Designing Effective Learning Environments

Yesterday’s Australian carried a story lamenting the extent of cheating at one of the nation’s top universities. It reflects a broader truth: our traditional approaches to assessment are under strain in the face of rapid technological change. As I’ve noted in recent posts about AI and its impact on universities, we cannot meet this challenge with detection software and punishment alone. These systems are unreliable, prone to false positives, and always a step behind the latest tools. They do little to build trust or prepare students for the realities of their future workplaces. The opportunity is far greater if we see AI as a catalyst for innovation rather than a threat. Assessment can, and must be reshaped to mirror real-world professional practice including: • Authentic tasks where AI is used as part of the toolkit for deeper insight and analysis. • Human skills first—ethical judgment, empathy, care, and critical reasoning, which AI cannot replicate. • Programmatic approaches emphasising growth, feedback, and competency over one-off testing. • Workplace-relevant evaluations that prepare graduates for careers where AI collaboration is the norm. This isn’t about “stopping cheating.” It’s about preparing students to thrive as ethical, capable professionals in an AI-enabled world. AI has already changed education. The real question is whether universities will lead that change—or be dragged along by it.

🎓 Can we revolutionize university education by borrowing a strategy from medicine?🎓 In healthcare, teaching hospitals have long been the gold standard for preparing future doctors—immersing them in real-world scenarios under the guidance of experienced professionals. Imagine applying that same model across other disciplines. This is exactly what the Space Flight Laboratory (SFL) at the University of Toronto has done, and the results speak for themselves. Since 1998, SFL has adopted a "teaching hospital" approach to educate its graduate students in spacecraft engineering, blending formal instruction, cutting-edge research, and hands-on, real-world practice. Students don't just learn theories—they apply them in mission-critical environments, working on actual satellite projects for paying customers. The outcome? Graduates who are not only skilled but also seasoned in the complexities of their field, ready to tackle challenges with confidence and creativity. Why stop at aerospace engineering? Entrepreneurial pedagogies have similarly embraced hands-on, real-world learning, pushing students to solve complex problems with innovative thinking. Like the teaching hospital model, entrepreneurial education thrives on bridging the gap between theory and practice, ensuring students are not just academically proficient but also professionally ready. Universities often keep real-world practice at arm's length, relegating it to internships and co-op programs. But as the demands of society grow more complex, it's time to rethink this approach. Imagine what could happen if we integrated these immersive learning models into disciplines beyond medicine and engineering—fields like business, environmental science, and the humanities. We could cultivate a new generation of graduates with the critical thinking skills and practical experience necessary to make immediate, impactful contributions to their fields. It's time to challenge the status quo and advocate for wider adoption of teaching hospital and entrepreneurial models across university disciplines. The future of education and society may depend on it. #EducationInnovation #TeachingHospitalModel #ExperientialLearning #EntrepreneurshipEducation #HigherEd #FutureOfEducation #InnovationInEducation #Universities

The Inconvenient Truth About Learning Design: From Content to Context As we delve deeper into the realms of education and professional development, there is an undeniable shift taking place. Many organizations still cling to the age-old idea that providing an abundance of content equates to effective learning. However, the inconvenient truth is that this approach is no longer sufficient. It’s time to move from content saturation to context-driven learning! The crux of effective learning design lies not just in the "what" but in the "how" and "why." Here are a few key insights on how this paradigm shift can redefine our strategies: 1. Understanding the Learner's Journey: Contextual learning begins with understanding the backgrounds, experiences, and challenges learners face. Tailoring content to real-world scenarios allows for a deeper connection and better retention. 2. Emphasizing Application Over Memorization: In a world filled with information, the capacity to apply knowledge in practical ways is paramount. When learning experiences are grounded in relevant contexts, they become not just theoretical but transferrable to real-life situations. 3. Creating Collaborative Environments: A learning design focused on context encourages interaction and collaboration. By facilitating a space where learners can share experiences and insights, we promote a richer, more diverse learning ecosystem. 4. Measuring Impact, Not Just Engagement: It's not enough to just collect data on how many people viewed your content. The real metric of success is the transformation that occurs— how the knowledge is applied and what changes result from it. 5. Iterative Learning Experiences: The journey of context-driven learning should be continuous. Regular feedback and refinement help ensure that learning experiences constantly evolve to meet the dynamic needs of learners. The future of learning design isn’t just about filling minds with information; it’s about creating meaningful, contextual experiences that inspire change. As we embrace this shift, let us challenge ourselves: how can we design learning experiences that go beyond content and truly resonate with our audiences? I invite you to share your thoughts below on how we can move from content to context in our learning approaches. Your insights could be the catalyst for someone else's journey! #LearningDesign #ContextOverContent #Education #ProfessionalDevelopment #LifelongLearning #LearningStrategies

