Remote Learning Technologies

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

Two of the biggest problems I hear about in leadership development: 1/ “Learning doesn’t stick.” 2/ “We don’t have a culture of learning.” BOTH of these problems can be solved. The key is to create a “learning ecosystem.” I’m not saying it’s easy...It’s certainly not something you can do overnight. But, these 7 tactics can go a long way: 1/ Hold a monthly community of practice Get your audience together each month (on Zoom). Use the call to: - reinforce key learnings - forge peer connections - give everyone a chance to ask Qs & share challenges - facilitate practice 2/ Create a Resource Vault Store learning resources in one live folder. Keep your docs updated in real time: - Insert new examples - Take & apply real-time feedback from learners - Create new resources based on what learners need The goal here is to make the vault a place your learners return to often. 3/ Send Weekly Behavioral Nudges Weekly behavioral nudges: - are a simple way to double or triple the value of an existing assessment or training program - can take a one-and-done program/assessment and add a year-long tail of exercises and key insights Nudges = STICKY learning 4/ Give Every Learner Access to a REAL Coach Use message-based coaching to: - expand the number of employees you can offer coaching to - meet employees at the exact moment that they need help 5/ Create a Peer Learning Network Peer learning tech enables collaboration in new ways. (And in ways that in-person can’t) Example: One leadership development team at a big tech company used a simple Google doc where learners shared questions, insights, and examples from over a dozen locations. As their doc grew… - themes emerged - ideas intersected - they had a running record of key info 6/ Deliver Microlearning in the Flow of Work Micro-learning: - makes learning available on-demand (open book test) - helps increase repetition to build habits - brings learning into the flow of work 7/ Trigger Organic Conversations You might: - use conversational guides (between peers or between learners & managers). - use prompts in your peer learning network - hold breakouts in your community of practice The idea is that over time, your learners will naturally use the language and ideas from your learning in their daily conversations. ____ Apply these 7 tactics (or even just a few) and you'll be well on your way to creating a learning ecosystem. One that will: 1/ take in new topics and spit out behavior change 2/ generate more feedback than you can collect 3/ solidify a culture of learning What other components do you include in your programs? #leadershipdevelopment

Could a new layer of openness help unlock truly adaptive learning? Most learning materials still come in a single flavour: one language, one reading or grade level, one version for all. Open Educational Resources (OER) made a leap forward with free, openly licensed, remixable content. Yet most OER remain ‘fixed’, to be used ‘as is’. 𝐀𝐈 𝐭𝐨𝐨𝐥𝐬 𝐚𝐫𝐞 𝐛𝐞𝐠𝐢𝐧𝐧𝐢𝐧𝐠 𝐭𝐨 𝐬𝐡𝐢𝐟𝐭 𝐭𝐡𝐢𝐬 𝐩𝐚𝐫𝐚𝐝𝐢𝐠𝐦 With AI tools, this is changing. For example, UNICEF’s Accessible Digital Textbooks tool can already convert a single source file into multiple languages and accessible formats for learners with disabilities. Prompts can provide deeper personalisation, and emerging prompt libraries are a good start. But what if we reimagined prompts in the spirit of OER? What if they were openly licensed, shared, remixed and iteratively improved? This leads to a question:  𝐂𝐨𝐮𝐥𝐝 𝐰𝐞 𝐢𝐦𝐚𝐠𝐢𝐧𝐞 𝐬𝐨𝐦𝐞𝐭𝐡𝐢𝐧𝐠 𝐥𝐢𝐤𝐞 𝐎𝐩𝐞𝐧 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐏𝐫𝐨𝐦𝐩𝐭𝐬 (𝐎𝐋𝐏)? Picture prompts not as one-liners, but as modular, openly licensed learning objects that span subject areas, contexts, themes, and pedagogical models. They could: ● Live in a public, version‑controlled repository under open licences, where community feedback and up‑votes both surface the most effective versions and guide ongoing iteration ● Adapt automatically to learner and teacher profiles (such as language, reading level, accessibility needs, preferred themes and other interests) ● Support peer review, localisation, reuse across platforms, and model-agnostic design ● Integrate with national digital learning systems rather than sitting on the side‑lines We’re already seeing glimpses - like Gemini Gems and custom GPTs that package multi-step logic. But combining open licensing, profile-aware design, cross-platform integration, and iterative improvement could unlock more meaningful, accessible and scalable personalisation across contexts. There would be many challenges, of course: digital divides, bias in outputs, language limitations, and - who builds and maintains it? Would love to hear from others - educators, developers, AI practitioners, accessibility advocates, startups, and anyone exploring the intersection of learning and technology: What might help - or hinder - such a system to accelerate personalised learning opportunities across different contexts?

