How Change and Learning Work in the Body

Curiosity used to be a mark of intelligence. When students stayed up nights, not for exams, but because something fascinated them so deeply that they could not rest until they understood it. When teachers were not content creators, and learning was not a mechanical exchange of information but a relationship of discovery. That world is now gone. Today, curiosity has been replaced by convenience. Instead of learning how to think, students are learning how to prompt. Instead of struggling through confusion, they are outsourcing clarity. AI has made access infinite, but attention scarce. It has given answers to those who never learned to ask questions properly. The problem is not that students use AI. The problem is that they use it without understanding what it takes away. When a machine begins to think for you, your ability to think for yourself slowly erodes. The joy of arriving at an idea after hours of wrestling with it is being replaced by a synthetic sense of accomplishment: a dopamine hit for typing a query and getting an instant answer. Even teachers have not escaped this collapse. Instead of mentoring minds, many have become managers of engagement. They chase views, not vision. They trade the dignity of a classroom for the vanity of a reel. The focus has shifted from depth to delivery, from substance to spectacle. In that trade-off, education has lost its soul. True learning demands discomfort. It requires slowness, patience, and a willingness to be wrong. But this generation is being trained to believe that efficiency is intelligence, and that speed equals superiority. AI has not made us smarter; it has only made our ignorance faster. We are raising a generation that knows how to “get” information but not how to “grasp” it. A generation that can mimic expertise without mastery. Unless we rebuild curiosity as a value - not as a habit, not as a hobby, but as a cultural foundation - we are heading towards an era where machines will not replace humans, but where humans will voluntarily reduce themselves to machines. Curiosity is not about knowing more. It is about wanting to know why and how. That, sadly, is the part AI cannot teach. #riosophy

Resilience isn’t about “toughing it out” — it’s about adaptability and creating opportunities to learn. Hold your students' hands and slowly walk them through what they struggle with. Relate to them, get down to their level and go at their pace. Ask them questions that they can understand and foster problem solving and critical thinking in them. In this day and age of AI and answers coming at a simple click or tap, critical thinking is more important than ever.

Workforce development, artificial intelligence, and student success are more interconnected than ever. As technology continues to reshape industries, preparing students with the skills they need to thrive in the future workforce is critical. By integrating AI into education, we can personalize learning, identify opportunities for growth, and support students in achieving their full potential. Investing in workforce development today ensures that tomorrow’s professionals are equipped not just with knowledge, but with adaptability, problem-solving skills, and resilience. Aligning student success initiatives with emerging industry trends is no longer optional, it’s essential for creating a workforce ready for the challenges and opportunities ahead. #WorkforceDevelopment #AI #StudentSuccess #EducationTechnology #FutureOfWork #CareerReadiness #HigherEducation #SkillsForSuccess #InnovationInEducation #LifelongLearning

“Your AI agent will reflect your institution back to you: its supports and strengths, but also its messiness and opacity. That’s a feature, not a bug.” - Anna Sharpe, Ph.D., Dean of Student Success, Berry College At Berry College, Anna Sharpe, Ph.D. and her team are setting a new standard with their AI One Stop, Sylas: a true and 24/7 extension of their team and campus culture. In their standout 2025 NACADA session, Anna and Lorianna Mapps, Ed.D., VP of Partner Success at CollegeVine, emphasized that adopting AI in student advising is no longer “Should we?” but “How do we?.” Students today expect immediate, intuitive support and many hesitate to ask questions in person for fear of judgment. With well-trained, purpose-built AI, colleges can create safe spaces where students seek answers freely and confidently.

A new study shows the type of feedback a chatbot gives affects learning and brain activity. Reflective feedback boosts problem-solving, while encouraging feedback improves memory.

