EdTech Implementation Guidance

🌍 UNESCO’s Pillars Framework for Digital Transformation in Education offers a roadmap for leaders, educators, and tech partners to work together and bridge the digital divide. This framework is about more than just tech—it’s about supporting communities and keeping education a public good. 💡 When implementing EdTech, policymakers should pay special attention to these critical aspects to ensure that technology meaningfully enhances education without introducing unintended issues:  🚸1. Equity and Access Policymakers need to prioritize closing the digital divide by providing affordable internet, reliable devices, and offline options where connectivity is limited. Without equitable access, EdTech can worsen existing educational inequalities.  💻2. Data Privacy and Security Implementing strong data privacy laws and secure platforms is essential to build trust. Policymakers must ensure compliance with data protection standards and implement safeguards against data breaches, especially in systems that involve sensitive information.  🚌3. Pedagogical Alignment and Quality of Content Digital tools and content should be high-quality, curriculum-aligned, and support real learning needs. Policymakers should involve educators in selecting and shaping EdTech tools that align with proven pedagogical practices.  🌍4. Sustainable Funding and Cost Management To avoid financial strain, policymakers should develop sustainable, long-term funding models and evaluate the total cost of ownership, including infrastructure, updates, and training. Balancing costs with impact is key to sustaining EdTech programs.  🦺5. Capacity Building and Professional Development Training is essential for teachers to integrate EdTech into their teaching practices confidently. Policymakers need to provide robust, ongoing professional development and peer-support systems, so educators feel empowered rather than overwhelmed by new tools. 👓 6. Monitoring, Evaluation, and Continuous Improvement Policymakers should establish monitoring and evaluation processes to track progress and understand what works. This includes using data to refine strategies, ensure goals are met, and avoid wasted resources on ineffective solutions. 🧑🚒 7. Cultural and Social Adaptation Cultural sensitivity is crucial, especially in communities less familiar with digital learning. Policymakers should promote a growth mindset and address resistance through community engagement and awareness campaigns that highlight the educational value of EdTech. 🥸 8. Environmental Sustainability Policymakers should integrate green practices, like using energy-efficient devices and recycling programs, to reduce EdTech’s carbon footprint. Sustainable practices can also help keep costs manageable over time. 🔥Download: UNESCO. (2024). Six pillars for the digital transformation of education. UNESCO. https://lnkd.in/eYgr922n  #DigitalTransformation #EducationInnovation #GlobalEducation

