Education

🥦Spain is leading the way on healthy sustainable school food 🇪🇸 In 2022 Spain updated its dietary guidelines to be more in line with the latest science on healthy sustainable diets (EAT-Lancet Planetary Health Diet). Now they are pioneering implementation -- having just passed a new royal decree on school food that brings what is served in line with NDG recommendations. The aim of this decree is for all children, regardless of family income level, to have access to healthy, nutritious meals at school. 🌟Highlights 🥩Meat to be served maximum three times a week. Red meat maximum once a week, processed meats maximum twice a month 🍇Focus on local, seasonal food -- 45% fruit and veg served must be in season 🫘Ramping up legumes -- to be served 1-2 times a week minimum in a variety of ways including as primary protein source in a main, or as part of a starter or side dish. Only 14% of schools currently serve legumes once a week 🚫Limits on processed foods -- pre-prepared options like pizzas, empanadillas, and croquetas can only be served once a month, and sugar-sweetened beverages, energy drinks and processed snacks will be banned from vending machines and school cafes 🍆Fully plant-based menus available for children who want them ⏰The new decree comes into effect next term, in all 17.000 Spanish schools (primary and secondary, public and private) This is an amazing step forwards, and I'm excited to see healthy sustainable food in Spanish school canteens. To ensure the policy vision becomes a reality on the 'school floor', compliance monitoring and enforcement will be key, as well as securing catering suppliers who are able to rapidly meet these new needs. Photo credit: Manu Garcia, La voz del sur. #foodpolicy #schoolfood #healthydiets #sustainablediets #publichealth #spain

Let’s talk about hidden disabilities—ADHD, dyslexia, anxiety, and others that don’t meet the eye. Too often, these students are left to struggle because their needs aren’t immediately visible. But here’s the thing: when we ignore those needs, it’s no different from denying someone in a wheelchair access to a ramp. Think about it. Would you expect someone to climb stairs without the tools they need? Of course not. Yet we often expect students with hidden disabilities to navigate education without the accommodations that would level the playing field. It’s not fair, and it’s not right. Accommodations like extra time, clear instructions, or a quiet space aren’t “special treatment.” They’re the difference between drowning and swimming. They’re the tools these students need to show us their potential, not their struggles. I’ve seen the power of a single adjustment. They’re what happens when we meet students where they are. What if we reimagined education as a place where every student feels valued and equipped to succeed? What if we stopped seeing accommodations as “extras” and started recognizing them as essential? Here’s a question for you: Have you seen examples of simple accommodations making a big impact? Or do you think schools are doing enough to support students with hidden disabilities? Let’s share, reflect, and push for better together. Image Courtesy: No Nonsense Neurodivergent #Disability #Accessibility #SDGs #Equity #HumanRights #WeAreBillionStrong ID: Allowing a student with a hidden disability (ADHD, Anxiety, Dyslexia) to struggle academically or socially when all that is needed for success are appropriate accommodations and explicit instruction, is no different than failing to provide a ramp for a person in a wheelchair.

I have a DEI secret… And it’s a big one. Ready? The accommodations I make for my neurodivergent team members… Also benefit my neurotypical team members. Ground breaking, right? 😏 I hear a lot about companies pushing back on accommodations, but I thought I’d show you just a few of the simple things we do here. I’ll use myself as the example, and let you see how it helps everyone. 👉 I like to sit on my legs and fidget in my chair. ✨ So we’ve got comfy chairs, wider than your standard office ones, for everyone. 👉 I regularly forget my breakfast or lunch. ✨ So we keep a fully stocked drinks fridge and snack cupboard. Open to everyone. 👉 Sometimes I find the main office overwhelming when I’m trying to focus. ✨ So we created two quiet workspaces in different rooms. Everyone can use them when it all gets a bit much. 👉 I used to get anxious about calling in sick and having to justify it to my old manager. ✨ Now? Just send a text. No explanations needed. If you say you’re ill, that’s enough. Applies to everyone. 👉 I had a habit of staying too late, sometimes working 3 or 4 hours longer than I should. ✨ So we finish at 4pm. And we mean it. Everyone is made to down tools and heads off. No late-night badge of honour here. I could go on, but you get the idea. There’s really no excuse not to make accommodations for your ND teammates. Because when you do… It makes things better for everyone.