The classroom was silent. 30 students, heads down, writing answers they memorized late last night. I was one of them many years ago, and many of our kids remain today such students. Education systems are mostly built for a world that no longer exists. A world where intelligence was personal, not widely accessible. We continue to assess students fine-tuning an industrial-age model. Prioritizing recall over reasoning, structure over adaptability, compliance over curiosity. In an AI-powered world, following instructions and repeating facts are no longer competitive advantages. Some educational systems are taking bold action: -         Finland has replaced subject silos with environments where students explore complex, real-world, topics across multiple disciplinary lenses -         Singapore aims to evolve its national curriculum beyond traditional academic knowledge by embedding 21st Century Competencies through its Social-Emotional Competencies framework and the EdTech Masterplan 2030 initiatives -         Khan Lab School lets students progress based on true mastery, not arbitrary term limits These initiatives and others will lead kids to: • be able to think critically and ethically • get comfortable with ambiguity • develop skills in collaborating with intelligent systems • build confidence in applying knowledge in unstructured, real-world scenarios We do not need another curriculum update. We need a fundamental rethinking of what education is for. AI is currently rewriting the rules of work, creativity, and leadership. It is time our schools started reflecting on and preparing for that new reality. To education leaders, policymakers, and innovators: What bold moves are you making to prepare students for a world shaped by intelligent machines?

Good learning design can only get you so far... For years, I thought L&Ds should focus solely on designing fantastic learning experiences. 👉 Learning how the brain works 👉 Learning how behaviors change 👉 Understanding & combining different learning methods 👉 Spacing learning in time 👉 Offering space to practice 👉 Making the experience hyper relevant All of these ARE important. But over time, seeing many L&Ds frustrated, even with the BEST learning experiences, I've come to reflect on how important the environment truly is. If, after a learning experience, people go back to a space where: 👎🏻 Curiosity is punished. 👎🏻 Experimentation is banned. 👎🏻 Failure is seen as the devil. 👎🏻 There's no opportunity to apply what they've learned. 👎🏻 Pressure to deliver is higher than the reward for improvements. 👎🏻 They hear: "We're doing things a certain way, there's no time to change." Even the best learning experiences will not deliver to their potential. Let me add some controversy to the mix: 😳 I believe AI will be able to design & deliver FANTASTIC learning. 👀 I also believe human-to-human learning experiences will become a "luxury". ✨ And it still WON'T be enough. No matter how good AI gets, and no matter how good L&Ds get at delivering learning, the environment will still kick our asses. So, to all the companies looking to adapt to what's coming next, let your L&Ds: ✌🏻 Employ AI to design and deliver just-in-time, on-the-job learning. ✌🏻 Design learning experiences that focus on connection over content. BUT most importantly: ✌🏻 Diagnose and act on what's blocking people from learning. Even if that means adapting processes, running long-term change projects, redesigning incentives, or rethinking org structure. Rant done 🎬. #learninganddevelopment #learningarchitecture

When was the last time you asked yourself "What can I add to this learning experience?" You're asking yourself the wrong question. I learned this the hard way when designing a leadership program for first-time managers. My first iteration on paper was packed with content: video lectures, case studies, role-play scenarios, reflection exercises, peer discussions, and multiple assessments. I was proud of how comprehensive it was. Then I realised the harsh truth: these managers do not have so much time. If I were to get this program live, no one would finish it. I needed to simplify it - A LOT. The best learning designs aren't built up. They're stripped down. 🧩 The Jenga Strategy Now I design everything by "designing to the breaking point" - removing elements one by one like Jenga blocks until the tower wobbles, then adding back just enough to prevent collapse. That wobble zone is where the real learning happens. I took a radical approach: no instructors, no videos, no perfect examples. I removed element after element until we had just 4 things: - Real-world case studies - Peer feedback loops - Weekly mentor check-ins - Actionable tools to apply in their context The result? We had a ~90% completion rate! ✅ WHAT WORKS: Removing instructions until learners must think critically Cutting content to create productive struggle Eliminating scaffolding to promote problem-solving ❌ WHAT DOESN'T: Endless resources "just in case" someone needs them Over-explaining that robs learners of discovery Perfect examples that discourage experimentation Your best learning designs aren't the ones with the most elements. They're the ones where every single element earns its place by driving real results. The next time you're designing a learning experience, don't ask "What else can I add?" Ask "What else can I take away before it breaks?"

We’ve got it backwards. Students arrive on campus, pick a major (often by default or pressure) and then spend four years trying to figure out what jobs that major “slots” them into. It’s a process driven by tradition, not by purpose. What if we changed things up? What if we started by helping students discover what kind of work gives them energy, what kinds of problems they want to solve, and who they want to serve? Then, and only then, we guide them toward academic paths and experiences that align with that purpose. This is where experiential learning plays a critical role. When students take on real-world projects, they will get the necessary exposure which is insight. It’s a chance to test what resonates and what doesn’t. They learn not just how to work but why. If we’re serious about preparing students for fulfilling, future-ready careers, we can’t treat education and work as separate worlds. They have to inform each other, from day one. The price of college is too high for students to leave without clarity, confidence, and connection.