Dear EdTech Investors - Part 3 In my last post, I told you about the 5 percent problem. Only about 5 percent of students use most edtech tools at the level needed to show results. After reading that, some might blame the product. Sometimes they are right. But often the product is fine. The problem is that nobody showed the teacher how to use it effectively. I know this because I used to be that person. Before I became a principal, I was an instructional technology coach for a large school district. My job was helping teachers integrate new tools into their classrooms. I was the bridge between the product and the practice. 𝗧𝗵𝗲 𝘁𝗼𝗼𝗹 𝘄𝗮𝘀 𝗻𝗲𝘃𝗲𝗿 𝘁𝗵𝗲 𝗵𝗮𝗿𝗱𝗲𝘀𝘁 𝗽𝗮𝗿𝘁. The hard part is fitting it into a 50-minute class with 35 students who are all in different places. The hard part is leaders making the case to staff that this tool is worth their time when they have been burned by the last three. That is where a lot of EdTech investments fail. 𝑵𝒐𝒕 𝒂𝒕 𝒕𝒉𝒆 𝒑𝒓𝒐𝒅𝒖𝒄𝒕 𝒍𝒆𝒗𝒆𝒍, 𝒃𝒖𝒕 𝒂𝒕 𝒕𝒉𝒆 𝒑𝒆𝒐𝒑𝒍𝒆 𝒍𝒆𝒗𝒆𝒍. And that means your portfolio company's churn problem might not be a product problem. It might be an implementation problem. That is fixable, and fixing it is profitable. When you evaluate a company, do you ask how they support implementation? Not a PDF guide. Not a webinar. Real, sustained training that meets teachers where they are. A product without implementation support is a product waiting to be abandoned. Here is the part that should interest you: 𝒕𝒓𝒂𝒊𝒏𝒊𝒏𝒈 𝒊𝒔 𝒏𝒐𝒕 𝒋𝒖𝒔𝒕 𝒂 𝒄𝒐𝒔𝒕. 𝑰𝒕 𝒊𝒔 𝒂 𝒓𝒆𝒗𝒆𝒏𝒖𝒆 𝒔𝒕𝒓𝒆𝒂𝒎. Because schools would pay for professional development to support successful, ongoing implementation. When a company offers training that actually helps our teachers use the tool well, we will find the money. Because it makes the tool work 𝙁𝙊𝙍 the teachers, which makes the investment worth renewing. That is recurring revenue your portfolio company is leaving on the table. The companies that get this right hire former educators. They offer onboarding that goes beyond "click here, then click here." They check in at month three. They ask teachers what is not working and actually fix it. Those companies do not have a 5 percent problem. They have loyal customers. The ones that give logins and ask teachers to go to the company website's FAQ page? They end up on my list of tools to cut. If the answer to "What is your training model?" is "We have a help desk" or "We built an AI chatbot," that is not a training model. 𝑰𝒏𝒗𝒆𝒔𝒕𝒊𝒏𝒈 𝒊𝒏 𝒄𝒐𝒎𝒑𝒂𝒏𝒊𝒆𝒔 𝒕𝒉𝒂𝒕 𝒊𝒏𝒗𝒆𝒔𝒕 𝒊𝒏 𝒑𝒆𝒐𝒑𝒍𝒆 𝑾𝑰𝑳𝑳 𝒎𝒂𝒌𝒆 𝒚𝒐𝒖 𝒎𝒐𝒓𝒆 𝒎𝒐𝒏𝒆𝒚 𝒊𝒏 𝒕𝒉𝒆 𝒍𝒐𝒏𝒈 𝒓𝒖𝒏. Because that is how you build a company that schools keep for a decade. #EdTech #PreK12 #SchoolLeadership #EdTechInvestment #AIinEducation

Common Sense Media recently released a comprehensive risk assessment of AI teacher assistants/lesson planning tools. Their findings reveal that while these tools promise increased productivity and creative support, they're also creating "invisible influencers" that could fundamentally undermine educational quality. Unlike GenAI foundation model chatbots, these tools are specifically designed for instructional planning and classroom use and are rapidly being adopted across districts. Key Concerns from their report: • "Invisible Influencers" in Student Learning: AI-generated content directly shapes what students learn through potentially biased perspectives and historical inaccuracies that teachers may miss; evidence also shows these tools suggest different approaches and responses based on student race/gender • “Outsourced Thinking" Problem: Tools make it dangerously easy to push unreviewed AI instructional content straight to classrooms, while novice teachers lack experience to spot subtle errors and biasses • High-Stakes Outputs: IEP and behavior plan generators create official-looking documents that could impact student educational trajectories even though these plans should be human-generated (and in the case of IEP goals are mandated to be human generated) • Undermining High-Quality Instructional Materials: Without proper integration, these tools fragment learning and can undermine coherent, research-backed curricula Recommendations from the report: • Experienced educator oversight required for all AI-generated educational content • Clear district policies and guidelines for AI teacher assistant implementation • Integration with existing high-quality curricula rather than replacement of established materials • Robust teacher training on identifying bias and evaluating AI outputs • Careful oversight of real-time AI feedback tools that interact directly with students We'd also recommend foundational AI literacy for teachers before they begin using GenAI teacher assistants, so that they are aware of the potential limitations. While AI teacher assistants aren't inherently problematic, they require the same careful implementation and oversight we'd expect for any tool that directly impacts student learning. The potential for enhanced productivity is real, but so are the risks to educational equity and quality. This report underscores the urgent need for GenAI EdTech tool makers to provide evidence of how their tools mitigate these issues along with evidence-based policies and professional development to help educators navigate AI tools responsibly. All of which underline how important AI Literacy is for the 2025-2026 school year. Link in the comments to check out the full report. Also check out our 5 Questions to Ask GenAI EdTech Providers resource in the comments if you are planning to implement any of these tools in your school or district. #AIinEducation #ailiteracy #Education #K12 AI for Education

