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.

The Department for Education has published its "Technology in Schools Survey 2024–25", and the findings offer a clear picture of how digital capability is evolving across the sector Here are some of the insights that stood out: 🔹 Digital strategies are becoming the norm 70% of secondary schools now have a digital strategy in place, and teacher engagement in digital planning has increased significantly since 2023. But only around a third of schools have any framework for evaluating the impact of their technology use, a reminder that strategy alone isn’t enough without measurement. 🔹 AI adoption is accelerating 44% of teachers report using Generative AI tools, mainly for lesson planning and admin. Younger teachers are leading the way, while leaders report growing challenges around pupil use, from plagiarism to misinformation. Most schools expect to expand AI training over the next two years. 🔹 Infrastructure is improving at pace Schools are rapidly upgrading: Wi-Fi 6, full-fibre broadband, improved cybersecurity practices and greater use of cloud-based storage. Secondary settings continue to demonstrate higher “digital maturity” overall. 🔹 Technology is increasingly linked to workload reduction and attainment 61% of leaders and 43% of teachers say technology has reduced workload over the last three years, with the biggest time-savers being planning, data management, resource sharing and communication. Two-thirds of leaders believe technology has improved pupil outcomes. 🔹 But classroom device use remains limited Despite better access to hardware, most teachers (around 75%) still use end-user devices in fewer than a quarter of lessons. The shift towards more digital-first pedagogy is happening, but slowly. 🔹 Financial barriers remain the biggest challenge Budget constraints continue to top the list of obstacles. Staff confidence and access to CPD are also recurring themes, particularly as technology evolves faster than training can keep up. The report reinforces a message many of us know well: technology alone doesn’t improve learning, strategy, capability, culture and investment do. AI literacy, cloud-first infrastructure, accessibility tools, and digitally confident staff are becoming essential components of a modern, resilient, future-ready institution.

🌍 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

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

Resistance isn’t the enemy of change. Poor planning is. Change doesn’t fail because people are difficult. It fails because leaders rush in without structure. That’s why the ADKAR model works - it gives you a step-by-step way to make change stick. Step 1: Awareness Start by making the case for change. – Share the “why” with clarity – Use data and relatable stories – Highlight what’s at risk if nothing changes Step 2: Desire Create personal buy-in. – Speak directly to individual concerns – Tie the change to personal wins – Invite feedback, don’t just announce Step 3: Knowledge Make learning simple and accessible. – Train based on roles, not just theory – Break content into smaller lessons – Encourage peer learning Step 4: Ability Create space for hands-on experience. – Pilot with smaller teams – Offer coaching and feedback – Let teams experiment and iterate Step 5: Reinforcement Make sure the change sticks. – Track adoption with real metrics – Celebrate visible progress – Keep communication going Change isn’t about pushing harder. It’s about planning smarter. Now the question is: Where are you seeing resistance today? -- 📌 If you want a high-res PDF of this sheet: 1. Follow Daniel Lock 2. Like the post 3. Repost to your network 4. Subscribe to: https://lnkd.in/eB3C76jb

📘 New evidence from the European Commission’s JRC on Generative AI in secondary education – and why VET should pay close attention https://lnkd.in/eAG6E5T3 💡This JRC study explores how early adopters across five EU countries are already using Generative AI (GenAI) in schools. While focused on general secondary education, its insights are highly relevant for VET, skills systems and workforce development, where the boundary between learning and work is even thinner. 🔍 GenAI is moving fast from “disruption risk” to “pedagogical tool” – but policy, skills and institutions are struggling to keep up. 🧠 Key themes and takeaways (with a VET lens): 🤖 AI literacy is now a core skill ▪️GenAI reshapes what “digital competence” means for learners and teachers. ▪️AI literacy goes beyond tools: it includes critical thinking, ethics, bias awareness and human agency. ▪️For VET, this is directly linked to employability, adaptability and lifelong learning. 👩🏫 Teaching practices are already changing ▪️Early adopters use GenAI to personalise learning, simplify complex concepts and generate feedback. ▪️Teachers save time, but only if they understand how the system works. ▪️In VET, this mirrors the need to support trainers in dual systems, work-based learning and skills validation. 📝 Assessment is under pressure ▪️Traditional assessment models are challenged by GenAI’s capacity to generate content ▪️Shift needed towards competence-based, authentic and performance-oriented assessment ▪️This aligns perfectly with long-standing VET principles – but requires system-level support 👥 Students are ahead of institutions ▪️Learners use GenAI extensively as a “personal assistant” ▪️They value efficiency, but still want human feedback, presence and trust. ▪️Risk: widening digital divides if access and guidance are unequal – a major concern for inclusive VET ⚖️ Ethics, integrity and governance lag behind ▪️Concerns focus on plagiarism, bias and data protection ▪️Broader issues (environmental impact, digital sovereignty, labour behind AI) are largely absent ▪️VET has a responsibility to reconnect AI use with values, citizenship and decent work 🏗️ Policies and support are not ready (yet) ▪️Teachers and leaders report insufficient guidance, training and infrastructure ▪️The AI Act, DigComp 3.0 and the upcoming AI Literacy Framework are crucial – but implementation will be key ▪️For VET, this calls for systemic approaches, not isolated pilots 🧩 Looking ahead: ▪️Excellence in skills systems will increasingly depend on how well we combine: technological capability, pedagogical innovation, inclusion, and human judgement ▪️Centres of Vocational Excellence, strong teacher/trainer development, and coherent skills governance are more relevant than ever #ArtificialIntelligence #DigitalEducation Romina Cachia, PhD Daniel Villar-Onrubia, DPhil Christian Rietz Hannele Niemi Dr. Michael Hallissy Robert Reuter EU Employment and Skills

