Remote Learning Technologies

Last week Google announced Learn Your Way - a research experiment to reimagine the most overused, under-loved artifact in education: the textbook. The problem is obvious: textbooks are one-size-fits-all. Written once, updated rarely, inflicted equally. Great for industrial-scale learning, terrible for actual students. Learn Your Way tries to fix that with AI: a student picks their grade level and interests (sports, music, food). The system then “relevels” the text, swaps out generic examples for personalized ones (Newton’s apple becomes a soccer ball), and builds a personalized core. From there, it spins out multiple formats: immersive text with visuals, section-level quizzes, narrated slides, Socratic dialogues, even mind maps. In a controlled trial with 60 high schoolers, it beat the humble PDF reader across the board: comprehension, retention, and preference. AI is going to fundamentally change education. The way I see it, we will move from: ▪️Standardization → Personalization: Education has been built for scale: 1 teacher, 30 students, 1 chalkboard. AI flips that. Materials adapt to pace and interest; assessment becomes continuous, not blunt. ▪️Knowledge Transfer → Cognitive Coaching: When facts are instantly accessible, memorization stops being the scarce skill. The real edge is knowing when AI is wrong, asking sharper questions, and connecting ideas across disciplines. ▪️Classrooms → Learning Ecosystems: Teachers shift from lecturers to facilitators and motivators. AI covers explanations and drills; humans teach judgment, values, and meaning. Peer learning deepens when everyone brings AI-augmented insights. ▪️Exams → Evidence of Thinking: With AI co-pilots, recall-based tests lose power. Evaluation moves to process, projects, and defense - not “what’s the answer?” but “show your reasoning.” ▪️Scarcity → Abundance (with new inequities): AI promises tutoring for anyone with a smartphone. But access to devices, connectivity, and high-quality models could widen divides. A new gap may emerge between students trained to use AI critically and those who consume it passively. Here's the irony: in making information abundant, AI paradoxically revives the oldest form of teaching. Socrates didn’t assign PDFs; he asked questions until you realized you didn’t know what you thought you knew. His role wasn’t to supply answers but to train skepticism. That is the teacher’s role again. Not to out-explain Gemini, but to show when not to trust it. To cultivate judgment, doubt, and the art of better questions. AI hasn’t reinvented education so much as rerouted it back to its roots: the Socratic method - only now Socrates is paired with a chatbot that never sleeps and never hesitates.

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

Quarterly trainings don’t build mastery, daily reps do. When I started my career, “practice” meant awkwardly presenting in front of a manager or peer. They were scripted, rushed, and rarely stuck. Learning happened in events, not in habits. Fast forward to today, and the landscape looks completely different. Last week, we had the privilege of joining the Google Mastery team in San Francisco to dive deeper into this shift. What stood out to me in those conversations is how much learning has evolved, and how leaders are rethinking it as a continuous, embedded process. Huge shoutout to Myles Riseborough, Shruti Shah, Dr. Janine Lee, MBA, Ed.D., Chase Knowles, and Jennifer Raven-Harris, and the team for championing this movement 🙌 Why now? 1) AI has unlocked scalable practice. No more waiting for facilitators or fixed scripts, adaptive simulations can run anytime, anywhere. The “practice room” is always open. 2) Tech ecosystems are finally integrated. CRMs, enablement tools, and conversation intelligence systems are no longer silos. This creates a rich data fabric to trigger personalized practice and feedback loops. 3) Measurement is automated. Skill growth used to be subjective. Now, AI scorecards quantify behaviors in real time and tie them directly to business outcomes. 4) Culture has caught up. Shorter product cycles and competitive markets mean one-off training isn’t enough. Continuous “everboarding” is becoming the norm. 🔑 Takeaway: Learning is shifting from events to ecosystems. The most effective organizations will blend high-impact moments (like onboarding or certifications) with always-on, learner-led development, embedded right in daily workflows. To leaders: Does your company have a culture of continuous practice, not just when training is scheduled?