Education technology is easy to build in theory. The real challenge is making it work in the hands of a student whose internet drops mid-lesson, or a working mum who is logging into university for the first time on a shared device. The test is not in creating EdTech tools but in making them work for the people who need them most. When we started uLesson in 2019, we built a platform with high-quality video lessons, quizzes, and practice tests. Everything worked perfectly in our offices in Jos and then, Abuja. But that changed when we tried to get them into the hands of students in towns and villages where electricity was unreliable, data was expensive, and smartphones were often shared among siblings. The same lessons appeared when we launched Miva Open University, an affordable, accessible university that delivers quality education with the same rigour as a physical campus. Creating the platform was one challenge; helping working adults adapt to digital learning for the first time was another. Some of our students had never studied without the structure of a physical classroom. Many were logging in from places where network connectivity was patchy at best. These challenges sit against a larger backdrop: According to Quartz, only 1 in 4 students applying to university will get accepted. Not because they didn’t study hard enough, instead, in many cases, it is because there simply isn’t enough room for all of them. From these experiences, I’ve learnt that successful EdTech implementation requires: - Designing for context: Tools must work offline or in low-bandwidth environments. - Investing in people: Teachers, facilitators, and students need training, support, and trust to use technology effectively. - Patience in adoption: Communities don’t adopt new systems overnight. Value has to be proven, and trust earned, over time. I remain convinced that EdTech will play a central role in the future of African learning. But for it to truly work, it must be built not just for ambition, but for reality. It has to be built for students walking kilometres to school, for families sharing a single device, and for communities learning to trust digital tools for the first time. We’re still learning. We’ll keep improving. And with each iteration, we get closer to delivering not just access, but quality learning wherever a student lives.

Selecting the right AI tool can be challenging when new products appear almost daily. This guide helps you cut through the noise with a clear, structured process for testing, evaluating, and integrating AI tools in the classroom. It introduces a practical framework built around three pillars: usability, pedagogy, and ethics. Each is broken into a checklist of focused questions to help educators quickly determine whether a tool fits their curriculum, supports deep learning, and meets privacy standards. The guide also includes tips for piloting tools with a small group, gathering student feedback, and reflecting on results. This guide is informed by key resources, including aiEDU’s AI Readiness Framework, ISTE’s Teacher Ready Edtech Product Evaluation Guide, the U.S. Department of Education’s AI Integration Toolkit, and UNESCO’s Recommendation on the Ethics of AI. These references shaped the usability, pedagogy, and ethics checklists to keep the framework practical and research-based. #AIinEducation #EdTech #TeachingWithAI #TeacherTools #AIforTeachers #EdLeaders #ClassroomInnovation #DigitalLearning #AIIntegration #EducationTechnology