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

After 13 years of teaching, I banned all phones and laptops in my classroom, and got the best reviews I’ve ever received! Hard to believe students gave me BETTER reviews after I made them put away their digital lifelines? Let me explain. Initially, students were skeptical. But after a couple weeks, they were more engaged, absorbed information better, and actually enjoyed class time. The research backs this up: students who take handwritten notes retain significantly more information than those typing on computers. And the mere presence of smartphones (even when turned off) reduces cognitive capacity and makes social interactions less engaging. While 11 states have enacted statewide phone bans in K-12 schools, this trend hasn't quite caught on at colleges and universities where it's desperately needed. Yes, 18-year-olds are legal adults, but they still need structure to optimize their learning – their prefrontal cortices aren't fully developed yet. We can't turn back time to the flip phone era, but we can preserve our classrooms as sacred spaces for genuine teaching and learning. More thoughts in my The New York Times piece, linked in the comments below. #HigherEducation #StudentLearning #TechInClassroom

The shift toward #onlinelearning is enhancing #highered's ability to meet all students where they are. But much work still remains to educate all relevant stakeholders—including policymakers, institutional leaders, and even students’ families—about the potential benefits tech-enabled learning can yield. As the president of Western Governors University, I recognize the unique role I can play in elevating this discussion. Today, both innovative online universities and established brick-and-mortar institutions are leveraging technology to provide students with greater flexibility and personal ownership over their experience; recently it was reported that 70% of college students are enrolled in at least one online course. But offering online courses or even programs doesn’t necessarily mean an institution is fully capitalizing on technology’s potential. As with any innovation, its potential rests in how it’s deployed. Unfortunately, online learning is often deployed with the same artificial constraints that exist in traditional models of learning, ensuring its impact will be limited. (It's been said before, but I'll say it again: delivering lectures via Zoom is not quality online learning). In stark contrast, effective online learning design should be purposefully designed for the virtual environment, leveraging digital tools and approaches that would be difficult to replicate in-person, at scale. Thanks to advances in technology, for instance, readily available data on how students are doing can empower faculty to reach out to students in need—and critically before they fall too far behind and get discouraged. At WGU, we use machine intelligence to better understand our students’ momentum at a given moment, drawing on indicators such as how they’re interacting with learning resources, the extent to which they’re engaging with faculty, and how they’re progressing. By identifying when students have less momentum and are in greater need of support, our faculty are empowered to design personalized interventions when students need them the most, which we’ve shown improves retention and progression. Compiling this sophisticated level of actionable information simply would not be possible without the support of technology. I’d love to know—how else are you seeing online learning deployed deliberately and effectively?

Nothing says you are ready for modern legal practice quite like spending three years learning nineteenth century doctrine and then getting asked on your first day why a chatbot cannot be hired as counsel. New lawyers are starting to enter offices where clients are already using AI tools, where machine generated text shows up in email threads, and where people assume (incorrectly) that any confident sounding output must be legitimate. Lawyers are expected to explain why a prompt is not legal advice and why a judge will not be swayed by a hallucinated citation that an algorithm invented on a Tuesday afternoon. These are not side issues anymore. They are part of daily practice. Yet most law schools still treat the modern tools of the profession as an optional extra rather than a core competency. Students leave knowing the rule against perpetuities but with little sense of how to evaluate or supervise systems that now sit inside research platforms, drafting tools, and client communication channels. Updating legal education is not about replacing doctrine. It is about giving students the ability to understand the systems they will rely on, identify where those systems break down, and make sound judgments about when technology supports the analysis and when it quietly undermines it. That kind of training requires more than a scattered elective. It requires curriculum that reflects the reality of the work. Law schools that take this seriously will prepare students for the world they are actually entering. Those that do not will keep producing graduates who know the law but are left to figure out modern practice on their own, one awkward chatbot conversation at a time. I'm Colin, General Counsel at Malbek and author of The Legal Tech Ecosystem. #legaltech #innovation #law #business #learning