Reimagining Bloom’s Taxonomy with AI: The Future of Learning Design For decades, Bloom’s Taxonomy has been the foundation for structuring learning objectives. But with AI tools, we can now unlock each level of Bloom’s hierarchy in more practical, personalized, and scalable ways—transforming how learners absorb, apply, and innovate knowledge. Here’s how AI supports each stage, with outcomes that matter for modern L&D: 🔹 Create – Tools like ChatGPT, Canva AI, Gamma help design projects, assessments, and innovative solutions. 👉 Outcome: Encourages innovation, design-thinking, and co-creation—key drivers for organizational growth in the digital era. 🔹 Evaluate – Tools like Consensus, Eduaide, Claude assist learners in critiquing arguments and peer-reviewing work. 👉 Outcome: Develops judgment, discernment, and evidence-based evaluation skills needed in leadership roles. 🔹 Analyze – Tools like Perplexity, Claude, Elicit help compare perspectives, organize data, and identify patterns. 👉 Outcome: Enhances critical thinking and decision-making, vital for solving ambiguous and complex business problems. 🔹 Apply – Tools like MagicSchool AI, Gemini, Photomath demonstrate step-by-step problem-solving. 👉 Outcome: Learners practice application in simulated environments, boosting confidence to solve workplace challenges. 🔹 Understand – Tools like ChatGPT, Otter.ai, Brisk Teaching simplify complex concepts using analogies and real-world examples. 👉 Outcome: Learners move beyond rote memorization to grasp concepts deeply, enabling transfer to new situations. 🔹Remember – Tools like QuizGPT, Kahoot, Quizizz generate flashcards, quizzes, and recall games. 👉 Outcome: Strengthens foundational knowledge, reduces cognitive load, and ensures faster retrieval of information. AI doesn’t replace Bloom’s Taxonomy; it elevates it into a dynamic ecosystem where learning is continuous, contextual, and customized. For L&D leaders, this means moving from "training delivery" to "learning orchestration." The future is clear: by embedding AI into Bloom’s framework, organizations can build smarter learning journeys that not only measure learning outcomes but also directly impact business performance. How is your organization blending AI with Bloom’s Taxonomy to build future-ready learners? #LearningAndDevelopment #AI #FutureOfWork #InstructionalDesign #BloomTaxonomy #DigitalLearning #WorkplaceLearning

The Chan Zuckerberg Initiative just unveiled foundational resources that put educators at the center of the AI era, building the public infrastructure needed for trustworthy, research-backed tools in every classroom. 📍 Knowledge Graph: An open, machine-readable map of academic standards, math learning components, and learning progressions. It works like a navigation system for learning, allowing AI tools to chart precise pathways through academic content. With datasets covering standards from all 50 states across English, math, science, and social studies plus detailed breakdowns of math concepts into smaller learning components - Knowledge Graph makes it possible to design tools that understand learning as a sequence of interconnected skills, much like a GPS mapping roads and routes. 📊 Evaluators: Open tools that check AI-generated outputs for accuracy, rigor, and grade-level appropriateness, beginning with literacy. Developed in partnership with leading experts, these Evaluators help ensure teachers can trust the quality of AI-generated passages, exercises, and other content. 🤝 Claude Integration: Educators can now access Knowledge Graph directly in Anthropic Claude giving them powerful new ways to design lessons and materials grounded in research-backed content, academic standards, and learning progressions. Here’s why this is a big deal: many teachers already turn to Claude for planning and content creation. By connecting Claude to Knowledge Graph through a custom MCP server, its outputs are no longer just  helpful — they’re trustworthy. Teachers can rely on responses that align with state standards and the science of how students learn. Because the integration is built on the open MCP, in the future, they're working on enabling any AI model or edtech tool to more easily plug into Knowledge Graph. This sets the foundation for an entire ecosystem of education technology that’s coherent, rigorous, and easier for educators to trust at scale. 🌳 Learning Commons: CZI's work in education will now be called Learning Commons reflecting their sharpened focus and role within the education ecosystem. CZI is committed to building the core AI infrastructure that supports educators in the classroom, deepening partnerships with teachers, researchers, and developers. As its tools move from private beta to broader availability in 2026, Learning Commons will carry forward the same values: working for a future where education and technology unlock student potential and accelerate meaningful progress for all. This commitment includes continued collaboration across the education ecosystem: co-building the future with educators, district leaders, researchers, and developers. Congrats to the amazing team who led this: Sandra Liu Huang, Helen Hwang, Kristin M., Dan Quine, Frankie Warren, Grace Kuo, Raymonde Charles, Alicia Pompei Links in comments Read Sandra's post here: https://lnkd.in/e38iyAKK

