E-Learning Course Design

Many people believe live trainings work better simply because people can talk to each other face‑to‑face, but that’s not the real reason. In reality, their effectiveness comes from something else entirely, they naturally follow a powerful learning rhythm. Great offline trainings follow one simple logic: action → reflection → understanding → application. This is Kolb’s Cycle. And it’s incredibly powerful. The problem? It was almost impossible to implement it in online learning. That’s why 90% of online courses look like “interactive lectures”: nice slides, videos, quizzes. But that’s content consumption, not transformation. And now - the unexpected twist. For the first time, online learning has caught up with offline experiences. Because AI removed the main barrier: it finally allows learners to get experience, reflection, and practice in a personalized way. Here’s how Kolb’s Cycle looks in modern learning design: 1️⃣ Concrete Experience — action Essence: the learner must do something, live through a situation, face a task — ideally experiencing difficulty or making a mistake that shows their current model doesn’t work. How online: role-based dialogue, scenario simulation. 2️⃣ Reflective Observation — reflection Essence: pause and think — what happened, what actions were taken, and why the result turned out this way. How online: interactive reflection prompts; AI coach provides feedback based on performance and the learner’s own reflections. 3️⃣ Abstract Conceptualisation — understanding Essence: form a new behavioural model — concepts, principles, algorithms that explain how to act more effectively. How online: short video lecture, model breakdown, interactive frameworks, checklists, interactive infographics. 4️⃣ Active Experimentation — application Essence: try the new model in a safe environment and observe the result. How online: AI-based simulation, situational exercise, case-solving with the new approach; AI coach supports and adjusts. The outcome? Online learning stops being “content” and becomes a behaviour tracker. A course becomes a training simulator, not a film. Kolb’s Cycle finally becomes real in digital learning. Do you use this framework? What results have you seen?

Too many learning designers obsess over learning goals. But learning goals alone don’t drive results. A goal without a plan is a wish. A plan without habits is a dead end. If you’re not designing for execution, you’re designing for failure. What you need is a GPS. 📍 Goal = Your Destination (Where are we going?) 🗺 Plan = Your Route (How do we get there?) 🔁 Systems = Your Driving Habits (What keeps us moving forward?) Without all three, learning gets off track. Here’s how to make them work together: STEP 1: Set a Clear Goal 📍 A goal defines success. It answers: What should the learner achieve at the end? What doesn't work: ❌ "Improve digital literacy" (What does that even mean?) ❌ "Complete compliance training" (Nobody cares) ❌ "Learn leadership skills" (Too vague to be useful) Instead, give your learners real destinations: ✅ "Build and launch a working website for your side project by next month" ✅ "Prevent a data breach by identifying the top 3 security risks in your daily work" ✅ "Lead your first team meeting using our new decision-making framework" 👉 WHAT TO DO: Write your learning goal using this formula: "By the end of this course, learners will be able to [specific skill or outcome]." STEP 2: Create a Realistic Plan 🗺 A learning plan without milestones is like a road trip without rest stops – it leads to burnout and abandonment. Your plan should include: - A structured learning path (What concepts come first? What builds on them?) - Delivery methods (Instructor-led, self-paced, hands-on?) Milestones & check-ins (How do you track progress?) 💡 Example Plan for a Web Development Course: Week 1: HTML Basics (text, images, links) Week 2: CSS Fundamentals (styling, layouts) Week 3: Hands-on Project (Build a personal site) Week 4: Peer review & iteration 👉 WHAT TO DO: Start with the final assessment or project, then reverse-engineer your learning plan. Plan for failure. Build recovery routes and alternative paths. Your learners will thank you. STEP 3: Build Supporting Systems 🔁 Here's where the rubber meets road. Systems aren't sexy, but they separate success from wishful thinking. 💡 Example Habits for Learners: Reflect after each lesson (Journaling habit) Apply skills in small, real-world tasks (Practice habit) Engage in discussion forums (Community habit) 👉 WHAT TO DO: Pick 2–3 small habits to reinforce learning effectiveness. STEP 4: Track & Adjust 📐 A great plan still needs real-time tracking to adjust the course. - Completion Rates – Are learners dropping off? Where? - Knowledge Checks – Are they grasping key concepts? - Engagement Metrics – Are they interacting with content/peers? - Post-Course Outcomes – Are they applying what they learned? 💡 Example: If learners struggle in Week 2, add a quick video explainer or hands-on exercise before moving forward. 👉 WHAT TO DO: Use a simple feedback loop: Observe → Adjust → Test → Repeat. So before launching your next course, ask yourself: "Is my GPS in place?"

