Remote Learning Technologies

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

𝐇𝐨𝐰 𝐜𝐚𝐧 𝐰𝐞 𝐝𝐞𝐬𝐢𝐠𝐧 𝐀𝐈 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐨𝐧𝐬 𝐭𝐡𝐚𝐭 𝐩𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐬𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐨𝐯𝐞𝐫 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞? 𝗧𝗵𝗲 𝗰𝗼𝗿𝗲 𝗮𝗿𝗴𝘂𝗺𝗲𝗻𝘁: Large language models (LLMs) are rapidly transforming knowledge work by improving the quality and efficiency of tasks such as writing, coding, and data analysis. However, their growing use in education has exposed a learning-performance paradox: while they can enhance short-term task performance, they may also undermine genuine learning, including cognitive growth, knowledge transfer, and metacognitive development. I'm thrilled to share that I have been working with the dream team Dragan Gasevic, Shazia Sadiq, Lixiang (Jimmie) Yan, Jason M. Lodge, Jason Tangen, Paul Denny, Kristen Eignor DiCerbo, Simon Buckingham Shum, and Ryan Baker to ground a response that tackles this head-on: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗜 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘀𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗼𝘃𝗲𝗿 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲. 📄 Preprint available here: https://lnkd.in/gbts24D2 This paper addresses the question of how artificial intelligence should be designed and used to support learning rather than merely improve immediate outputs. We introduce the concept of AI learning companions, defined as adaptive, pedagogically informed, LLM-powered agents designed for integration into learning environments, built around three foundations: 🧠 𝗣𝗲𝗱𝗮𝗴𝗼𝗴𝗶𝗰𝗮𝗹 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻: How students learn with AI, grounded in deep and interactive learning, guided scaffolding, metacognitive development, and contextual, authentic engagement. 🔄 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻: How AI learns about students, through a continuous cycle of capturing learner data, modelling cognitive and affective states, adapting instruction, and evolving over time. 🛡️ 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗱𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻: How companions act with integrity, remaining transparent, accountable, inclusive, and secure. The paper features five case studies spanning global K-12 tutoring (𝗞𝗵𝗮𝗻𝗺𝗶𝗴𝗼), AI-assisted co-creation of educational content (𝗥𝗶𝗣𝗣𝗟𝗘), scaffolded programming support (𝗖𝗼𝗱𝗲𝗛𝗲𝗹𝗽), AI-assisted course discussion and formative feedback (𝗝𝗲𝗲𝗽𝘆𝗧𝗔), and institution-wide AI companion design for higher-order learning (𝗥𝗲𝗰𝗮𝘀𝘁 at UTS), each illustrating what a deliberately designed AI learning companion can look like in practice. 𝗧𝗵𝗲 𝗸𝗲𝘆 𝗶𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻: Designing AI for learning is not a minor prompt-engineering adjustment. It requires building systems that model learners, adapt to their needs over time, and are grounded in pedagogical principles, shifting from optimising task outputs to cultivating learners who are more reflective, more metacognitively aware, and better equipped to learn independently in an AI-rich world. 💬 Have you developed or used AI tools that prioritise learning over performance? We'd love to hear about them in the comments.

