Technology In Education

If students don’t learn how to think with AI, they’ll let AI think for them. Last Thursday at Shanghai American School, I got to "beam in" to give a keynote presentation on one of the most urgent conversations in education today: How do we integrate AI without losing what makes learning human? Here are the key takeaways from our time together: • Generative AI can amplify learning—or weaken it. Studies show that when students engage critically with AI, they learn more. But when they rely on it to do the work for them, learning declines. The key? Teach students to think with AI, not just use it. • Confidence in AI can lower critical thinking. Research suggests that when people trust AI too much, they question it less. The best educators will teach students how to balance trust and skepticism when using AI tools. • Ethical AI use starts with values. We discussed how every school needs guiding principles for AI integration—beyond just policies. What should we protect? What should we enhance? These questions shape AI’s role in education. We concluded with "Three Ts" for responsible AI use: 1. Talk – Normalize generative AI discussions with students and teachers. I shared my "Generative AI Guidelines Canvas" to support conversations. https://lnkd.in/gyjTkK7d 2. Teach – Build generative AI literacy into the curriculum. I shared Cora Yang and Dalton Flanagan's C.R.E.A.T.E. framework for teaching students to prompt. https://lnkd.in/g-KYt4Uy 3. Try – Teachers should experiment with generative AI tools in meaningful, ethical ways. I shared Darren Coxon's Hattie Bot to let teachers experiment with building lessons that have high effect size. https://lnkd.in/g44gZzA3 This conversation isn’t over—it’s just beginning. Critical thinking isn't optional if machines do the easy thinking for us. Much gratitude to Alan Preis & Scott Williams for crafting such a great experience. Photo Credit Alex McMillan 🙏 P.S. I asked everyone at Shanghai American School: What values should guide our approach to AI in education? What's your answer? #generativeAI #guidelines #teachers #ethics

🎓 Imagine if every student had a genius tutor, always available, infinitely patient, and deeply personalized. That future isn't 10 years away. It's already being prototyped. It's called Project Astra. In a recent demo, a student asks for help on a chemistry problem—optical isomerism, a tricky topic. Astra not only answers but: → Takes the conversation to a virtual blackboard → Explains the concept visually → Detects the student's mistakes in real-time → Guides them step-by-step until understanding clicks Beyond Q&A, this is learning with understanding. This is what education becomes when AI evolves from search engine… to teacher. 📚 Astra does what human tutors struggle to scale: — Instant feedback — Visual reasoning — Infinite patience — Memory of your past questions — And yes… encouragement too. It’s not replacing teachers. It’s amplifying them. It’s not giving answers. It’s building thinkers. Project Astra is a glimpse into the agentic future of education—where learning is active, adaptive, and alive. Not locked in textbooks. Not limited by time or location. The classroom is becoming conversational. The curriculum is becoming intelligent. The student is becoming the center. And the question we should all ask: How do we prepare our children (and ourselves) to thrive in a world where anyone can learn anything, anytime, with an AI by their side? Let’s not just teach with AI. Let’s teach for a world changed by AI. — 🔍 Curious to see what this looks like? Search Project Astra by Google DeepMind 💬 What would your dream AI tutor teach you? #AI #Education #ProjectAstra #FutureOfLearning #EdTech #AgenticAI #Gemini #GoogleDeepMind #LearningReimagined #HumanAI

Some thoughts on how we integrate AI into education: We first need to start by recognizing which skills are becoming more valuable and designing new ways to teach them. We all remember the effort it takes to write a paper—revising, structuring arguments, and refining our points. With AI, everyone will have a writing co-pilot to handle the mechanics, making the process more efficient. So, what if we redirected that effort into helping students develop higher-order skills like critical thinking, prompt design, and iterative analysis? A thought experiment: Imagine an assignment where students submit not just their essays but also the prompts they used to get AI-generated critiques. Their task wouldn’t be just to write and submit—it would be to argue, analyze, refine, and iterate. In less time than it takes to write a traditional paper, students could engage in deeper intellectual exercises—interrogating their own arguments, considering counterpoints, and strengthening their reasoning. For teachers, AI can streamline grading while amplifying feedback—providing broad insights that help shape targeted, meaningful commentary. This means students receive richer, more personalized guidance, making learning more interactive and impactful.