Teachers and EdLeaders: Feeling overwhelmed by the pressure to integrate AI into your classrooms? Let’s simplify it. 🍎💡 As a Google AI Tools Specialist and Educational Diagnostician, I see firsthand how the idea of adopting new tech can feel like just one more thing on an educator's already full plate. But leveraging tools like Google Gemini doesn't require a computer science degree, it just requires a starting point. I created this quick-start visual guide to help educators step into AI with confidence. When we focus on AI Literacy and foundational Prompt Engineering for Education, Gemini transforms from a daunting technology into an invaluable instructional design assistant. Here are a few key takeaways for educators starting their AI journey: 🎯 Start with Pedagogy: AI works best when you define your lesson objectives first. 🔄 Iterate and Differentiate: Use Gemini to easily adjust your content for struggling students or neurodiverse learners, supporting Universal Design for Learning (UDL) principles. 🛑 Protect Privacy: Never input personally identifiable information (PII). AI Ethics and Responsible Use must always be at the forefront of our practice. 🧠 You Are the Expert: Gemini is your starting point, not your final answer. The human-in-the-loop is non-negotiable. AI is here to stay. Whether you are a classroom teacher looking to save time on curriculum development, or a school district/workforce board needing to meet federal AI compliance requirements, building foundational AI literacy is the first step. 👇 Save this post for your next planning period, and share it with a fellow educator who could use some time back in their day! Are you looking to bring comprehensive, compliant AI Literacy Training to your school district or workforce development program? Send me a direct message and let’s talk about empowering your team. #AILiteracy #GoogleGemini #EdTech #PromptEngineering #TeachersOfLinkedIn #EducationalLeadership #UniversalDesignForLearning #InstructionalDesign #SpecialEducation #EdLeaders #FutureOfWork #AIinEducation

How we helped one EdTech company break the "Pilot Loop." It’s one of the most frustrating phone calls I get. A founder calls and says, "Lisa, they love the tool. They’ve been using it for a semester or two but when we want to onboard the remaining sections and initiatives to pilot are over we struggle to convert to paid users. This is the "Pilot Loop." It happens when a proof of concept proves the tech works, but fails to prove the experience is worth the change. We recently stepped in to help a team in this exact spot. Here was the 3-step adjustment we made to their "Adoption Roadmap": Step 1: Focus on the Faculty "Wins" (Not just the data) The customer success team was sending reports on "Average Time for Students on the Platform." The educators didn't care. We shifted the focus to faculty testimonials that described the timing savings in office hours and student questions. We needed the "stuck" pilots to hear from peers who said, "This actually gave me hours of my life back." Step 2: Curate the Evidence We stopped sending generic PDF brochures. Instead, we built a library of student outcome case studies. When an educator is in a pilot, they are under a microscope. They need to justify their choice to their peers especially if they are "change agents". We gave them the "Social Currency" (the data and stories) they needed to look like heroes in their own meetings. Step 3: The "Reference" Bridge We identified "Champion Users" from previous successful adoptions and offered them as references. Not for a sales call, but for a "peer-to-peer" chat. Knowing that another school with the same challenges and same student demographic had succeeded changed everything. The result? The pilots didn't just move forward; they moved faster. Why? Because we removed the fear of being "The First." In education, no one wants to be the pioneer who gets the arrows. Everyone wants to be the one who followed a proven path to better outcomes. If you’re stuck in pilot mode, stop tweaking your UI and start building your "Evidence Library." What’s one piece of "Peer Proof" you could share with your pilot users today that has nothing to do with your features?

Everyone has a hot take on AI in Education. Here's mine. But it's not about the tech. It's grounded in practical implementation, understanding deeply how an education ecosystem works and what actually happens in a classroom each day. Inside out. I'm not a technical AI expert. But I've spent 17+ years in EdTech, I've been training my own Claude instance for 9 months to work faster and smarter, and I'm learning Agentic AI from people way smarter than me (looking at you, Kunal Dalal). Here's my thesis: We're in the dial-up era of AI. It feels like the 5th inning. We're probably still warming up. And most of what I see in K-12 AI right now? It's one of three things: AI FOR AI'S SAKE. No strategy. Inject some AI, put it in the pitch deck, call it innovation. Looks sexy. Adds little value. BASIC STUDENT-FACING AI. Look up an answer. Solve a problem. ChatGPT can do this. This isn't creating student agency it's inhibiting it. BASIC AI FOR EDUCATORS. Summarize data. Create documents faster. This is table stakes. It's 0.0001% of what's possible. So where's the real value? INTEGRATION. AI needs to plug into the district ecosystem — SSO, SIS, benchmark data, LMS. Without integration, you're a standalone tool. With it, you're part of the workflow. IMPLEMENTATION. What's the actual use case in a real school day? An AI tutor loaded with student data, lesson plans, state standards, and tutoring methodologies — deployed in intervention blocks with teacher insights? That's not a feature. That's a system. PD & TRAINING. Adults need the WHY before they buy in. One-time PD doesn't cut it. Ongoing training integrated into PLCs drives adoption that makes the AI smarter. Here's what I believe: Humans will always be the core of education. But the tools we're giving educators today aren't sufficient especially in high-needs communities with classrooms spanning 6+ grade levels. AI can close equity gaps at scale. But only if we stop treating it as the showy front-end feature... And start building it as the strategic engine on the backend integrated, intentional, outcome-driven. That's where the value is. That's my bet.