Continuing from last week’s post on the rise of the Voice Stack, there’s an area that today’s voice-based systems often struggle with: Voice Activity Detection (VAD) and the turn-taking paradigm of communication. When communicating with a text-based chatbot, the turns are clear: You write something, then the bot does, then you do, and so on. The success of text-based chatbots with clear turn-taking has influenced the design of voice-based bots, most of which also use the turn-taking paradigm. A key part of building such a system is a VAD component to detect when the user is talking. This allows our software to take the parts of the audio stream in which the user is saying something and pass that to the model for the user’s turn. It also supports interruption in a limited way, whereby if a user insistently interrupts the AI system while it is talking, eventually the VAD system will realize the user is talking, shut off the AI’s output, and let the user take a turn. This works reasonably well in quiet environments. However, VAD systems today struggle with noisy environments, particularly when the background noise is from other human speech. For example, if you are in a noisy cafe speaking with a voice chatbot, VAD — which is usually trained to detect human speech — tends to be inaccurate at figuring out when you, or someone else, is talking. (In comparison, it works much better if you are in a noisy vehicle, since the background noise is more clearly not human speech.) It might think you are interrupting when it was merely someone in the background speaking, or fail to recognize that you’ve stopped talking. This is why today’s speech applications often struggle in noisy environments. Intriguingly, last year, Kyutai Labs published Moshi, a model that had many technical innovations. An important one was enabling persistent bi-direction audio streams from the user to Moshi and from Moshi to the user. If you and I were speaking in person or on the phone, we would constantly be streaming audio to each other (through the air or the phone system), and we’d use social cues to know when to listen and how to politely interrupt if one of us felt the need. Thus, the streams would not need to explicitly model turn-taking. Moshi works like this. It’s listening all the time, and it’s up to the model to decide when to stay silent and when to talk. This means an explicit VAD step is no longer necessary. Just as the architecture of text-only transformers has gone through many evolutions, voice models are going through a lot of architecture explorations. Given the importance of foundation models with voice-in and voice-out capabilities, many large companies right now are investing in developing better voice models. I’m confident we’ll see many more good voice models released this year. [Reached length limit; full text: https://lnkd.in/g9wGsPb2 ]

Major update on our work: In the last few years, a flood of new research has altered the landscape of the debate around kids, smartphones, and social media. 1️⃣ First, there is now a lot more work revealing a wide range of direct harms caused by social media that extends beyond mental health (e.g., cyberbullying, sextortion, and exposure to algorithmically amplified content promoting suicide, eating-disorders, and self-harm). These direct harms are not correlations; they are harms reported by millions of young people each year. 2️⃣ Second, recent research — including experiments conducted by Meta itself — provides increasingly strong causal evidence linking heavy social media use to depression, anxiety, and other internalizing disorders. (We refer to these as indirect harms because they appear over time rather than right away). Together, these findings allow us to answer the product safety question clearly: 📣 No, social media is not safe for children and adolescents. The evidence is abundant, varied, and damning. We have gathered it and organized it in two related projects which we invite you to read, in this post: https://lnkd.in/eAvfH3aQ

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

I believe that AI is evolving education into something more powerful. It’s reshaping the entire learning experience. Teachers are becoming personalized learning architects - designing AI-driven curricula that adapt to each student's pace and strengths. Administrators are evolving into data-driven leaders who use AI insights to predict student needs and optimize resources. Curriculum specialists are shifting toward adaptive content design while AI handles routine delivery. But the bigger story? The entirely new roles that will emerge in education: - AI Curriculum Architects design learning pathways that adapt in real-time - Learning Analytics Specialists analyze patterns across thousands of students to identify what actually works - Digital Instruction Coaches help teachers integrate AI without losing the human connection - AI Ethics Coordinators ensure algorithms don't disadvantage any student groups In this newsletter, I break down the roles emerging in education, identify the skills that matter most, and share how education leaders can position their teams for this shift. Education is entering its most exciting chapter yet - one where learning becomes deeply personal, data-driven, and accessible at scale.  What AI roles in Education are you most excited about? #Education #AI #FutureOfWork