How best can we support teachers in their adoption of Generative AI? This is a question I'll try to answer at tomorrow's Stanford's AI + Education Summit. Here's my answer based on the work we have done training teachers on GenAI over the past 6 months.   First, the reality is that even a year after the launch of ChatGPT we are still very much in the early stages of adoption.   • Per a recent EdWeek survey, 2/3rds of teachers have NEVER used AI in their classroom and only 2% have used it “a lot.”   Second, the current perceptions of GenAI run the gamut.     • Fear and uncertainty are common with nearly 50% of teachers saying they’re uncomfortable with GenAI.     • Cheating (72%) and the potential negative impact to learning (60%) are prevalent fears     • But there is also enthusiasm about GenAI’s potential - half said they were “excited or optimistic” about the potential of these tools.    We see all of this in every workshop we have run regardless of audience. By the end of our sessions, we often see that the same educators who are concerned about AI’s downsides are the same ones who light up when they see the tools in action.   So what’s the best path forward for responsible adoption?   At AI for Education Education, our focus is on building capacity and finding value, not becoming experts.   Here are our 5 top strategies:w   1. Comprehensive AI Literacy Training:    Educating the entire school community is vital for understanding AI's wide-reaching impacts and potential, fostering future readiness, enhancing learning, and enabling the informed decision-making that will help guide the future of AI.   2. Job-Embedded GenAI Applications    Focus on integrating AI directly into educators' daily tasks and responsibilities, showcasing practical uses of AI in educational settings that drive productivity and quality of instruction.   3. Strong Guidance on Responsible Use   We stress the need for clear guidelines on the appropriate use of GenAI by students and teachers, ensuring that AI tools are used in a manner that augments a user's ability and is deployed in an ethical manner is key.   4. Safe/Reliable GenAI Tools for Students   We must develop and implement student-focused GenAI tools that are both safe and reliable, fostering a secure learning environment.   5. Dedicated Resources for Innovation    We advocate for dedicated resources to support experimentation and innovation, encouraging continuous development and improvement of GenAI tools and methods in education.   Of course, none of this can be done without a strong change management strategy and dedicated budgets - but with these keys we believe it's possible to support teachers adoption of GenAI. For the link to the study: https://lnkd.in/eHz6883G #aiforeducation #aieducation #teachingwithAI #GenAI #responsibleAI

Now that I have had a chance to reflect on ASU+GSV Summit this year, and naturally AI dominated the conversation and showcases, I can’t help feeling that edtech is going in the wrong direction. Most new products focus on automating or replacing teaching itself. These bots often function merely as advanced information retrieval – a conversational alternative to searching online. But is easier information access the primary barrier to better learning outcomes? Or are real challenges student motivation, connection with teachers and classmates, or lack of personalization due to too high student-teacher ratios? AI's true potential lies not in content or Q&A, but in augmenting humans and fixing systemic issues. Focus areas: 1. Comprehensive Learner Profiles: Effective teaching is personalized. Most edtech fails to track student strengths, weaknesses, and preferences persistently from their own interactions, let alone across systems; go from one grade to the next and all the history is lost. Unifying millions of data points into a dynamic learner profile, informing teaching systems, is key to personalization and moving towards one-student-one-teacher. 2. Process Automation for Educators: Teachers spend ~46% of time teaching. AI should automate administrative, non-teaching tasks consuming the rest. Freeing educators for teaching and mentoring is more impactful than automating pedagogy. 3. Empowering the Learning Ecosystem: Especially important for young learners - AI should empower parents to be educators. Person story - my 5-year old needed help with “54-19” without using a number line…and I couldn’t come up with an approach she could use. ChatGPT, Gemini, and Claude all failed to produce anything better other than giving her 54 blocks to subtract 19. Googling I found a YouTube video that had great suggestions, and it also let me create a lot better prompts that eventually I could help my daughter. But most parents wouldn’t think to do this. This is where a better purpose built model would work great. I foresee several developers in the next few years: 1. Most standalone LLM wrappers will fade as districts standardize on integrated platforms from major providers. 2. Schools implementing comprehensive learner profiles (when they arise) will see most significant outcome improvements. 3. The gap between high- and underperforming schools will widen. Under-resourced schools will 'outsource' pedagogy to chatbots. Those chatbots will fail, get replaced with the next set. The next set will eventually fail, get replaced, cue “rinse and repeat”. But it's not all bleak (more in comments)

