Learning Experience 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?

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?

Why do some training programs create real transformation, while others fade before the next team meeting? I recently joined Bill Banham on The Voices of the Learning Network Podcast to unpack this question and preview my keynote at this year’s Connect Conference. The answer lies in neuroscience: the brain’s architecture defines how we learn, remember, and apply. When organisations ignore that, even the best-designed programs fail to leave a trace. Listen to the full conversation here: https://lnkd.in/en5cKVFE Overload vs. Effectiveness Many organisations fall into what I call the “efficiency trap.” They design training for the facilitator’s convenience, not the learner’s brain. Our brains don’t thrive under marathon sessions or dense slide decks. They need rhythm, variety, and rest. The science is clear: • Shorter, spaced sessions improve consolidation and memory. • Multimodal design (visuals, discussion, application) keeps engagement high. • Deliberate downtime activates the brain’s default mode network — where meaning forms. It’s not about more information. It’s about designing conditions for real change. Behaviour Change, Not Just Courses Too often, the answer to every performance problem is “build another course.” But knowledge alone doesn’t drive change, behaviour does. Effective learning experiences include: • Experience-based triggers that prompt action. • Social reinforcement to sustain new habits. • Retrieval practice to strengthen recall and confidence. When you shift from course completion to behaviour activation, learning stops being an event; it becomes a habit. Navigating AI and Automation AI brings both opportunity and risk. If we outsource too much thinking, we weaken the neural pathways that make us adaptable and creative. Some guiding principles I shared on the show: • Use AI to augment critical thinking, not replace it. • Design friction points that encourage reflection. • Give early-career learners space to build expertise before automation takes over. AI can enhance learning, but only when we keep the human brain at the center. Whole-Brain Design in Action At Synaptic Potential, we’ve seen organisations transform by embedding neuroscience into learning strategy. One global firm reshaped C-suite culture by introducing neuroscience-based reflection tools that transformed how leaders approached feedback. Another redesigned performance reviews to make them more constructive and less stressful, boosting engagement and trust. These results didn’t come from adding more content, but from aligning with how people actually learn. A Field Guide for Learning That Lasts If you’re in L&D or leadership, your challenge isn’t just to deliver information, it’s to create change that endures. That starts with respecting how the brain learns, consolidates, and grows. Because when we design with the brain in mind, learning doesn’t just stick, it scales.

When Teams Grow, Design Their Experience: An LXD Perspective. Rapid growth is often celebrated as a marker of success. Teams expand, business objectives increase, and new responsibilities are introduced. Yet growth often comes faster than the systems and processes that support it , leaving teams misaligned, overwhelmed, and disengaged. A sales team I worked with had grown from 10 to 25 members over six months. While expansion brought exciting opportunities , it also introduced a host of challenges: 📝 Increased administrative work and reporting requirements 📅 More frequent meetings for alignment across an expanded team 🎯 Higher performance expectations and KPIs ❓ Ambiguity in roles and responsibilities as new members joined Despite their enthusiasm and capability, the team began reporting stress, confusion, and a sense of constant pressure. From a Learning Experience Design perspective, processes that worked for a smaller team often do not scale without adjustment. The team’s capacity their available time, attention, and cognitive bandwidth did not expand in line with expectations. Role ambiguity and overlapping responsibilities created duplication of effort and accountability gaps. Here came an opportunity to redesign the team’s capacity and learning ecosystem rather than simply redistribute tasks. Key interventions included: 🔍 Conduct a Capacity Audit: Every task, meeting, and reporting requirement was analyzed to identify bottlenecks, duplication, and low-value activities. 📌 Prioritize Strategic Work: Non-essential tasks were delegated or removed. Core responsibilities aligned with business impact were clearly highlighted. ⚙️ Redesign Processes: Reporting templates were streamlined, recurring meetings reduced, and approvals standardized to reduce friction. 💡 Embed Reflection and Learning: Weekly “team retrospectives” were introduced, where team members shared wins, challenges, and lessons learned, enabling process improvement and knowledge transfer. 🧩 Clarify Roles and Responsibilities: Each team member’s tasks and ownership were mapped, eliminating overlap and increasing accountability. The results were striking. Performance stabilized as team members could focus on fewer, high-impact activities. Engagement increased 💪 because individuals felt their work mattered, and they had the space to contribute strategically rather than simply execute. Teams are more than output machines they are human systems. Rapid expansion can overwhelm these systems if we fail to consider capacity, clarity, and reflection. Designing growth with empathy and learning in mind ensures that teams remain motivated, skilled, and aligned. Ultimately, success comes not from doing more, but from doing better, together 🤝. #microlearning #learningeveryday #learningwithhiral #LearningExperienceDesign #EmployeeEngagement #Leadership #TeamDevelopment #ContinuousLearning #TeamCollaboration #LeadershipDevelopment