What if universities became the launchpads for 𝐀𝐈-𝐧𝐚𝐭𝐢𝐯𝐞 𝐭𝐚𝐥𝐞𝐧𝐭—not just academic hubs? "AI is making students lazy." We hear this a lot. But what if the opposite is true? Used well, AI doesn’t replace learning—it deepens it. It can help students ask better questions, receive instant feedback, unlock personalized pathways, expand access to research, and transition from memorization to curiosity, experimentation, and mastery. This is the shift I’ve been observing across Asia’s education landscape, and it was powerfully echoed at THE Digital Universities Asia 2025, where academic leaders and tech innovators explored how universities can evolve in an AI-powered world. One standout voice: Junfeng Li, VP of Huawei and CEO of Global Public Sector BU. His keynote made a bold case for transformation, backed up with tangible results. Huawei is partnering with universities globally to redesign how students learn, engage, and research in the digital age. Here’s what stood out: 1. From Passive Learning to Active Exploration Smart classrooms aren’t just delivering content faster—they're creating space for personalized, adaptive learning. Zhejiang Shuren University uses AI-driven lesson planning and 24/7 intelligent Q&A—tailoring the experience to students. 2. Every Major Needs Digital Fluency No matter the discipline, students need applied tech skills. Shenyang Institute of Technology integrates real-world enterprise practices into learning. With Huawei, it built 28 industry-aligned labs in 5G, HarmonyOS, AI, etc., cultivating job-ready talents and accelerating education transformation through deepening industry-academic integration.   3. Campuses as hands-on Innovation Hubs At Shanghai Jiao Tong University, Huawei co-built one of the world’s largest campus innovation hubs. Through diverse practical initiatives, this hub—featuring shared devices, open practice hub, bootcamps, and competition— effectively empowers thousands of students to become innovative and future-oriented talents. Huawei’s “1+3” Intelligent Education Solution also shows how it turns curiosity into capability. •1 Core: Hands-on digital training •3 Scenarios: Smart Classroom, Smart Campus, Research Data Management/Scientific Research   This is not only about future-proofing students. It’s about present-empowering them. To think critically. To build creatively. To collaborate courageously, with each other 𝐚𝐧𝐝 AI. AI isn't a shortcut—it's a mirror, reflecting our institutions' readiness to evolve, our willingness to reimagine education, and our commitment to preparing the next generation.   I’m grateful to collaborate with partners like Huawei, who are leading this transformation not just as tech providers, but as co-creators of a more intelligent and impactful education ecosystem. Education and future-work leaders: How do you see #AI supporting—not sabotaging—real learning? Let’s keep bridging the gaps between knowledge and action, academia and industry.

🎯 One size never fits all in the classroom. That’s why differentiated instruction isn’t just a buzzword, it’s the reality of teaching today. This framework breaks it down into four simple levers: 1. Content → What students learn 2. Process → How students learn 3. Product → How students show learning 4. Environment → Where students learn When we adjust these, even slightly, we shift classrooms from “delivering lessons” to designing learning experiences. Some highlights I love from this chart: 📚 Tiered assignments & choice boards (student ownership in content) 🧩 Jigsaw method & gallery walks (collaboration in process) 🎭 Performance tasks & digital portfolios (creativity in product) 🪑 Flexible seating & movement breaks (agency in environment) It’s not about doing everything at once. It’s about finding the one small change that unlocks engagement for more students. 👉 Teachers, which of these strategies do you already use and which one are you curious to try next? #Education #TeachingStrategies #DifferentiatedInstruction #EdTech #ActiveLearning

Using unique nationally representative school and system survey data from 13 education systems in low and middle-income countries collected through the World Bank’s Global Education Policy Dashboard (GEPD), we examine how the pedagogical practices, including practices to foster student engagement and subject content knowledge of primary-school teachers, correlate with their students’ learning outcomes. My colleagues below find that student performance on literacy (and, to a lesser extent, math) assessments are correlated with receiving instruction from teachers with better-measured pedagogical skills. Learning strategies that support greater student engagement appears to be highly predictive of student learning outcomes in literacy. The findings confirm the important role of interventions that provide direct pedagogical support and feedback to teachers through training, instructional leadership, and evaluation. https://lnkd.in/efZ6WZrf Brian Stacy Sergio Venegas Marin Halsey Rogers Maryam Akmal Hersheena Rajaram Viyaleta (Violeta) Farysheuskaya