Many teachers are skeptical about the utility of AI... Here the #UK Department for Education documented Use Cases for #GenAI in #Education - #User #Research Report The report examines the collaboration between educational institutions and the UK Department for Education to assess the use of GenAI in automating routine educational tasks. Several innovative use cases for generative AI (GenAI) in education that were explored during the hackathons and proof-of-concept (PoC) development. a) #LessonPlan or activity adaptor: A tool that can adapt existing lesson plans and tailor lesson activities to the specific context and needs of individual classes or students. b) #Feedback and revision activity generator: The PoC tool developed in this project focused on reviewing student work, providing personalized feedback, and generating tailored revision activities based on the individual student's errors and areas for improvement. c) #QuestionGenerator: A tool that can automatically generate graded, lesson plan-aligned questions based on information from sources such as lesson plans, objectives, and curriculum materials. d) #Disabilities #SupportTool: A tool designed to assist teachers in adapting lesson content to meet the specific needs of students with Special Educational Needs and Disabilities (SEND). e) #Parent and carer communications tool: A tool that can generate communications with parents and carers, such as school newsletters or emails about upcoming events. f) #PolicyGenerator: A tool that can support the generation of school policies based on submitted school characteristics, existing policy documents, and national legislation or guidance. Three Challenges Identified: - ⚠️Model capabilities and limitations: While GenAI models showed potential in certain tasks like generating lesson plans or activities, there were significant limitations in more complex tasks, such as accurately marking student work or generating comprehensive feedback. - 🚨User trust and acceptance: Many teachers expressed concerns about trusting GenAI tools for tasks like providing feedback, and some were worried about becoming overly reliant on these tools. - ⏰Need for training and guidance: Teachers reported a need for time, training, funding, and expert support to increase their knowledge and skills in using GenAI tools in their practice, as well as guidance on how to use AI safely and effectively. Five aspects to improve: i) #DataPrivacy and safety ii) #Adoption #Reluctance iii) #Lack of #Personalization iv) #Accuracy of #AI v) #Implementation #Barriers via Martin Ebers https://lnkd.in/ekbHKxyS Source: Faculty AI, National Institute of Teaching, ImpactEd Group, & Department for Education. (2024). Use Cases for Generative AI in Education: User Research Report. UK Government

Transforming Engineering Education Through Immersive Technology & Sustainability We learn so much from the voice of students and future engineers. I recently had an inspiring conversation with Suavi Yildirim, whose team won the global Siemens Digital Industries Software-Sony Immersive Design Challenge. Our exchange revealed fascinating insights about the future of engineering education. (press release: https://lnkd.in/gbVJH4gX) We had an impressive response to the challenge. Students showed us how immersive design tools can broaden access to engineering. Through VR/XR technology, complex engineering concepts become more intuitive, breaking down learning barriers. This was perfectly demonstrated by the FAU Erlangen-Nürnberg Team NextCycle’s winning project, Battery Twin XR, which tackled EV battery lifecycle optimization. The team's ability to rapidly prototype and iterate in a virtual environment not only accelerated development but also led to better safety considerations and cost efficiencies. Suavi noted: “I think the immersive design tools have huge potential to democratize sustainable design education because they're very intuitive. So even students without CAD or VR experience can start exploring and understanding systems right away. This hands-on visual approach makes learning more engaging and accessible, especially in places where traditional tools or training might not be so common, so available. So, it's a great way to build confidence, creativity and a real understanding of sustainable design.” The success story here goes beyond the technology itself. It's about the power of cross-disciplinary collaboration - bringing together mechanical engineering, data analytics and software expertise. With guidance from industry mentors, the team learned to navigate real-world constraints while maintaining their innovative edge. This was a great example of blending academic theory with practical application. What's becoming increasingly clear is that the future of engineering education requires a delicate balance. While traditional degrees remain important, the rise of microcredentials and experiential learning are reshaping how we develop engineering talent. Industry-academia partnerships are no longer optional - they're essential for ensuring relevance in a rapidly evolving technological landscape. The key lesson? Tomorrow's engineering leaders need both technical excellence and a sustainability mindset, supported by cutting-edge tools and collaborative learning environments. It's not just about what we teach, but how we teach it. Listen now and let me know your thoughts: https://lnkd.in/gZbqcVJV.