Four roles. Seven years. Still there. The real question is why. Manjari Singhal, Chief Growth and Business Officer at Cleartrip, gives a direct answer: autonomy. The freedom to experiment, pivot, and try something entirely new within the same organisation. She is clear that it was the culture, specifically the accessibility and psychological safety to learn through doing, that kept her engaged across such a long and varied tenure. This challenges the assumption most companies carry into retention conversations. About 65% of professionals in India are actively exploring new roles. Compensation is typically treated as the primary retention lever. But Singhal's story complicates that directly. She acknowledges that better-paying opportunities existed. The deciding factor was something a salary band can rarely capture: the freedom to reinvent a career from within, repeatedly, without starting over elsewhere. When she stepped into a larger, more complex role at Cleartrip, the transition came with a steep learning curve. What made it manageable was a culture where making mistakes is part of the process, where leadership is genuinely accessible, and where the expectation of arriving fully formed is replaced by the expectation of learning fast. That shift in expectation changes everything about how a career transition feels. Rather than performing competence from day one, employees are encouraged to demonstrate curiosity and own the outcome. That is a fundamentally different environment to build a career inside, and it produces a fundamentally different kind of commitment. For organisations trying to understand why retention programmes keep underdelivering, Singhal's story offers a clearer diagnosis. Freedom, ownership, and genuine support for growth are the retention levers that matter most. They are also the hardest to build. Flipkart has been building them, quietly and deliberately, for years. #Flipkart #TalentRetention #CareerOwnership #PsychologicalSafety #Leadership https://lnkd.in/dph9-8SV

Ten years of NIRF data as analysed by KPMG India now offers a rare longitudinal view of how Indian higher educational institutions are performing. Keeping aside the integrity issues, this is indeed a positive trend for higher education. The next ten years can be transformative, if the government is willing to make some bold reforms in higher education. ▪️ Participation in NIRF grew from 2,426 institutions in 2016 to 7,692 in 2025. The college category alone expanded from 803 to 4,030 institutions. Law and medical categories saw triple-digit growth. ▪️ PhD-qualified faculty in engineering institutions increased from 28 percent in 2017 to 48 percent in 2025. Top-ranked institutions now report over 73 percent PhD faculty across most categories. Management institutes exceed 90 percent. ▪️ PhD student enrolments in universities rose from 97,947 in 2019 to 118,556 in 2025. Completions increased from 16,403 to 24,481 in the same period. Institutions ranked 76 to 100 showed the fastest growth in enrolments, while top-ranked institutions led in completions. ▪️ Research publications increased by 150 percent in engineering and universities. Pharmacy and management categories recorded a 300 percent rise. India’s share of global publications moved from 3.5 percent in 2017 to 5.2 percent in 2024. ▪️ Patent filings by educational institutions tripled between 2022 and 2024. India is now among the top six countries globally in patent activity. ▪️ Median salaries of graduating students across institutions nearly doubled over five years. This reflects improved graduate outcomes and stronger employer confidence. ▪️ In the QS World University Rankings 2026, India is the fourth most represented country with 54 institutions. This is a fivefold increase since 2015.

My first 5 grant applications were rejected. Every single one. Here's how I went from £10k to £10m in research grant funding: I remember opening that fifth rejection email and thinking maybe my research just wasn't good enough. Maybe I wasn't cut out for this. Then a panel reviewer told me something that changed everything. She said: "I stopped reading on page 2." Not because the science was weak. Because the way I presented it was. I had buried the real-world impact on page 3. I led with the literature gap instead of the problem. My methodology was sound but my narrative was invisible. I was writing for academics. I should have been writing for funders. So I rebuilt my entire proposal structure around three principles. I now call it the 3P Proposal Structure. P1: Problem Framing. Lead with the real-world problem and its cost. Not the gap in the literature. Funders don't fund gaps. They fund solutions. "This problem costs the NHS £2.3 billion annually" hits harder than "this area remains under-explored." P2: Path Innovation. Show what you will do differently. Not just what you will study. Every applicant studies something. Very few explain why their approach is the one that will actually work. P3: Projected Impact. Connect your outcomes to the stakeholders who fund research. If the funder can see themselves in your story, you win. Same research question. Completely different proposal structure. The next application secured half a million pounds. Then a million. Then over the course of my career, more than £10 million in research funding. Grant writing is storytelling. Your research is the plot. The funder needs to see themselves in the story. What's the most frustrating feedback you've received on a grant application? Save this framework. Repost for anyone applying for funding. #GrantWriting #AcademicFunding