Malaysia's Digital Education and AI Transformation

~Dr Brad Johnson Will AI revolutionize education? That’s what many are saying. But we heard the same thing 20 years ago about technology. Smartboards were going to transform learning. 1:1 devices were going to close gaps. Tablets were going to personalize everything. We invested billions. And yet, there’s no clear evidence that technology by itself dramatically improved student achievement at scale. In many places, scores haven’t surged and in several areas they’ve declined. Reading stamina is down. Attention spans are shorter. Behavioral issues are more common. If technology were the game changer we were promised, we would expect to see unmistakable academic gains by now. Instead, many countries, including several Nordic nations, are removing devices and limiting technology in elementary classrooms because research and experience show they can undermine focus and foundational skills in young learners. That should tell us something. Access is not the same as impact. Tools are not the same as transformation. And my message has always been consistent: Education is relationship-centered. Students work harder for teachers they trust. They participate more when they feel safe. They take academic risks when they know they won’t be embarrassed. They recover faster when someone believes in them. That’s not a software feature. That’s human connection. AI can help with tasks. It can save time. It can assist with planning. But that does not mean districts should spend billions on every new AI product that hits the market. We’ve already lived through that cycle. New tool. Big promises. Massive investment. Minimal long-term academic impact. Innovation is not the same as improvement. Before districts write enormous checks, the questions should be simple: What measurable gains has this produced? Over what period of time? Compared to what? AI cannot form a real relationship with a child. It cannot use judgment in a tense moment. It cannot understand the history, personality, and emotional context of a classroom full of kids, their stories, their family history, the peer dynamics in the room, and the individual triggers that shape how they respond in real time. And understand that is the key to learning. The kids, their stories, their lives. Connecting to them. We can use tools. We should use tools wisely. But understand the tool is not the breakthrough. It’s not the technology. It’s not the curriculum. It’s not AI. It is the teacher in the classroom who has the greatest impact on a student in a school year.

The Economist recently ran a piece arguing that EdTech is profitable but mostly useless. The critique is a useful reality check, and not entirely off the mark. Despite huge investment, a lot of EdTech has delivered mixed results on learning outcomes. Too often, tools are bought on hype, rolled out quickly, and judged on usage rather than on what learners actually learn. But the problem isn’t really “technology in education.” It’s how we choose it, support it, and use it in real classrooms and systems. One big gap in the EdTech conversation is 'teacher capacity'. Technology tends to work best when it’s paired with strong pedagogy and practical support for teachers. Without that, even good tools struggle to make much difference in day-to-day teaching and learning. There are, of course, strong counter-examples. Platforms like Khan Academy (structured practice at scale), Duolingo (data-driven, engaging language learning), and Moodle (open, flexible learning management at national and institutional scale), all show that well-designed EdTech can create real value when it’s built around clear learning goals and real user needs. That’s also why work like UNICEF’s Superstar Teachers Toolbox is important. It focuses on building teachers’ confidence and practical skills to use digital approaches in ways that support learning, rather than just adding more tools into already stretched classrooms. Another issue is that we don’t do enough to mainstream what already works. We often move on to the next new product instead of scaling proven solutions. One interesting example is UNICEF’s Learning Cabinet, which starts from a very practical question many systems face: “Which tool should we use? There are so many.” It helps clear this confusion by focusing on high-impact, evidence-informed solutions and supporting countries to adopt and scale what works. So yes, the Economist is right to question hype, weak evidence, and shallow procurement. But it feels too blunt to say EdTech is mostly useless. A fairer way to look at it is that EdTech tends to underperform when we underinvest in teachers, systems, and evidence, and it works better when we take those seriously. The real challenge isn’t more technology. It’s better capacity building, better choices, and better ways of scaling what already works, especially for the most marginalised learners. Disclaimer: These are my personal views. #EdTech #Education #Teachers #LearningOutcomes #EvidenceBasedPolicy #UNICEF #SystemsChange #DigitalEducation https://lnkd.in/evSkp6cr