🤖 AI + Learning Differences: Designing a Future with No Boundaries 🌍 💡 A powerful new white paper from the Stanford Accelerator for Learning explores how Artificial Intelligence (#AI) can transform #education for learners with diverse abilities — turning inclusion into innovation. 🔍 Why it matters: ▪️AI can help redesign learning environments to serve every learner, but only if co-created with those who experience learning differences firsthand. ▪️This document offers a roadmap for a more inclusive, human-centered AI future — one that enhances both learning equity and skills for life and work. 💬 Key Themes & Insights: 🧩 Co-design & Collaboration: Inclusive innovation starts with people — learners, parents, educators, and technologists — designing together. Co-design ensures that AI tools reflect real experiences and reduce barriers, not reinforce them. 🎯 Learning for the edges: “Providing students what they need is not an edge — it’s just learning.” AI can help design flexible, personalized learning that values variability and fosters a sense of belonging and agency for all learners. 📘 Special Education & IEPs: AI-powered tools can simplify and personalize Individualized Education Plans (IEPs) — from real-time feedback to adaptive learning supports — freeing teachers to focus on human connection. 🧠 Early Identification & Mediation: AI can assist in early detection of learning differences and support tailored interventions, provided it is transparent, bias-aware, and always guided by human judgment. 💞 Social & Emotional Well-Being: Beyond academics, AI can nurture emotional intelligence, empathy, and positive relationships — essential for lifelong learning and well-being. 🦾 AI as Assistive Technology: From speech recognition to adaptive tutoring, AI can extend independence and agency for learners, redefining what “support” means. 👩🏫 AI in Teacher Development: Teachers need career-long learning to use AI ethically and effectively. AI can also personalize professional learning and reduce administrative burden. 💼 AI and the Workforce: Preparing all learners for an AI-shaped economy demands inclusive pathways to quality work, ensuring no one is left behind in the digital transition. 🌐 Interdependence & Life Satisfaction: The ultimate goal: AI that fosters autonomy, community, and well-being across a lifetime — learning without boundaries. 🧭 Call to Action Developers, educators, researchers, and policymakers must work together to ensure that AI systems are co-designed, equitable, and responsive to human diversity. #AIinEducation #InclusiveInnovation EfVET European Association of Institutes for Vocational Training (EVBB) European Vocational Training Association - EVTA EUproVET EURASHE eucen WorldSkills International OECD Education and Skills International Labour Organization Cedefop European Training Foundation EU Employment and Skills UNESCO-UNEVOC National Centre for Vocational Education Research (NCVER) CoP CoVEs

AI isn’t replacing instructional designers—it’s expanding what we’re capable of. Over the past few months, I’ve been hosting workshops to help real IDs to bring their AI projects to life. And these aren’t surface-level demos.... We dive into real use cases, engineer effective prompts, and sometimes even write JavaScript to power the experience. I just published a new video that showcases four of the most impressive AI-powered projects to come out of these workshops. In it, you'll see: 1. A Storyline roleplay that simulates group facilitation with six unique AI-powered personas 2. A custom-coded web object that teaches people to read bearing rate graphs (built without writing code) 3. A GPT designed to help teachers reframe their experience for ID interviews 4. A de-escalation scenario with an AI character and a coaching assistant that gives personalized feedback After each demo, the creator joins me to break down their process, lessons learned, and advice for others who want to start building with AI—even if they’re not developers. If you're curious about what AI makes possible in learning design, this video will give you a glimpse into the future—and the people already building it. You can check out the video with the link in the comments. And let me know which project stands out to you. 😄 #LinkedInWithDevlin #InstructionalDesign #Learning #LearningAndDevelopment #eLearning

The most misunderstood benefit of AI in education: Equity. Not automation. Not speed. Here’s how AI is quietly helping students from ALL backgrounds catch up (and even pull ahead): Most people think AI in education means cheating, robot teachers, or screen-addicted kids. But the reality is that AI's true power is in leveling the playing field for ALL students. I've spent 10+ years revolutionizing education with my schools. Over the last several years, we discovered how AI can eliminate educational inequality when implemented correctly. In Brownsville, Texas, 1/4 of the community lives below the poverty line. We started a school that serves SpaceX employees' kids and students from he local, under-resourced community. Split 50-50. Yet our learning outcomes are identical across both groups. Traditionally, zip codes determine educational destiny. But our AI-powered model breaks this pattern. Local students who joined us in the 31st percentile jumped to the 86th percentile in just one year. How is this possible? Because traditional schools use a one-size-fits-all approach. In a typical classroom, abilities range widely, from kindergarten to sophomore level. What textbook works for that range? AI creates a personalized learning path for each student. It's like giving each child their own private tutor, something previously only available to the wealthy. Our model proves that kids are more capable than what traditional schools allow. With AI adjusting to each child's unique aptitudes and needs, students learn 2x faster. But it's not just about academic results. We want to transform how children see themselves as learners. And AI delivers that better future. Where educational inequality has been entrenched for generations, AI creates unprecedented opportunity. Students who are often left behind can thrive when liberated from a system not designed for their success. ALL kids can learn at high levels with the right tools and approach The question isn't whether AI belongs in education. It's whether we're ready to use it for true equity, ensuring every child can reach their full potential. AI isn't replacing teachers. It's reshaping what's possible for our kids.