A year ago I shared a framework called GROWTH™. It didn’t perform particularly well. Which is funny, because over time it’s become one of the models I rely on most when designing learning experiences. Most training programs are built as courses. But the way people actually develop capability looks very different. Progress happens across a series of experiences—practice, feedback, reflection, and iteration. In other words, it happens through a learning journey, not a single event. The GROWTH framework is a way to design those journeys more intentionally. It breaks the process into six stages: G — Goal Setting R — Research & Empathy O — Outline the Experience W — Work in Layers T — Test & Adapt H — Highlight Progress Over the past year, I revisited the framework, expanded it, and turned it into a practical guide with examples, worksheets, and a full case study on redesigning onboarding as a learning journey. I also realized something interesting. GROWTH is actually one of the foundational pieces behind another model I’ve been developing called The Academy Engine™, which focuses on building scalable learning ecosystems. If the Academy Engine explains how education systems operate, GROWTH focuses on how the learning journey itself should be designed. If you’d like the full guide and templates, you can download it below. Curious how others think about this. When you design learning, do you think in terms of courses or journeys?

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

Designing learning that works for every mind. In preparation for our session at World of Learning in October, Emma Hutchins and I are asking neurodivergent learners to share the 'one thing' above all others that would improve their digital learning experience. Thanks so much to everyone who engaged with and contributed to our last LI post. The list below is what we have so far. But are we missing anything? We'd love to hear from you in the comments if your 'one thing' doesn't appear on our list. Content design and structure - Provide clear and consistent instructions throughout all learning materials. - Ensure a clear and logical content structure so information fits neatly into well-defined categories. - Avoid poor colour contrast and other design issues that contribute to sensory overload. - Avoid locked navigation controls (like 'Continue' buttons) unless it is obvious what needs to be completed to progress. Control over media and sensory input - If possible, avoid linking to external video sites (such as YouTube) unless the learner’s return path is clear and accessible. - Do not include moving or animated content unless learners can pause or stop it. - Allow learners to change the speed of video content (both slower and faster) to suit their processing needs. - Always provide transcripts for video and audio to offer choice in how content is accessed. - Give learners control over narration and audio - allow them to start, stop, or bypass it entirely. - Keep multimedia experiences manageable to avoid overstimulation from multi-sensory overload. Assessment and feedback design - Write unambiguous questions and instructions and test them for clarity. - Provide clear, direct feedback for knowledge checks - explicitly state the correct answer and explain why it is correct. - Avoid double negatives in both questions and feedback, as they slow comprehension and retention. #WOL25 #Neurodiversity #Inclusion #Accessibility  (Five outlined human profiles, each with different colourful brain representations, including connected nodes, flowers, gears, puzzle pieces, and hearts, symbolising diverse thinking styles.)

A course slide isn't done when the content is in. There's a version that looks finished. And a version that actually works. A single screen of learning content has more invisible decisions in it than it appears. Take text alone. The weight of the heading. The size relative to the body. The spacing between lines. The width of a paragraph block. Each of these is a decision. And each one either helps the reader move through the content or quietly works against them. It sounds like an aesthetic preference. It isn't. When text hierarchy is off, learners don't struggle consciously. They just feel the friction. Their attention wanders. They lose the thread. When it's right, they don't notice it at all. They just... follow. That's the real job of formatting. Not alignment. Not font size. Attention management. Every heading placement, every line break, every block of white space is a quiet instruction to the reader's brain: Start here. This matters. Pause. Move on. Some clients come to me having already built a course in-house. The content is solid. The subject matter experts did their job. But the learning isn't landing. Very often, it’s not the content. It's that no one managed the reader's attention. If your courses look fine but aren't performing, this is worth looking at before anything else. — Take a look at the example below, it’s a very old and well-known one. If it hits you the way it hit me the first time, that reaction is the point. That's your brain responding to good attention management. It's not a trick. It's design doing exactly what it's designed to do. #LearningAndDevelopment #CorporateTraining #ElearningDesign #LDStrategy #VisualDesign

