineer/doctor/CA/lawyer. → A growing number of students genuinely don’t know what they want to do. → Star teachers are a boutique business - stop trying to scale them. → AI might be the best teacher we’ve been waiting for. → Personalized one-on-one human support will stay relevant for a long time. → Colleges that bring students together IRL will remain necessary - we just need a new generation of them. → High achievers need separate schools; their capability is getting stifled in normal ones. → We’ll need new vocational colleges for new-age professions - built by a new wave of education entrepreneurs. → Entrepreneurship-focused high schools may be the best way to nurture students who want to build. → We need a research-focused college for talent that doesn’t fit the current system - we’re losing far too much potential. → Teaching “Bharat adults” real, practical stuff (not random linkbait) is a massive opportunity enabled by AI-led content and personalization. → AI companions can finally solve the “motivation” layer in education (we tried and failed at this), and that can truly move the needle. → A “build and learn” model may be the most effective way to learn - we’re trying to enable some of this with AI Grants India. There are many more lessons from the incredible education entrepreneurs who built over the past decade in India. I hope these aren’t lost - and instead fuel the next generation.

India doesn’t lack students. It lacks sustainable EdTech. And the last 3 years have exposed that truth brutally. From Zoom classes to billion-dollar valuations. EdTech in India had its moment. But the crash that followed was equally brutal. On my podcast with Harshil Gala, CEO of NAVNEET TOPTECH, we unpacked the hard truths and opportunities that lie ahead. Here’s what stood out for me 👇 1. Market miscalculations : Everyone quoted “25 crore students” as the TAM. But no single product applies to all. India is fragmented: - 200 IB schools - 2,000 ICSE schools - 30,000 CBSE schools - 3,00,000 state board schools Many startups overestimated adoption, ignored willingness to pay, and collapsed. 2. Post-COVID correction : Parents shifted spending toward CBSE/English-medium schools and better infrastructure. But hype-driven models relying on aggressive sales tactics couldn’t survive. The sector is now being rebuilt around sustainability, not valuation. 3. The future is skill-based :  NEP + NCF are pushing India from rote learning to experiential, skill-based education. This isn’t a 3-year play, it’s a 30–40 year transformation. EdTech that aligns with this timeline will thrive. 4. AI in education :  Navneet’s AI, trained on 60+ years of proprietary content, is helping teachers generate quizzes, presentations, and games. The future isn’t “replacing teachers.” It’s empowering them. 5. The investment lens : VC funds run on a 7-year cycle looking for 100x returns. But education runs on decades. This mismatch has already exposed dozens of failed models. Winners will be the ones who build cash-flow positive, patient businesses. Education, it’s a responsibility. If you’re building in EdTech, stop chasing shortcuts. Align with how India actually learns, not how you wish it did. Because in this space, hype dies fast. But sustainable impact compounds for generations. A big Thanks to the our sponsors of the podcast: Powered by: NoFilter Juice  Co-Powered by: Titas Footwear  Venue Partner: Lets Work co-spaces  Growth Partner - GrowthOS Digital Media Partners - StartupNews.fyi 

In the past few months, we've worked with partners who've run into the same challenge with AI adoption. They rolled out policies or guidelines without bringing people into the conversation first—no workshop, no consensus building, just documents that needed signatures or implementation. Unsurprisingly, the result was frustrated staff expected to enforce or follow rules they had no part in creating, and leaders facing resistance instead of adoption. Both AI policies and guidelines are critical for responsible AI adoption, but they have to be built intentionally, with stakeholders driving consensus, or they most likely won't work. After working with hundreds of districts, we've created the resource below. Here are the best practices we recommend. Policies are your compliance layer and are designed to protect your district. We suggest adaptations to existing: ✔️ Acceptable use policies ✔️ Data privacy/FERPA protections ✔️ Academic integrity standards ✔️ Cyberbullying policies (to add deepfakes) Guidelines are your change management layer. They are the "why" that brings people along. We recommend including the following in your AI guidelines: 💡 Vision for GenAI adoption across your district 💡 GenAI misuse/academic integrity response protocols 💡 GenAI chatbot and EdTech tool vetting processes 💡 Digital wellbeing, data privacy, and student safety practices 💡 Implementation tips and instructional supports 💡 AI Literacy training opportunities and expectations What matters most is that both policies and guidelines should be built with stakeholders, not handed down to them. They should evolve with feedback, evidence of impact, and technical advancements. In all of our guideline and policy development work, we always start with AI literacy. It's important to build foundational understanding across stakeholders so that when policies and guidelines are developed, people can contribute meaningfully to the process and understand the "why" behind what they're being asked to implement. Intentional stakeholder engagement isn't a nice-to-have. It's what we've seen drive adoption. #AIforEducation #GenAI #ChangeManagement #AI

Innovation is the lifeblood of progress, but it doesn’t happen by chance. It’s cultivated in environments where team members feel safe to share ideas and challenge the status quo. Creating a culture of innovation means nurturing an environment where bold ideas can flourish. It’s about openness, diverse perspectives, and the freedom to experiment. When people feel empowered to speak up, creativity thrives, and true innovation follows. So, how do you create such a culture? 1️⃣ Embed a Growth Mindset: Encourage continuous learning and development across all levels of the organization. Provide resources for professional growth and celebrate learning milestones, fostering an environment where knowledge and skills are constantly evolving. 2️⃣ Facilitate Cross-Functional Collaboration: Break down silos and encourage teams from different departments to work together. Cross-functional projects can bring fresh perspectives and spur innovative solutions that wouldn’t emerge in isolation. 3️⃣ Implement Structured Feedback Mechanisms: Establish regular feedback processes focused on constructive criticism and actionable insights. Ensure psychological safety so team members feel secure, viewing feedback as an opportunity for growth rather than critique. 4️⃣ Encourage Calculated Risks: Promote a culture where calculated risks are welcomed. Empower your team to explore new ideas and approaches without fear of failure. Recognize and reward innovative efforts, even when they don’t result in immediate success. By embedding these principles into your organizational culture, you can pave the way for continuous growth and success. Let’s create spaces where innovation is not just an aspiration but a tangible reality. #Leadership #Innovation #FutureOfWork