🚨 Breaking: Anthropic just redefined how AI fits into education. Claude AI, their conversational AI, is no longer just a smart assistant — it’s quickly becoming a core part of the modern learning experience. With their latest update, Anthropic has launched powerful new educational integrations that bring AI directly into students’ and educators’ daily workflows. 🎓 What’s new? Anthropic’s Claude now integrates with: ✅ Panopto – so students can instantly access and reference lecture transcripts during AI conversations. Imagine asking Claude, “What did the professor say about protein folding last week?” and getting an exact excerpt from your recorded lecture. ✅ Wiley – giving access to peer-reviewed academic content in real-time. Claude can now pull high-quality, trusted material into the learning process. ✅ Canvas LTI integration – Claude AI is now embedded right inside one of the most widely used learning management systems. Students and teachers can use AI in coursework seamlessly, without context-switching. 📌 This is much more than just convenience. This is about contextual, real-time learning support that helps students work smarter, not harder. Need help understanding a tough concept from your lecture? Claude can walk you through it with reference to actual course material. Writing a paper? It can help synthesize ideas from credible sources, without hallucinating or inventing data. ⁉️ And for educators? It means students are more empowered to take ownership of their learning journey — reducing the burden of repeated questions and increasing meaningful engagement. 💡 Why this matters: We’re witnessing a shift where AI isn’t replacing education—it’s enhancing it. With integrations like this, Claude becomes an extension of the classroom, a personalized tutor that’s always available, and a gateway to verified knowledge. The real value lies in Claude’s ability to maintain context, respect privacy, and offer accurate, conversational support. Anthropic’s constitutional AI approach gives it an edge when applied in high-integrity domains like education. 🔮 The bottom line: AI is no longer a side tool in education—it’s becoming part of the core stack. These integrations show us what a future-ready, AI-powered education system looks like. Flexible. Personalized. And deeply rooted in trusted content. We’re just scratching the surface of what’s possible when #GenAI meets academia. #ClaudeAI #Anthropic #AIinEducation #EdTech #CanvasLMS #Panopto #Wiley #StudentSuccess #GenerativeAI #FutureOfLearning #AcademicInnovation #ConstitutionalAI #AItools #EducationReimagined #LearningWithAI 🚀📘🤖

AI's Powers For All 1.  Harnessing AI's potential in education:  Seiji Isotani's research delves into the intersection of artificial intelligence and education, specifically focusing on how AI and behavioral science can synergize to enhance learning experiences. By understanding how students learn and tailoring educational technologies to their individual needs, Isotani aims to optimize the educational process.   2.  Addressing global educational disparities:  Isotani's work extends beyond theoretical research to practical initiatives aimed at addressing global educational disparities. He emphasizes leveraging AI to bridge the digital divide, ensuring that even students in underserved communities have access to quality educational resources. By developing AI technologies that can function effectively with existing infrastructure, Isotani aims to democratize access to education worldwide. 3.  AIED Unplugged:  One of Isotani's notable initiatives is AIED Unplugged, which utilizes AI software accessible via cell phones to assist teachers in evaluating student writing. This initiative has had a tangible impact, reaching hundreds of thousands of students in countries like Brazil, Mexico, Peru, and the Philippines. By providing teachers with AI-powered tools for assessment and feedback, AIED Unplugged contributes to improving students' writing skills and overall academic performance. 4.  Gamification and personalized learning:  Isotani integrates gamification elements into AI-driven educational tools to enhance student engagement and motivation. By incorporating game-like features such as rewards, incentives, and personalized learning pathways, Isotani seeks to make learning more enjoyable and effective. This approach not only fosters student motivation but also allows educators to tailor learning experiences to individual student needs, thereby maximizing learning outcomes. 5.  Balancing AI hype with reality:  While acknowledging the transformative potential of AI in education, Isotani also emphasizes the importance of approaching AI adoption with caution and responsibility. He warns against succumbing to the hype surrounding AI and advocates for a nuanced understanding of its capabilities and limitations. By promoting responsible AI integration and innovation, Isotani aims to ensure that AI serves as a tool for positive educational transformation rather than a source of disruption or inequality. More info A Case Study on AIED Unplugged Applied to Public Policy for Learning Recovery Post-pandemic in Brazil https://lnkd.in/eg5MyKsH Source https://lnkd.in/ecgmg5wV