Spoiler alert: Forcing learners to view everything doesn’t improve learning.... It just teaches them how to click faster. You’ve built the slide in the course. -> Five hotspots on it. -> Next button locked. -> No progress unless they clicked every item. You tell yourself: All the 𝘤𝘰𝘯𝘵𝘦𝘯𝘵 𝘪𝘴 𝘪𝘮𝘱𝘰𝘳𝘵𝘢𝘯𝘵. 𝘛𝘩𝘦𝘺 𝘯𝘦𝘦𝘥 𝘵𝘰 𝘴𝘦𝘦 𝘪𝘵 𝘢𝘭𝘭. 𝘛𝘩𝘪𝘴 𝘬𝘦𝘦𝘱𝘴 𝘵𝘩𝘪𝘯𝘨𝘴 𝘰𝘯 𝘵𝘳𝘢𝘤𝘬. But here’s what 𝘁𝗵𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗿 𝘀𝗲𝗲𝘀: Click. ��𝘭𝘪𝘤𝘬. Click. 𝘕𝘦𝘹𝘵. This is not engagement. This is task completion. It's 𝗳𝗼𝗿𝗰𝗲𝗱 𝗰𝗼𝗻𝘁𝗿𝗼𝗹. 𝘈𝘯𝘥 𝘩𝘦𝘳𝘦’𝘴 𝘵𝘩𝘦 𝘱𝘳𝘰𝘣𝘭𝘦𝘮: Forced control doesn’t drive better learning. It drives frustration. Boredom. Fake interaction. You’re not guiding the learner. You’re micromanaging their experience. 𝗥𝗲𝗮𝗹 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 doesn’t happen because we lock content behind conditions. It happens when people choose to stay curious. 𝘎𝘳𝘦𝘢𝘵 𝘮𝘢𝘳𝘬𝘦𝘵𝘦𝘳𝘴 𝘢𝘭𝘳𝘦𝘢𝘥𝘺 𝘬𝘯𝘰𝘸 𝘵𝘩𝘪𝘴. • They use clear headlines to spark interest • They guide you with story, not rules • They give freedom but design every part to pull you forward That’s what we need more of in e-learning. That’s what 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗱 𝗳𝗿𝗲𝗲𝗱𝗼𝗺 looks like. 𝘚𝘰 𝘩𝘰𝘸 𝘥𝘰 𝘺𝘰𝘶 𝘢𝘱𝘱𝘭𝘺 𝘵𝘩𝘪𝘴 𝘪𝘯 𝘢 𝘚𝘵𝘰𝘳𝘺𝘭𝘪𝘯𝘦 𝘩𝘰𝘵𝘴𝘱𝘰𝘵 𝘴𝘭𝘪𝘥𝘦? Instead of locking the Next button: • Use hotspot titles that generate interest • Let learners explore the content in any order • Add a reflection prompt or mini-question after each hotspot • Wrap the slide with a clear call: Ready to move on, or explore another? No locks. No traps. Just clever design with a clear path. This approach doesn’t mean less structure. It means more intention. It means trusting the learner and designing content that earns their attention. Design freedom isn’t about letting go of control. It’s about using design to earn it back.