If you work in education or learning design, read Brian Klaas’s “The Death of the Student Essay"  https://lnkd.in/eGRMTBfd. It offers a sharp view of how AI is reshaping not just assessment, but thought itself. His argument rings true. While universities debate the future of the essay, the learning industry imagines a dazzling future: that AI-driven efficiency will free us to focus on higher-order thinking. Efficiency dominates every discussion. We talk of faster design cycles, AI-assisted content and personalised learning at scale. The promise is always the same: let machines handle the “doing” so people can spend more time “thinking.” But what happens when the next generation of talent arrives in the workforce without that ability? Klaas argues that AI has made the student essay obsolete, and with it, the slow, demanding process of learning to think critically. The essay was never just an assessment tool. It was a cognitive training ground, forcing reflection, structure, argument, and self-correction. The Struggle was where the learning and development really happened. Now, AI can do all that for you. The result may be a future workforce fluent in style but thin in reasoning. Capable of polished outputs yet short on original insight. If that is true, the implications for education and corporate learning are serious. Perhaps our goal should not be to make learning faster, but to make thinking harder. #LearningDesign #Education #CorporateLearning #AIandLearning #CriticalThinking #FutureOfWork

💡 𝐎𝐧 𝐏𝐨𝐥𝐢𝐜𝐲 𝐃𝐢𝐬𝐭𝐢𝐥𝐥𝐚𝐭𝐢𝐨𝐧 𝐀 𝐒𝐦𝐚𝐫𝐭𝐞𝐫 𝐋𝐞𝐚𝐧𝐞𝐫 𝐏𝐚𝐭𝐡 𝐟𝐨𝐫 𝐋𝐋𝐌 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 It’s always a pleasure to read Thinking Machines Lab blog. Their recent post on 𝐎𝐧 𝐏𝐨𝐥𝐢𝐜𝐲 𝐃𝐢𝐬𝐭𝐢𝐥𝐥𝐚𝐭𝐢𝐨𝐧 caught my attention not just for its clarity but for what it signals about the future of efficient model alignment. Traditional 𝐝𝐢𝐬𝐭𝐢𝐥𝐥𝐚𝐭𝐢𝐨𝐧 teaches a smaller student model to mimic a larger teacher by imitating its responses. Effective but limited because the student only learns from the teacher’s data not from its own experience. 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 (𝐑𝐋𝐇𝐅) fixes that by letting the model learn from its own outputs but at a steep cost: sparse rewards, high instability, and huge compute budgets. 𝐎𝐧 𝐏𝐨𝐥𝐢𝐜𝐲 𝐃𝐢𝐬𝐭𝐢𝐥𝐥𝐚𝐭𝐢𝐨𝐧 strikes a powerful balance. Here’s how it works: 🔥 The 𝐬𝐭𝐮𝐝𝐞𝐧𝐭 𝐦𝐨𝐝𝐞𝐥 generates its own outputs (on policy) 🧠 The 𝐭𝐞𝐚𝐜𝐡𝐞𝐫 𝐦𝐨𝐝𝐞𝐥 evaluates each token with a dense per step reward signal often computed via a reverse KL loss ⚙️ The student learns from continuous fine grained feedback instead of waiting for a single good or bad reward at the end Why this matters ✅ Dense feedback means faster and more stable learning ✅ On policy sampling reduces distribution shift ✅ No human labels or reinforcement pipeline means far lower cost ✅ Continual adaptability helps integrate new knowledge without forgetting old ones Now think about applying this to 𝐡𝐞𝐚𝐥𝐭𝐡𝐭𝐞𝐜𝐡 Imagine a smaller clinical assistant model that learns safe diagnostic reasoning from a trusted medical foundation model. It generates its own patient notes receives dense feedback from the teacher on clarity empathy and accuracy and improves continuously without retraining from scratch. That’s the promise of On Policy Distillation smaller safer domain aware models that learn efficiently in the environments they’ll actually be used. But here’s the question I’ve been thinking about 👉 𝘐𝘧 𝘥𝘦𝘯𝘴𝘦 𝘵𝘦𝘢𝘤𝘩𝘦𝘳 𝘧𝘦𝘦𝘥𝘣𝘢𝘤𝘬 𝘤𝘢𝘯 𝘳𝘦𝘱𝘭𝘢𝘤𝘦 𝘩𝘶𝘮𝘢𝘯 𝘳𝘦𝘸𝘢𝘳𝘥 𝘴𝘪𝘨𝘯𝘢𝘭𝘴, 𝘤𝘰𝘶𝘭𝘥 𝘵𝘩𝘪𝘴 𝘣𝘦𝘤𝘰𝘮𝘦 𝘵𝘩𝘦 𝘯𝘦𝘸 𝘥𝘦𝘧𝘢𝘶𝘭𝘵 𝘱𝘢𝘳𝘢𝘥𝘪𝘨𝘮 𝘧𝘰𝘳 𝘱𝘰𝘴𝘵 𝘵𝘳𝘢𝘪𝘯𝘪𝘯𝘨 𝘢𝘭𝘪𝘨𝘯𝘮𝘦𝘯𝘵 𝘯𝘰𝘵 𝘫𝘶𝘴𝘵 𝘪𝘯 𝘓𝘓𝘔𝘴 𝘣𝘶𝘵 𝘢𝘤𝘳𝘰𝘴𝘴 𝘢𝘯𝘺 𝘳𝘦𝘢𝘴𝘰𝘯𝘪𝘯𝘨 𝘴𝘺𝘴𝘵𝘦𝘮? Would love to hear your thoughts. #AI #LLMs #MachineLearning #OnPolicyDistillation #RLHF #Distillation #HealthTech #ThinkingMachines #AIEthics

