How Educators can Shape Edtech Development

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.

Something unexpected has emerged in my AI literacy research that's challenging conventional wisdom: the critical role of acculturation patterns in how AI literacy actually develops in educational settings. Most frameworks treat AI literacy as a structured set of skills to acquire - a checklist of competencies to master. But what I'm observing in classrooms and teacher workshops is something far more organic and culturally embedded. It mirrors how communities have historically adopted and adapted to new cultural tools. Let me share a pattern I've seen repeat across multiple schools: It begins with personal experimentation, often kept private. Teachers and students explore AI tools on their own, testing boundaries and building personal comfort. This phase is marked by curiosity but also hesitation - a natural part of engaging with any transformative technology. Then comes a pivotal shift: tentative sharing with trusted colleagues or peers. A teacher mentions using ChatGPT for lesson planning in the break room. A student shows a classmate how they're using AI to brainstorm essay topics. These small moments of vulnerability and exchange begin building a shared understanding. The most fascinating stage emerges next: collaborative exploration and systematic integration. Once enough individual comfort exists, communities begin collectively reimagining their practices. I watched one department move from individual experimentation to co-creating AI-enhanced curriculum units within a semester. The key wasn't just training - it was trust and shared experience. What's particularly striking is how this pattern mirrors historical educational technology adoption, from calculators to computers. Yet AI adds a unique dimension: the tool itself participates in and shapes this acculturation process. It's not just a static technology to master but an interactive partner in the learning process. This raises profound questions about how we support this cultural transition. Should we focus less on formal training and more on creating safe spaces for experimentation? How do we honor the organic nature of this process while ensuring equitable access and development? #AIResearch #EducationalChange #TeacherDevelopment #EdTech Dr. Sabba Quidwai France Q. Hoang Pat Yongpradit Mike Kentz Phillip Alcock Doan Winkel Jason Gulya Marc Watkins Sonia Kathuria MA. Ed

While the world races to scale artificial intelligence, we asked a different question: What would it look like if those closest to students, teachers, led the conversation about how AI shows up in schools? The result: The Teacher-Created AI Guidelines — born out of the Codesign Collective, an innovation from Leanlab Education, with 228 Accelerator as a facilitation partner. These guidelines are not corporate white papers or top-down policy briefs. They are crowdsourced human intelligence, built from the lived experiences, fears, hopes, and wisdom of real educators, designing for justice at the intersection of AI and learning. In a moment where hype outpaces humanity, these guidelines center: 1. Equity over efficiency 2. Agency over automation 3. Relationships over replacement 4. Design with—not for—communities Why does it matter? Because how we design AI now will shape who it serves — and who it leaves behind — for generations. Read the complete guidelines. Share them. Use them. And most importantly: let educators lead. #AI #Education #EquityXDesign #CodesignCollective #TeacherVoice #HumanIntelligence #EdTech #EthicalAI #LiberatoryDesign https://lnkd.in/ewmbbzrD

To mitigate harm and improve EdTech, start by listening to teachers! - That is the big takeaway on the use of AI in education from this new research. “Teachers have to be on board. And teachers’ input about their students is supremely important in creating these tools. Because if a teacher is not bought in, they are not going to use it with fidelity… So yes, I get principal buy-in and support is important. But do not forget the teachers… The teachers are supremely important in making all of this happen. So listen to them” (pp. 14). The paper from Cornell University, "Do not Forget the Teachers: Towards an Educator-Centered Understanding of Harms from Large Language Models in Education", makes one thing clear. AI in education will only succeed if teachers are part of the process from the beginning. Too often, AI tools are designed without considering how teachers and students will actually interact with them. This research highlights a clear disconnect. EdTech companies focus on technical risks such as bias, privacy, and hallucinations. Teachers are more concerned about the long-term impact on student learning, teacher workload, and equity. One of the key findings is that AI tools should be designed with teacher input from the start, not added as an afterthought. Teachers need the ability to shape AI tools based on their real-world classroom experiences and provide direct feedback on how students are engaging with them. If we want AI to truly enhance education, we need a fundamental shift toward educator-centered AI governance. That means: - Teachers involved in AI tool design and development. - AI tools built to align with evidence-based teaching practices. - School leaders ensuring teachers have the final say in how AI is used in their classrooms. Thank you to the authors, Emma Harvey, Allison Koenecke, and Rene Kizilcec of Cornell University The research was shared by Ben Williamson from The University of Edinburgh. Link to download the paper in the first comment. #aiineducation #edtech #teachers #educationpolicy #aigovernance

Often, when we discuss tech in education, we focus on student-facing tools: smarter apps, adaptive platforms, and AI tutors. But the most critical layer is the teacher. Without a teacher who understands the "why" and "how" of technology, even the best tools risk being underused or misapplied. Just came across this inspiring case study from Kerala, India. The state government’s e-learning platform KOOL, launched in 2018, has now upskilled and certified over 58,000 school teachers in AI and emerging technologies. This is a systemic reboot of pedagogy. This is exactly the kind of foundational investment that creates lasting impact. Upskilling teachers creates a ripple effect. Each empowered educator influences hundreds, if not thousands, of students over their career. It builds institutional confidence, reduces resistance to change, and fosters a culture of continuous learning within schools themselves.    When teachers are confident and competent in emerging technologies, the whole system becomes more resilient, adaptive, and ready for whatever comes next. Read more here: https://lnkd.in/gZuZFkAZ    #AIForEducation #AIForIndia #AIAdoption

🚨 𝗦𝘁𝗼𝗽 𝗯𝘂𝘆𝗶𝗻𝗴 𝘀𝗵𝗶𝗻𝘆 𝘁𝗼𝗼𝗹𝘀. 𝗦𝘁𝗮𝗿𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝘄𝗼𝗿𝗸 𝗦𝗵𝗮𝗽𝗲 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 whitepaper from Bett, ASCL and Educate Ventures highlights the same gaps across schools: ⚠️ Four recurring problems • 𝗡𝗼 𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆, leaving schools to decide on AI and EdTech alone • 𝗗𝗲𝘃𝗶𝗰𝗲𝘀 𝗮𝗿𝗿𝗶𝘃𝗶𝗻𝗴 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴, creating frustration and underuse • 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 squeezed into full timetables, with leaders calling for protected, mandatory training time • 𝗢𝗻𝗲-𝗼𝗳𝗳 𝗴𝗿𝗮𝗻𝘁𝘀 that block long term planning 💡 What the report makes clear Technology only improves learning when schools invest in more than devices. Invest in: • 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 • 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗳𝘂𝗻𝗱𝗶𝗻𝗴 • 𝗦𝘁𝗮𝗳𝗳 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 🔎 Why EdTech leadership matters • Aligns technology with learning goals • Secures sustained resources and a clear strategy • Embeds training so tools support teaching rather than sit unused ❓ Question How is your school balancing tools, training and strategy? 📄 Download the whitepaper (PDF) https://lnkd.in/ebg_rdjm