AI is rushing into education faster than most institutions can adapt — and the gap between early adopters and everyone else is widening. Today, I published a podcast episode and new article (below) breaking down the 10 most practical steps educators can take right now to integrate AI and immersive tech responsibly, equitably, and at speed. The message is simple: "If we don’t start playing with these tools, we won’t be ready to teach with them." In my latest Immersive Medical Podcast episode with Reed Dickson, we dug into: • Why “phones-out” learning accelerates AI literacy • How to stop relying on broken AI detection tools • The power of interdisciplinary AI cohorts • How VR training can be integrated without hardware overwhelm • Why transparency, trust, and human-centered adoption matter more than the tech itself • What healthcare educators must get right to prepare future clinicians • How AI can increase equity if we design for it intentionally • Why the future belongs to adaptable generalists who know how to learn fast Educators aren’t just teaching content anymore — we’re teaching adaptability, meta-learning, and the ability to collaborate with AI. And that means our own willingness to experiment matters more than ever. If you’re an educator, instructional designer, clinical trainer, or academic leader, I think you’ll find this article useful. These are steps you can implement tomorrow — not abstract theory or futurism. 📘 Read the full article below 🎧 And check out the full conversation with Reed on the Immersive Medical Podcast [link in article]. This one is especially important for educators, nursing faculty, EMS programs, and anyone redesigning curriculum for an AI-enabled future. Let’s build the future of learning — intentionally, equitably, and with a spirit of curiosity + play. #AIinEducation #EdTech #HealthcareEducation #NursingEducation #XR #VRTraining #ImmersiveLearning #AI #GenerativeAI #ClinicalEducation #FutureOfWork #HigherEd #MedicalTraining #ImmersiveMedicalPodcast

There is a big "implementation gap" in American education right now when it comes to AI. While 33 state departments have issued official guidance, only about one third of school districts have a formal policy in place. As a former Technology Leader for the NYC Department of Education, I’ve seen this cycle before: states lead, districts wait, and students are left to navigate the technology on their own. We can’t let that happen with AI. District leaders aren't ignoring the tech, they’re overwhelmed by shrinking budgets and daily operations. But here’s the reality: The AI is already in your classrooms. If you don't have a framework, you aren't protecting the school, you're just losing control over how the data is handled. Here are 5 steps every district leader should take right now: 👉 Form a Team: Don't make this just an "IT project." Bring in teachers, parents, and students. 👉 Take Inventory: Spend 30 days mapping every AI tool currently being used (you’ll be surprised by how much shadow tech is already there). 👉Focus on Privacy & Integrity: Don't lead with fear or bans. Define exactly what student data can be used and what "honest work" looks like now. 👉 Group by Grade Level: A kindergartner doesn't need a chatbot, a high schooler needs to know how to use one responsibly. Tailor your policy to the age of the student. 👉 Be Transparent: Tell parents which tools you use and why. Trust is built through honesty, not a 50 page manual no one reads. The cost of waiting for "perfect information" is much higher than the cost of building a thoughtful framework and fixing it as you go. Is your district leading the AI reality or just reacting to it? #K12 #Education #AI #SchoolLeadership #EdTech #DigitalTransformation #DataPrivacy