Two recent studies, one from OpenAI's analysis of 2.5 billion daily ChatGPT messages and the other from Google's controlled trial of AI-augmented textbooks, provide converging evidence of a fundamental shift in how people learn. ChatGPT, with 700 million weekly users, sees 10% of all messages dedicated to tutoring, predominantly from users aged 18-25. Surprisingly, students primarily use AI to deepen understanding rather than complete tasks: 49% of interactions seek explanations and comprehension, not ready-made answers. This organic adoption shows students creating personalized learning experiences that traditional one-size-fits-all textbooks cannot provide. Google's Learn Your Way validates this approach experimentally. By personalizing textbook content to student interests and reading levels, explaining physics through basketball or economics through music, the system improved test scores by 13 percentage points. Both studies show AI transforms passive reading into active engagement through questions, multiple content representations, and immediate feedback. The gender gap in usage has closed, and adoption is accelerating in lower-income countries, though educated professionals still dominate work-related usage. The convergence is becoming more clear: millions of students aren't waiting for institutions to provide AI learning tools, they're already using GenAI as a personalized tutor. The data suggests GenAI works best as a learning companion that enhances understanding rather than replacing formal education. As we move forward, the question isn't whether AI will transform education, that transformation is already underway, driven by millions of students who have discovered that AI can provide something traditional educational materials cannot: personalized, patient, always-available support for learning. The question is how educational institutions, policymakers, and technology developers will respond to and shape this transformation to ensure it enhances rather than undermines human learning and development. https://lnkd.in/gpAxJrfF

🧠 AI will not replace your need to learn or even your ability to learn, but it will replace how you learn. What if you could learn almost anything faster, and remember it longer? For my generation, remember the countless hours running around the library finding sources? For the generation after me, remember when learning something new meant hours Googling and guessing what mattered? AI  changes that, completely. 💡 This week’s tip for GenAI beginners:  Use Generative AI for learning assistance, to simplify, summarize, and deepen your understanding of almost any topic. Here is how to begin: 📚 Simplify Complex Topics “Explain blockchain as if I were a high school student.” “Summarize this whitepaper in three key takeaways I can discuss in a meeting.” AI shines when you use it to decode complexity, not just to Google faster. 🔍 Deep Research Deep Research such as the ones integrated in ChatGPT, Anthropic Claude and Google Gemini, go beyond summarization. They search the web, filter credible information, and provide insights with citations, creating a trusted foundation for your learning. “Research the five leading use cases of AI in manufacturing, including examples and data from 2024.” “Compare three reports on renewable energy growth and summarize the key trends.” “Find the latest statistics on mental health in the workplace and cite credible sources.” 🧩 Active Learning and Review You no longer have to “Make Do” with whatever tools are provided, you can build your own personal learning assistant that caters to the way you learn best. “Create a quiz from this document to test my understanding.” “Turn this transcript into a set of flashcards for study.” “Generate a 10-question self-test based on this training manual.” 🎧 Multimodal Learning Use tools such as Google’s NotebookLM (SEE my post last month) to upload materials and generate: Audio overviews that sound like podcasts built from your notes. Mind maps that visualize relationships between ideas. Study guides and timelines to reinforce memory and structure. 📊 Why this matters Knowledge workers spend nearly 20% of their week searching for and gathering information, according to McKinsey & Company Software provider Valamis found that employees lose an average of 1.8 hours per day just searching for information. A study from Cornell University found that AI-assisted learning can reduce study time by 27% and improve comprehension and organization. When used well, GenAI turns static information into active understanding, helping you learn smarter, not harder. ✅ Takeaways GenAI is not just a research tool; it is a learning companion. The key is to move beyond answers, use AI to engage with and apply what you learn. 💬 Your turn What is something new you have wanted to learn but never found the time for? 👇 Share it below, and let us see how AI can help you master it faster. #AI #GenAI #Learning #Productivity