Here's something I've learned as an instructional designer - More interactivity doesn't necessarily equate to a more effective course... In the effort to create engaging content, it's easy to fall into the trap of equating busyness with learning. But let's be real - a course overloaded with clicks, games, and gimmicks might just be pretty packaging on a lackluster product. It may look fun, but if those elements don't align with the course's objectives, they're really just window-dressing. I'm a big believer in avoiding adding unnecessary fluff - words, images, sounds - that don't contribute to learning. These elements can increase cognitive load, leading to learner fatigue and diminished effectiveness. When considering interactive features like quizzes, simulations, or discussions, ask yourself: do they enhance the learning goals? Interactivity can be as simple and profound as fostering a community through discussion, promoting dynamic, peer-supported learning environments. So, here's the takeaway for all of us designing learning experiences... Align every element of your course with the intended learning outcomes. Evaluate the relevance and impact of interactivities. Resist the allure of interactivity for its own sake. Purposeful design is key. What strategies do you use to ensure your course interactivities are meaningful and effective? #eLearning #InstructionalDesign #InstructionalDesigner #LearningandDevelopment

AI is reshaping the future of learning, not by replacing educators, but by amplifying human potential. I just read Google’s new position paper on 'AI and the Future of Learning', and several points resonate strongly with my own experiences in e-learning, agentic AI, and responsible innovation. Key takeaways for educators, learning designers and AI practitioners:- 1. Human-in-the-loop matters:- AI should empower teachers and learners, not supplant them. Educators remain central in designing, customizing, and supervising AI tools. 2. Personalized, adaptive learning:- AI can meet learners where they are, adapt to their pace, strengths, and needs, especially powerful in large scale or resource-constrained settings. 3. Ethics, fairness, transparency:- Tools must be built responsibly, transparent about data usage, bias, and decisions. Learners, teachers, and their families should understand how AI arrives at suggestions and always have recourse. 4. Skills for the future:- Beyond knowledge recall, education needs to foster curiosity, metacognition, collaboration, and lifelong learning. AI becomes a partner in cultivating how we learn, not just what we learn. As someone who leads e-learning and agentic AI initiatives (and working on courses / frameworks for learning system design), here are some reflections:- 1. Design with pedagogy first:- When building courses or tools, we must anchor in learning science and best practices. Agents or AI modules should align with what we know about how people learn, including cognitive load, scaffolding, and feedback loops. 2. Build with practitioners:- Co-design with educators ensures the AI tools remain grounded in context, and helps avoid misalignment or unintended biases. 3. Measure impact holistically:- Beyond completion or test scores, we should evaluate growth in learner agency and self regulation, especially for adult learners or professionals. 4. Scale responsibly:- The potential for scaling personalized learning is huge, but we must not lose sight of the social, cultural, and equity aspects of learning design. 🧭 In my upcoming course on Augmenting Collective Intelligence via Autonomous Agents + Human Experts, I'll integrate several of these insights:- embedding AI tutors in training, designing feedback loops, and ensuring alignment with ethical & pedagogical frameworks. 💡 Question for my network:- How are you balancing AI tool adoption in education or training environments while preserving educator control, equity, and learner agency? Would love to hear your experience or frameworks that are working. #AI #EdTech #LearningDesign #AgenticAI #LifelongLearning #InstructionalDesign #AIgovernance

“Make it harder—but in a good way.” We often chase smooth training experiences: flawless slides, perfectly timed modules, minimal friction. But according to Elizabeth Bjork & Robert Bjork, that’s exactly where we miss the boat. Their research argues that desirable difficulties—those thoughtfully introduced hurdles—boost long-term learning far more than comfortable ease. Key takeaways: • Learning ≠ Performance: Just because learners blaze through a module doesn’t mean they’ll remember it. • ‘Make it harder—but make it meaningful’: Spacing, interleaving, retrieval practice (yes—frequent testing) all work. • Don’t mistake familiarity for mastery: Rereading feels good. It doesn’t last. So what does this mean for us as designers and facilitators? Rethink your “easy wins” modules. Could you insert a quick retrieval task or surprise switch-up? Instead of big blocks of content, build short segments that force learners to pull information—not just consume it. Add variety—flip the order, change the format, ask a question instead of delivering a slide. Variety + retrieval = stronger memory. When we shift focus from “smooth experience” to “durable learning,” we flip the script. Training becomes less about immediate comfort and more about lasting impact. If you’re designing your next workshop, micro-course, or internal training, ask: Where am I making it too easy? Maybe that’s where the magic is hiding. 🔗 https://lnkd.in/gyh362hv