Language learning has always been a rich field of exploration for teachers and students, and today’s digital landscape gives us more tools than ever to make the journey engaging and effective. From AI chatbots that can generate tailored grammar activities or help refine pronunciation, to classic exchange platforms where learners connect with peers around the globe, the options are diverse. What excites me (as a former language teacher) is not only the sheer learning possibilities these tools create, but also they can work together: AI to scaffold learning, apps to practice daily, exchanges to build fluency, and podcasts or videos to bring language into everyday contexts. Think of it like creating a language ecosystem for your students. A learner can start a day with Duolingo or Babbel, get feedback on writing from Grammarly, chat with a partner on Tandem, and finish by listening to Luke’s English Podcast on their commute. That mix of structured practice and authentic interaction is what helps language stick. This visual brings together a wide range of resources (e.g., AI-powered chatbots, apps, exchange platforms, YouTube channels, TED talks, and podcasts) that teachers can weave into their practice and students can explore independently. Full guide link the in first comment

A student once asked me, ‘Sir, will AI replace teachers?’ I paused, smiled, and said, "Not teachers—but it will change how we teach forever." As an educator and entrepreneur, I’ve witnessed every shift in the education industry, from chalkboards to digital classrooms. But nothing has intrigued me more than the rise of AI in education. A few months ago, a student in my class struggled with understanding rotational mechanics. Despite multiple attempts, he couldn’t grasp the concept. So, I experimented. I used an AI tool to create personalized simulations of real-life scenarios he could relate to. Within 30 minutes, the light bulb went off—he finally got it. That’s the power of AI. It’s not here to replace teachers; it’s here to empower us. How I See AI Shaping the Future of Education: → Personalized Learning Every student learns differently. AI allows us to create customized learning paths based on strengths, weaknesses, and pace. Imagine a classroom where no one feels left behind. → Better Access to Quality Education AI-powered tools can bring the best teachers and resources to even the most remote corners of the world, bridging the education gap like never before. → Liberating Teachers AI can take over repetitive tasks—grading, administrative work—so teachers can focus on what truly matters: teaching, mentoring, and inspiring. AI is a tool, not a solution. The magic of education lies in the human connection—a teacher understanding a student’s unspoken hesitation or cheering their smallest victories. At Motion Education Pvt Ltd, we’re already exploring how to integrate AI into our teaching methodologies without losing that human touch. Because the future of education isn’t man vs. machine—it’s man with machine. So, to my students: Don’t fear AI. Embrace it. Use it to amplify your learning. And to my fellow educators: Let’s lead this revolution together. The classrooms of tomorrow are in our hands. What do you think? Will AI transform education for the better, or is there more to consider? Let’s discuss. #AI #AIinEducation #EdTech #NVSir

𝗛𝗼𝘄 𝘁𝗼 𝗖𝗿𝗲𝗮𝘁𝗲 𝗮 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺 🌐 Struggling with disconnected learning platforms and resources? I get it—fragmented learning experiences can derail your L&D programs, making them less efficient and effective. When your team has to juggle multiple systems, it hampers their ability to learn and grow seamlessly. Here’s how you can build an integrated learning ecosystem to connect all your platforms, resources, and tools for a smooth, unified learning experience: 📌 Centralize Your Resources: Start by consolidating all learning materials into a single, accessible repository. This can be a Learning Management System (LMS) or a centralized digital library where employees can easily find what they need. 📌 Integrate Platforms: Use APIs and integration tools to link your LMS with other systems like HR software, productivity tools, and communication platforms. This ensures a cohesive experience where data flows seamlessly between platforms. 📌 Standardize Processes: Develop standardized protocols for content creation, curation, and deployment. This includes using consistent formats and templates, which help maintain quality and uniformity across all learning materials. 📌 Personalize Learning Paths: Leverage data analytics to create personalized learning paths for employees. Tailored content keeps learners engaged and ensures they acquire the skills most relevant to their roles. 📌 Foster Collaboration: Encourage peer-to-peer learning and knowledge sharing through forums, social learning platforms, and collaborative projects. This builds a community of continuous learning and support. 📌 Track Progress and Feedback: Implement tools to monitor learning progress and gather feedback. Use this data to continuously improve your L&D programs, ensuring they remain relevant and effective. By developing an integrated learning ecosystem, you’ll transform fragmented experiences into a cohesive journey that enhances learning efficiency and effectiveness. Your team will thank you for making their learning process smoother and more intuitive. What strategies have you used to create a seamless learning ecosystem? Share your insights below! ⬇️ #LearningAndDevelopment #TrainingInnovation #OnlineLearning #EdTech #LMS #EmployeeEngagement