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

📢 New Report: Key Insights on Digital Learning in Canadian Post-Secondary Education I'm excited to share key findings from the 2024 Pan-Canadian Report on Digital Learning by Nicole Johnson at CDLRA/ACRFL ! This comprehensive report, based on surveys from Spring and Fall 2024, offers valuable insights into the current state and future trends of digital learning in Canadian post-secondary institutions. At D2L we were so excited to sponsor this research! Here are some of the key takeaways: Technology is Here to Stay: Respondents expect technology use in post-secondary education to continue increasing across all modalities, including hybrid and online learning. The most common technologies used in teaching and learning are learning management systems (LMS), online polling/quizzes, and video-based technologies. Hybrid Learning is Leading Growth: Of all learning modalities, hybrid learning is expected to grow the fastest. GenAI is on the Rise: There's a strong consensus that generative AI (GenAI) will become a normal part of post-secondary education within a few years, with many already using it for teaching activities and student learning. Future Outlook: While most respondents expect post-secondary education to be different in five years, there is an increased sense of pessimism compared to last year, stemming from concerns about funding, faculty support, and the sustainability of the current system. I encourage you to read the full report for a more in-depth understanding: https://lnkd.in/eqtDJWeV Let's discuss the implications of these findings for the future of education! #DigitalLearning #HigherEducation #EdTech #CanadianEducation #OnlineLearning #HybridLearning #GenAI #CDLRA #D2L

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?

What if you had a personal learning support system with custom AI helpers guiding you, challenging you, and giving you just the right practice at the right time? At work, I’ve been exploring strategies for using AI agents to deliver more personalized learning. With AI agent-driven experiences, you’re not just interacting with a chatbot, you’re learning through focused, goal-aligned support. Each agent plays a specific role: one might give you practice activities tailored to your skill level, another might offer feedback on what to improve, and another helps keep your learning aligned with your bigger goals. It’s not about dumping content. It’s about giving you the right nudge, the right challenge, or the right reflection at just the right time. That got me thinking… what if I built one just for me? Just for something I love and want to build my skills more on like 3D printing and laser cutting. This way not only do I learn more about AI ecosystems but something I enjoy. So I've added to my personal learning roadmap to start a side project to build an AI agent ecosystem that helps me learn through doing. One agent might quiz me on printer maintenance. Another could challenge me with a new project idea or walk me through troubleshooting a tricky print. Another might generate custom practice activities based on what I’ve struggled with. Because sometimes, the best way to level up is to design your own way there. #InstructionalDesign #GenAI #LearningDesign #eLearning #AIinLearning #CourseDevelopment #DigitalLearning #IDStrategy #EdTech #eLearningDesign #LearningTechnology #InnovationInLearning

Yesterday, I was in a group investor meeting and got a question I love—one I’m hearing more and more often: “What’s the difference between a traditional LMS and an AI-First learning platform?” It’s a simple question with a big answer—because it reflects the shift we’re leading at Docebo. Here’s how I explained it: From System of Record to System of Intelligence: First, we’re moving from platforms that track learning to platforms that drive it. Five pillars define this shift. 1️⃣ Agentic Automation AI isn’t just assisting, it’s operating. With Docebo Harmony, we’re embedding AI agents that automate admin work, content tagging, learner nudges, even orchestrating workflows across third-party tools. Think of it as your learning co-pilot—working even when you sleep. 2️⃣ AI-Powered Content Creation for All Docebo Creator empowers anyone—not just L&D—to build high-quality, localized content in seconds: • AI Video Presenters • AI Podcasts • Auto-translation • Collaborative authoring 3️⃣ Hyper Connected Neural Search = Knowledge Activation Imagine asking a question and instantly receiving an answer tailored to your organization—then turning it into a course. That’s Docebo Neural Search. It understands intent, not just keywords—and it learns with you. It starts from within Docebo sources and expands across multiple sources of information (your Google Drive, Confluence, Slack etc) 4️⃣ Hyper-Personalization at Scale AI dynamically maps skills, closes gaps, and adapts each learner’s journey in real-time. This isn’t one-size-fits-all—it’s one-size-fits-one. 5️⃣ Learning by Doing From scenario-based simulations to interactive labs, we’re bringing immersive learning to the enterprise. Because people don’t just learn by watching. They learn by doing. This is the shift from LMS to AI-first. From static to adaptive. From content consumption to intelligent enablement. We’re not just building software—we’re helping organizations unlock human potential through intelligent learning. It is an ambitious plan. We are working our way through lots of AI-Noise and the usual dilemma of innovate, versus micro improvements to the status quo. But here is the thing, the status-quo is no longer enough. There is no choice but to innovate at high speed. #AI #FutureOfWork #LearningTech #Docebo #AgenticAI #CorporateLearning #LMS #ExperientialLearning

AR: Making Learning Fun and Interactive Remember those frustrating days of trying to fold origami or build a model from instructions alone? AR is here to change that! Inna Horobchuk’s video perfectly demonstrates how AR can transform the learning experience. Using Snap Spectacles, she effortlessly creates a paper plane, making the process both practical and engaging. AR and VR have the potential to revolutionize education by turning abstract concepts into tangible, interactive experiences. Instead of passively reading or watching, students can actively participate and experiment, making learning more fun and effective. While there may be initial hesitation, it's time to embrace these innovative tools. By incorporating AR and VR into education, we can open up new possibilities for learners of all ages and create a more exciting and engaging learning environment. Here are three possible uses: -Robotics: Students can interact with virtual robots, experimenting with different programming techniques and troubleshooting issues in a safe and controlled environment. -Design: Interior designers can visualize their creations in real-world settings, experimenting with different layouts, colors, and materials before committing to physical changes. -Medicine: Medical students can practice complex procedures on virtual patients, gaining valuable experience and honing their skills without the risk of harming real individuals. AR and VR offer immersive and interactive learning experiences that can enhance understanding, improve retention, and prepare students for real-world challenges. By embracing these technologies, we can create more engaging, effective, and accessible learning environments. What do you want to add to the list?