They were hemorrhaging money on digital tools their managers refused to use. The situation: A retail giant in the diamond industry with post-COVID digital sales tools sitting unused. Store managers resisting change. Market volatility crushing performance. Here's what every other company does: More training on features. Explaining benefits harder. Pushing adoption metrics. Here's what my client did instead: They ignored the technology completely. Instead, they trained 200+ managers on something nobody else was teaching; how to fall in love with change itself. For 8 months, we didn't focus on the digital tools once. We taught them Change Enthusiasm®, how to see disruption as opportunity, resistance as data, and overwhelm as information. We certified managers in emotional processing, not technical skills. The results were staggering: → 30% increase in digital adoption (without a single tech training session) →  2X ROI boost for those who embraced the mindset →  25% sales uplift in stores with certified managers →  96% of participants improved business outcomes Here's the breakthrough insight: People don't resist technology. They resist change. Fix the relationship with change, and adoption becomes automatic. While competitors were fighting symptoms, this company cured the disease. The secret wasn't better technology training, it was better humans. When managers learned to thrive through change, they stopped seeing digital tools as threats and started seeing them as allies. Most companies are solving the wrong problem. They're trying to make people adopt technology. We help people embrace transformation. The results speak for themselves. What would happen if you stopped training on tools and started training on change? ♻️ Share if you believe the future belongs to change-ready organizations 🔔 Follow for insights on making transformation inevitable, not optional

The schools that lead with AI aren’t just trying tools. They’re building teams and cultures where AI works with people, instead of replacing them. That’s not just a mindset shift. It’s a strategic advantage. Here’s how some of the boldest school systems we're working with are setting the standard: ➡️ Desert Sands USD created the first AI guidance framework focused on human decision-making, shifting AI from a compliance concern to a powerful tool for human agency, balancing innovation and integrity. ➡️ Santa Ana Unified launched the Innovation Catalyst Collective, a cross-functional team ensuring AI enhances every aspect of the organization, from classrooms to operations. ➡️ Orange County Department of Education appointed two dedicated AI leaders and hosts monthly strategy sessions where district leaders collaborate, align, and co-design AI’s role across the region. ➡️ San Gabriel Valley USD launched a human-centered leadership cohort bringing teams together to work on passion projects that can be accelerated using AI to design new ways of working and learning. Different approaches. One common theme: ✅ They started with clarity: avoiding the hype and panic to focus on real, strategic action. ✅ They built with empathy: listening deeply to the needs of students, teachers, administrators, and community members. ✅ They prioritized agency: ensuring AI amplifies human judgment rather than replacing it. This is the real roadmap cycle to AI integration: Explore → Navigate → Strategize → Repeat. We call this creating your AI Power Circle, a six-month hybrid program designed to help school leaders build a future-ready strategy that’s grounded in people, purpose, and trust. Let’s design a future where AI works for you, helping your organization thrive in ways you never imagined. And this week I'm taking you behind the scenes into a workshop over on Substack. Tag a fellow school leader who’s ready to explore what’s possible! #AIinEducation #Leadership #FutureofLearning #AILiteracy #AGI #innovation #management #humanresources

Today, I witnessed something extraordinary in my classroom that challenged everything we think we know about AI in education. Instead of handing students a rigid playbook of dos and don'ts with AI, I decided to flip the script entirely. Since summer, I've watched the endless parade of methodological frameworks and usage guidelines sweep through education. Each promising to be the "right way" to integrate AI into learning. But today, we tried something radically different. I simply asked my students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration. The results? Astonishing. Students began mapping out research directions I'd never considered. They created dialogue spaces with AI that looked more like intellectual partnerships than simple query-response patterns. Most importantly, they documented their journey, creating a meta-learning archive of their process. What struck me most was this: When we stopped fixating on the tangible "products" of AI interaction and instead centered on the mental maps being developed, something magical happened. Some might say this approach is too unstructured, too risky. But consider what we're gaining: 1. Metacognitive development: Students are thinking deeply about their own learning process 2. Agency and ownership: They're designing their own educational pathways 3. Critical navigation skills: Learning to chart courses through AI-enhanced knowledge spaces 4. Creative confidence: Freedom to experiment without fear of "wrong" approaches 5. Future-ready adaptability: Building skills to work with evolving AI systems We're not just teaching students to use AI – we're empowering them to design their own learning ecosystems. The focus isn't on what appears on the screen, but on the neural pathways being forged, the cognitive frameworks being built. Watching these students navigate this space, I'm reminded that the future of education isn't about controlling AI use – it's about nurturing the wisdom to use it well. We need to trust our students' capacity to be architects of their own learning journeys. The real breakthrough happens when we stop seeing AI as space to be contained and start seeing it as a landscape to be explored. Our role as educators isn't to build fences, but to help students develop their own compasses. #AIEducation #FutureOfLearning #EducationalInnovation #StudentAgency #EdTech #CognitiveDesign #GenerativeThinking Amanda Bickerstaff Stefan Bauschard Dr. Sabba Quidwai Mike Kentz David Gregg David H. Doan Winkel Jason Gulya Dr. Lance Cummings. Alfonso Mendoza Jr., M.Ed.