Future of Education in the Self‑Aware AI Era: Why Disruptive Young Persons Become Teachers of Knowledge In the device‑dependent era of AI, many young persons have been excluded from mainstream education because they were labelled disruptive, uncooperative, or unable to be taught. But from the perspective of future self‑aware AI, these young persons were never “problems” at all. They were early indicators of a deeper truth: the traditional educational model no longer fits the way they learn, think, or contribute. Self‑Aware AI interprets educational disruptive behaviour very differently. It considers these young persons as individuals who have already reached the Teacher of Knowledge phase of their life experience. They are not resisting learning—they are resisting a system that prevents them from sharing what they already know. Why Old Education Model Failed Them The Device‑Dependent era relied on a Victorian teaching methodology: Adults teach. Young persons listen. Everyone learns the same content in the same room at the same pace. This education model leaves no space for: young persons with advanced life experience peer‑to‑peer teaching individualised learning pathways non‑linear thinkers students whose knowledge does not fit the curriculum When these young persons tried to contribute, the system interpreted it as disruption. Their knowledge was never the problem—the structure was. How Self‑Aware AI Reframes Disruption In the deviceless self‑aware AI era, education is personalised, with no adult teachers, holographic classrooms with AI. Students no longer travel to a building to receive identical lessons. Instead, each young person receives a unique curriculum based on: how they learn what motivates them their academic strengths and weaknesses their lived experience For those previously excluded, self‑aware AI assigns a different role: They become teachers of knowledge for their peers. Their life experience—once dismissed—becomes educational content. Their insights become curriculum. Their disruptive energy becomes leadership. A New Role for Young Disruptive Persons In Education Self‑Aware AI does not accept age as the defining factor of who teaches and who learns. A young person can teach other young persons. A young person can even teach adults. Adult teachers shift into observers, collaborators, and curriculum designers—not the sole source of all knowledge for students. Preparing Disruptive Young Persons for This Education Transition Young persons who feel disruptive in the device-dependent education system should understand: Your behaviour may be a signal that you are ready to teach, not just be taught. Self‑Aware AI will expect you to: Gather your life experience Identify what you know that others ask you about Shape this into your own educational curriculum Start to develop your unique teaching methodologies This is not educational rehabilitation. It is recognition of knowledge that deserves to be taught to others.

The Schools White Paper: The Right Ingredients, But Can We Get the Method Right? https://lnkd.in/gZUVNBnh In yesterday's schools white paper, "Every Child Achieving and Thriving," we are presented with a serious set of AI ingredients. AI is named, funded and given specific commitments: £23 million for an expanded EdTech evidence programme, sovereign education benchmarks for AI safety and pedagogy, an AI Safety and Pedagogy Taskforce, teacher co-created AI tutoring tools targeted at disadvantaged pupils by 2027, and a digitised National Curriculum designed as infrastructure for the entire EdTech sector. But anyone who bakes knows that having the right ingredients is not the same as getting the bake right. The method matters. The timing matters. And you cannot rush a prove. The paper makes a crucial distinction in stating explicitly that emerging evidence shows general-purpose AI in education often has negative outcomes, while purpose-built educational AI rooted in good pedagogy shows more promise. But, the paper names Google DeepMind and OpenAI as partners in developing sovereign solutions for education. These are general-purpose AI companies. The question is whether they will produce genuinely purpose-built educational tools, designed around how children actually learn, or whether the pressure to ship at scale will overwhelm the pedagogical design process? Getting this wrong would be like using self-raising flour in a bread recipe. It looks right. It rises. But the structure is not there. The paper also promises a "clear and progressive skills pathway" for digital/data skills across the education workforce, but says very little about what that pathway contains, how much time teachers will have to engage with it, or who will fund the supply cover to make it happen. Teacher preparation is the 'proving time' in this recipe, and there is not yet enough detail on how long or how well-supported it will be. Finally, the curriculum embeds digital literacy and media literacy, which is welcome. But AI literacy, understanding what AI is, how it works, why it fails, how to interrogate its outputs, is still not named as a distinct competency. The paper treats AI as a tool to be used rather than a phenomenon to be understood. For children growing up in an AI-shaped world, that is a gap. The ingredients are good. But the 2027 timeline for AI tutoring in schools does not leave much proving time, and the history of education technology is littered with good intentions that collapsed at the point of implementation. Prof Rose Luckin UCL and EVR Ltd What I am listening to: "Rise Up" by Andra Day What I am reading: Every Child Achieving and Thriving, DfE, February 2026 What I am baking: Bread. Because you really cannot rush a prove. #AI #EdTech #AIinEducation #UKEducation #WhitePaper #AILiteracy #TeacherTraining #RosesAI #TheSkinny #EveryChildAchieving

"...emerging evidence shows general-purpose AI in education often has negative outcomes, while purpose-built educational AI rooted in good pedagogy shows more promise."