You know that sinking feeling… Someone interrupts your carefully prepared presentation with “But what about...?” and raises a point you never considered. Everyone is looking at you, and you feel the weight of the world on your shoulders. In that moment, the idea or solution you’ve been presenting weighs in the balance. Address the resistance well, and your idea will likely be adopted with even more optimism than before. Address it poorly, and your idea is as good as gone. Here’s a quick overview of my “RAP” formula that you can use in these moments to turn blindside objections into “aha” moments. 1. R: Recognize the type of resistance you’re facing: - Logical resistance (conflicting data or reasoning) - Emotional resistance (values or identity challenges) - Practical resistance (implementation concerns) 2. A: Address it proactively in your presentation: - For logical resistance: Acknowledge competing viewpoints before they’re raised. "Some might point to last quarter’s numbers as evidence against this approach. Here’s why that perspective is incomplete..." - For emotional resistance: Connect your idea to their existing values. "This initiative actually strengthens our commitment to customer-first thinking by..." - For practical resistance: Demonstrate you’ve considered the real-world constraints. "I know this requires significant change. Here’s our phased implementation plan that accounts for..." 3. P: Provide a path forward that transforms resistance into alignment: - Give them space to voice concerns (but in a structured way) - Incorporate their perspective into the solution - Show how addressing their resistance actually strengthens the outcome The most powerful thing you can say in a presentation isn’t "trust me", it’s "I understand your concerns." When you genuinely see resistance as valuable feedback rather than an obstacle, you’ll find your ideas gaining traction where they previously stalled. #CommunicationSkills #BusinessCommunication #PresentationSkills

My AI lesson of the week: The tech isn't the hard part…it's the people! During my prior work at the Institute for Healthcare Improvement (IHI), we talked a lot about how any technology, whether a new drug or a new vaccine or a new information tool, would face challenges with how to integrate into the complex human systems that alway at play in healthcare. As I get deeper and deeper into AI, I am not surprised to see that those same challenges exist with this cadre of technology as well. It’s not the tech that limits us; the real complexity lies in driving adoption across diverse teams, workflows, and mindsets. And it’s not just implementation alone that will get to real ROI from AI—it’s the changes that will occur to our workflows that will generate the value. That’s why we are thinking differently about how to approach change management. We’re approaching the workflow integration with the same discipline and structure as any core system build. Our framework is designed to reduce friction, build momentum, and align people with outcomes from day one. Here’s the 5-point plan for how we're making that happen with health systems today: 🔹 AI Champion Program: We designate and train department-level champions who lead adoption efforts within their teams. These individuals become trusted internal experts, reducing dependency on central support and accelerating change. 🔹 An AI Academy: We produce concise, role-specific, training modules to deliver just-in-time knowledge to help all users get the most out of the gen AI tools that their systems are provisioning. 5-10 min modules ensures relevance and reduces training fatigue.  🔹 Staged Rollout: We don’t go live everywhere at once. Instead, we're beginning with an initial few locations/teams, refine based on feedback, and expand with proof points in hand. This staged approach minimizes risk and maximizes learning. 🔹 Feedback Loops: Change is not a one-way push. Host regular forums to capture insights from frontline users, close gaps, and refine processes continuously. Listening and modifying is part of the deployment strategy. 🔹 Visible Metrics: Transparent team or dept-based dashboards track progress and highlight wins. When staff can see measurable improvement—and their role in driving it—engagement improves dramatically. This isn’t workflow mapping. This is operational transformation—designed for scale, grounded in human behavior, and built to last. Technology will continue to evolve. But real leverage comes from aligning your people behind the change. We think that’s where competitive advantage is created—and sustained. #ExecutiveLeadership #ChangeManagement #DigitalTransformation #StrategyExecution #HealthTech #OperationalExcellence #ScalableChange

Nearly 8 in 10 faculty believe generative AI will reshape teaching in their department. 86% say it will change the work itself. And yet only a third feel positive about AI in higher ed. Among English faculty, 66% are negative. History and the humanities, 58%. The most resistant of all? Professors at the most selective institutions—and those with the least hands-on experience using the tools. In the latest issue of my newsletter, Next, I explore how the debates around AI on campuses are often closer to grief. AI challenges the very things that set faculty apart from their students: expertise, autonomy, belonging. As one provost put it: students are arriving AI-ready while their instructors are not. A new report lays out why leaders have to build trust before they can integrate AI. Drawing on research about psychological safety, it points to three conditions for traction: ⚖️ Stability: Set time-bound expectations so AI feels like a bounded initiative, not endless disruption. 🔎 Exposure: Build low-stakes ways to experiment, from sandboxes to peer-led demos. ❤️ Empathy: Read resistance as a signal, not a behavior to quash. Roll AI out without it, and faculty produce busy work or quietly sabotage the strategy. From there, what actually works spreads through people. The report outlines a framework as a way to surface faculty concerns, share what's working discipline by discipline, and scale it through peer leaders rather than mandates from above. Link to the report in the newsletter 👇