🤖🎓 AI is Transforming Higher Education — But the Real Revolution Is in How Students Think. In our discussion with Wael Kechli, we explore how Prompt Engineering is becoming a defining skill of the modern learner. It’s no longer enough to know the right answers — today’s students must learn how to ask the right questions. 💬 AI tools like ChatGPT are enabling a new kind of classroom — one driven by creativity, curiosity, and collaboration. And universities that embrace this change aren’t just integrating technology… they’re reimagining the entire learning process. 🌍💡 🎓 The result? Students who are adaptive thinkers, ethical innovators, and leaders in an AI-powered world. 🎥 Watch the highlight clip and catch the full conversation: 🔗 “Preparing Students for an AI-Powered Future with Higher Ed” 👉 https://lnkd.in/ghs9An2g #AIinEducation #PromptEngineering #HigherEducation #Innovation #ArtificialIntelligence #DigitalTransformation #AI #FutureOfLearning #Leadership #EdTech #Education

💬 “Who knows what technology will emerge in the next five years, let alone 20. Yet the education we provide our children now is supposed to last for decades. We cannot train them for jobs that do not even exist yet, but we can provide them with the minds and tools they’ll need to adapt to our ever-changing set of circumstances.” -Former NC Governor Jim Hunt That vision holds true for AI as well. We are all lifelong learners now. We are not just preparing our children to adapt to new technologies — we must be preparing ourselves. AI is clearly not waiting on us! 🎓 I’m honored to share that I’ve been appointed as an Adjunct Professor of Practice at Wake Forest University, teaching in the School of Professional Studies – Master’s in AI Strategy and Innovation. 🤖 My initial focus will be on classes in emerging technologies including generative AI, LLMs, benchmarking, and integration into business processes. 🧠 Working with students — from those just starting out to those mid-career — provides invaluable insight into how people absorb, apply, and extend AI. Understanding how people learn AI helps us design better, more human-centered systems and strengthen the foundation of human-machine teaming. And honestly, it makes AI a lot less scary! 🏛️ Growing up in North Carolina, I was always close to Wake Forest University Friends went there, friends teach there now, and I’m proud to join the Demon Deacon community. 💡 Teaching is one of the best ways to keep learning. It reminds us that building and learning are part of the same process — both driven by curiosity, accountability, and imagination. Go DEACS! #WakeForest #AI #AIInnovation #HumanMachineTeaming #AIEducation #Teaching #NorthCarolina #DemonDeacons #GenerativeAI #LLMs #AIRisk

Can artificial intelligence replace teachers? Today, many people feel anxious — will AI take their jobs? Let’s talk a bit about teachers. Teachers possess critical thinking, sensitivity, intuition, empathy, and emotional intelligence — and that’s what makes them truly irreplaceable. Unlike them, artificial intelligence is built on algorithms and therefore provides rather mechanical responses. It can’t feel the student, sense their fatigue, anxiety, or emotional state. Education needs more than just tools that deliver knowledge in a cold, mechanical way. It needs educators who act as mentors and guides, offering emotional support. This support directly impacts students’ academic performance, engagement, and motivation. Moreover, relying too heavily on AI limits students’ interaction with one another, hindering the development of essential emotional and social skills like communication, teamwork, and active listening — abilities that can only grow through real human connection. That’s why humans still surpass AI, especially in emotional and social aspects. I’m not against using AI as a tool, but it shouldn’t think for people or do all the work for them. In fact, as AI becomes more integrated into education, teachers with strong critical thinking, empathy, and emotional intelligence are becoming more valuable than ever. #AIineducation #AIvsHuman