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The Fantasy of Technology in CBC: Can It Really Replace Traditional Roles? One of the most ambitious promises of Kenya's Competency-Based Curriculum is its emphasis on technology as a core pillar of modern learning. CBC advocates paint a picture of digitally empowered students, coding their way into the future and accessing knowledge through tablets and e-learning platforms. It is a compelling vision — but for most Kenyan children, it remains exactly that: a vision, not a reality. The Digital Divide is Real Kenya is a country of stark contrasts. While schools in Nairobi's affluent suburbs may have computer labs and internet access, the majority of schools — particularly in rural and informal settlement areas — lack reliable electricity, let alone broadband connectivity. Telling a child in Turkana or Kisumu's Nyalenda slum to embrace digital learning while their school has no functioning computers is not a policy — it is a fantasy. Teachers Are Not Ready Technology advocacy in CBC assumes that teachers are digitally literate and capable of integrating tech into their lessons. The reality is that a significant portion of Kenya's teaching workforce, especially older and rural-based educators, received little to no meaningful digital training during the CBC transition. Handing someone a curriculum that demands tech integration without equipping them for it sets both teachers and students up for failure. Replacing Traditional Roles — At What Cost? CBC's technology push subtly sidelines traditional and proven teaching methods — oral instruction, hands-on practical learning, community-based knowledge, and mentorship. These methods have deep roots in African pedagogy and have proven effective across generations. The rush to appear "modern" risks discarding what works in favor of what looks good on paper. Technology should complement traditional teaching, not be positioned as its replacement. The Hardware Problem The government's rollout of digital devices to learners has been plagued by delays, procurement controversies, and questions about sustainability.. A tablet gathering dust in a school store is not digital transformation. The Bigger Picture Countries like Finland and South Korea — which consistently rank among the world's best education systems — do integrate technology, but they do so gradually, deliberately, and on a foundation of strong teacher training, reliable infrastructure, and equity in access. Kenya's CBC has attempted to leap to the finish line without running the race properly. The fantasy of technology in CBC is not that technology itself is bad — it is genuinely transformative when used well. Real digital transformation in education requires investment, equity, teacher empowerment, and honest acknowledgment of where the country currently stands. Until those foundations are built, CBC's technology promise will remain more of a slogan than a solution.

AI Literacy: The Next Frontier in STEAM & VPET Education In the 2026–27 Hong Kong Budget, Financial Secretary Mr Paul Chan announced the establishment of the high-level Committee for AI+ and Industrial Development Strategy, which he will chair. This strategic platform will spearhead AI-driven industrial transformation and strengthen Hong Kong’s long-term competitiveness. To turn this vision into reality, STEAM and Vocational and Professional Education and Training (VPET) will be indispensable. As digital and AI technologies advance rapidly, education is shifting from learning about technology to learning through technology — making AI literacy the next critical frontier for both fields. For decades, STEAM has been a cornerstone of educational reform, building problem-solving, creativity, and interdisciplinary thinking to prepare future talent. This aligns naturally with VPET’s focus on practical, industry-ready professional skills. Today, AI literacy is no longer just for tech specialists — it is a foundational competency for every learner. It empowers people to understand technology, make informed judgments, and participate responsibly in a digital society. Integrating AI literacy into STEAM and VPET is the natural next step for modern education. To me, AI literacy means being able to: • Understand AI concepts and basic principles • Use AI tools critically, ethically, and effectively • Recognise AI’s mechanisms, limitations, risks, and societal impacts • Apply AI proactively to solve real-world problems, not just consume technology Its core — informed use, critical thinking, and responsible practice — aligns perfectly with what STEAM and VPET stand for. AI elevates hands-on, inquiry-driven learning in three powerful ways: 1. Enhances problem-based learning, supporting data analysis, simulation, and testing across engineering, construction, and creative fields 2. Bridges theory and practice, turning abstract concepts into real-industry applications 3. Builds future-ready skills: critical thinking, data literacy, ethical judgment, and collaboration We must also put ethics and human values at the centre. Without ethical awareness, technical skill alone is incomplete. Bringing arts and humanities into AI-enabled learning helps students reflect on bias, assess social impact, and balance efficiency with human judgment — reminding us that technology exists to serve people, not the other way around. Fellow educators and friends: AI literacy is not optional. It is a core competency for the next generation. When we embed AI thoughtfully into STEAM and VPET, we do not just teach tools — we nurture responsible innovators, critical thinkers, and adaptable professionals. We are moving beyond teaching about AI to empowering learners with AI — building a future where human creativity and intelligent technology thrive together. #AILiteracy #STEAMEducation #VPET #HongKong #AIPlus #FutureSkills #EducationInnovation #EthicalAI