Microsoft Education has just released its 2025 Artificial Intelligence in Education report - a global snapshot of how AI is shaping learning, leadership, and future-ready skills across K–12 and higher education. A few key insights resonate with me, with the final one surely essential: * 𝐀𝐈 𝐢𝐬 𝐢𝐧 𝐜𝐥𝐚𝐬𝐬𝐫𝐨𝐨𝐦𝐬, 𝐛𝐮𝐭 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞 𝐢𝐬 𝐥𝐚𝐠𝐠𝐢𝐧𝐠. While 86% of institutions report using generative AI, fewer than half of educators and students feel confident navigating it. AI fluency is quickly becoming as essential as digital literacy once was. * 𝐒𝐭𝐮𝐝𝐞𝐧𝐭𝐬 𝐚𝐫𝐞 𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐛𝐢𝐠𝐠𝐞𝐫 𝐰𝐢𝐭𝐡 𝐀𝐈. Tools like Copilot empower learners to brainstorm, reflect, and expand ideas - especially when combined with peer collaboration and thoughtful instructional design. * 𝐀𝐈 𝐚𝐦𝐩𝐥𝐢𝐟𝐢𝐞𝐬, 𝐧𝐨𝐭 𝐫𝐞𝐩𝐥𝐚𝐜𝐞𝐬, 𝐭𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠. From reading comprehension to writing, AI is most effective as an assistant that supports deep learning rather than a substitute for it. * 𝐄𝐝𝐮𝐜𝐚𝐭𝐨𝐫𝐬 𝐚𝐫𝐞 𝐞𝐦𝐛𝐫𝐚𝐜𝐢𝐧𝐠 𝐀𝐈 𝐭𝐨 𝐫𝐞𝐜𝐥𝐚𝐢𝐦 𝐭𝐢𝐦𝐞. By reducing lesson prep, supporting differentiated instruction, and streamlining administrative tasks, AI helps teachers focus on what matters most: relationships and pedagogy. * 𝐄𝐪𝐮𝐢𝐭𝐲 𝐦𝐮𝐬𝐭 𝐠𝐮𝐢𝐝𝐞 𝐀𝐈 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧, 𝐧𝐨𝐭 𝐡𝐲𝐩𝐞. Early data suggests AI isn’t widening socioeconomic gaps, but inclusive access, scaffolding, and diverse representation in tool development remain critical. * 𝐀𝐈 𝐬𝐤𝐢𝐥𝐥𝐬 𝐚𝐫𝐞 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐜𝐚𝐫𝐞𝐞𝐫 𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲. With 66% of employers unwilling to hire without AI literacy, students must learn to lead with AI, not just use it. * 𝐓𝐞𝐚𝐜𝐡𝐞𝐫𝐬 𝐰𝐚𝐧𝐭 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 - 𝐚𝐧𝐝 𝐭𝐡𝐞𝐲 𝐦𝐞𝐚𝐧 𝐢𝐭. High-quality, contextual, job-embedded professional development is non-negotiable. This can’t be another “figure it out as you go” initiative. * 𝐒𝐭𝐮𝐝𝐞𝐧𝐭 𝐯𝐨𝐢𝐜𝐞 𝐢𝐬 𝐞𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥. Young people want to shape how AI is integrated into their learning. Let’s co-design the future with them, not just for them. This report is a timely reminder: AI can be more than a time-saver. Done right, it can spark creativity, enhance equity, and help us reimagine learning cultures grounded in agency, curiosity, and care. (Full report can be found in comments)

One of the premises of AI for education is the opportunity to create a more engaging and customized learning experience. Today we are introducing a new research experiment, Learn Your Way, which uses generative AI to transform static educational content into a learner-driven engaging experience. For textbook material, it generates multiple representations based on the source material - from mind maps and audio lessons to immersive text with interactive quizzes. Our recent efficacy study shows this approach can lead to improved learning outcomes on both short and long term recall tests. The system is grounded in learning science and powered by our pedagogy-infused family of models, LearnLM, which is now integrated directly into Gemini 2.5 Pro. Try the experience via Google Labs: https://lnkd.in/drGfTZpw Read more about the research on our blog: http://goo.gle/3KqM8i0 And in technical paper: https://lnkd.in/dZuUeKpa