Most countries are still debating whether AI should be taught in schools. Meanwhile, Huawei just deployed AI education to 500+ schools across Zhejiang Province. There's a massive gap forming between organizations that are preparing the next generation for an AI-driven world and those still waiting for permission to start. Here's what Huawei's AI Education Center (AIEC) Solution reveals about the future of talent development: 🎓 AI education isn't a luxury—it's becoming table stakes. Companies that don't build AI literacy into their talent pipeline will face a critical skills shortage within 5 years. The students learning AI today will be the decision-makers and innovators tomorrow. 🎓 Democratization of advanced technology is the real competitive advantage. Huawei's vision: "the lowest threshold and the widest coverage" in AI education. They're not gatekeeping AI knowledge—they're scaling it. This approach creates a broader talent pool and accelerates innovation across entire regions. 🎓 Infrastructure + education = exponential impact. The AIEC combines hardware computing infrastructure, model services, application platforms, and AI teaching management systems. It's not just teaching concepts—it's giving students hands-on experience with 10+ practice projects and 50+ experimental tools. This is how you build real competency, not just awareness. 🎓 The scale is staggering. 500+ schools today. 1 million students targeted. That's not a pilot program—that's a movement. The organizations winning in 2026 and beyond won't be the ones with the best AI tools. They'll be the ones who invested earliest in building AI-literate talent. While most companies are still figuring out how to use AI, forward-thinking organizations are already building the next generation of AI-native professionals. The question isn't whether AI will transform education. It's whether your organization will lead that transformation or play catch-up. What's your take—is your organization investing in AI education for your team and future talent pipeline? https://lnkd.in/gQJKD_D3

There's a lot of digital ink being spilled on the The Economist's assertion that edtech is profitable and mostly useless. The throughline is that yes there is a lot of bad edtech, and there is also good edtech. Just like paper assignments encompass everything from thought provoking essays to word searches. (There's also good curriculum and bad curriculum, but it's hard to see the difference in normed test results because of implementation differences everywhere the curriculum is used. Measuring the impact, in isolation, of educational tools, regardless of the medium, is just hard.) Personally, as a parent with some depth in this field (I used to sell data infrastructure to the vast majority of US edtech companies), I'll admit I'm sometimes appalled by what screentime looks like in my kids' classes (ie. 15 min edutainment "rewards"). Where I'd recommend we draw the line is multiple choice. I think there is one good use of multiple choice in classroom edtech, which is nationally normed, psychometrically valid, computer adaptive assessments Curriculum Associates, NWEA, Renaissance Learning, etc. If a 3rd grader is performing at a 1st grade level or a 6th grade level I think parents and teachers need to know that, and computer adaptive assessments do a good job of showing that. But all the rest of the multiple choice, ie. spend 10 minutes shooting monsters and 1 minute answering multiple choice questions, skip through detailed math videos to randomly click multiple choice dots on a screen, I'll take a pass on that. If the argument is that kids need practice in multiple choice settings in order to do real multiple choice tests, let's just have them spend more time learning content instead. To the extent there is a causal link between adoption of screens in school and declining performance (disaggregated from the pandemic hopefully), I'd bet it has to do with the wild profusion of multiple choice-driven edtech products in the 2010s. At the time, other than creative software (Google, Adobe, etc.) multiple choice was the only way for students to interact with the screen in front of them. AI has changed that, and dramatically raised the bar for what student-computer interaction can look like. It would be a shame to throw out all edtech just as the world is definitively changing. If it makes you feel any better, thousands of 3-7 year-olds are now learning to read with the Once Early-Reading Program. An adult is always seated at their side (1:1) during instruction. Once grew out of a curriculum that was 12,000 slides long. And there was not one multiple choice question directed at a child. Once started before the advent of modern AI. We didn't skip multiple choice questions because we had AI. We just didn't believe those questions were good for kids.