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 Pedagogically Intentional Framework for Lesson Planning High-quality instruction is the result of deliberate instructional design, not chance. This HyperDoc-based lesson planning framework functions as a conceptual and practical guide for educators seeking to design learning experiences that are rigorous, inclusive, and learner-centered. 🔹 Engage – Activating Curiosity & Prior Knowledge Instruction begins with a cognitively stimulating provocation that activates schema, builds relevance, and establishes purpose. Strategic hooks foster intrinsic motivation and emotional investment in learning. 🔹 Explore – Inquiry-Driven Knowledge Construction Learners interact with multimodal, curated resources that promote investigation, sense-making, and conceptual exploration. This phase privileges student voice, choice, and agency while supporting constructivist learning practices. 🔹 Explain – Conceptual Clarification & Explicit Instruction Through targeted instruction, guided discourse, and formative checks for understanding, educators address misconceptions and consolidate conceptual clarity. Learning intentions and success criteria are made explicit to anchor understanding. 🔹 Apply – Authentic Transfer & Skill Integration Students engage in performance-based tasks that require the application, synthesis, and transfer of learning. This stage deepens understanding by situating knowledge in authentic, real-world contexts. 🔹 Share – Feedback, Discourse & Knowledge Co-Construction Learners communicate their thinking, engage in peer critique, and respond to feedback. This social dimension of learning strengthens metacognition, accountability, and collaborative competence. 🔹 Reflect – Metacognitive Awareness & Goal Orientation Structured reflection enables learners to evaluate their learning strategies, monitor progress, and set intentional goals—cultivating self-regulated and reflective learners. 🔹 Extend – Deep Learning & Cognitive Stretch Extension opportunities provide pathways for enrichment, interdisciplinary connections, and higher-order thinking, ensuring sustained engagement beyond core instructional time. ✨ This framework serves as a pedagogical roadmap for lesson planning, firmly aligned with Universal Design for Learning (UDL) principles. It ensures accessibility, differentiation, and equity while maintaining high expectations and cognitive demand. 💡 Intentional lesson design transforms classrooms into spaces of deep inquiry, authentic engagement, and meaningful learning. #PedagogicalDesign #LessonPlanning #InstructionalExcellence #UDL #StudentAgency #InquiryBasedLearning #AssessmentForLearning #DeepLearning #EducationLeadership

Storyboards are more than design documents — they're powerful learning roadmaps. Many people see storyboards as just a collection of visuals. But they’re actually your secret weapon for designing impactful learning experiences. Here’s how to make storyboards that truly drive learning: 1️⃣ Align with objectives   → Don't just list topics.   → Match each slide to specific outcomes. 2️⃣ Know your audience → 2020: One-size-fits-all content. → 2025: Personalized learning paths. 3️⃣ Structure for success   → Break content into digestible chunks.   → Use consistent templates across modules. 4️⃣ Detail each slide   → Include visuals, text, interactions.   → Leave nothing to interpretation. 5️⃣ Visualize the journey   → Show how learners navigate the content.   → Use flowcharts to map decision points. 6️⃣ Plan for engagement   → Static slides are dead.   → Design interactions that spark thinking. 7️⃣ Integrate accessibility   → It's not an afterthought.   → Plan for diverse needs from the start. 8️⃣ Embed assessments   → Sprinkle in knowledge checks.   → Reinforce learning at every step. 9️⃣ Collaborate and iterate   → Involve SMEs, designers, developers early.   → Refine based on real-time feedback. 🔟 Version control is crucial   → Label clearly (v1.0, v1.1, v2.0).   → Track changes meticulously. Storyboards aren't just about layout. They're about crafting experiences. Master this approach: → Boost engagement → Improve retention → Generate tangible results What's your storyboarding strategy?

Golden Thread Series #6: Tie Culture + EX + CX through experience design. If culture, employee experience, and customer experience feel like three separate things in your organization, you don’t have a strategy problem. You have a design (and a leadership) problem. Experience design is where the golden thread either becomes real or quietly dies in PowerPoint. Here’s the truth: 👉 Most organizations talk about culture. 👉 Some measure EX and CX. 👉 Very few intentionally design experiences that connect all three. That’s the gap. Experience design is the discipline that forces alignment by answering uncomfortable questions: ❓ What do we want people to actually experience? ❓ And how do we make that repeatable? To operationalize the golden thread through experience design, leaders need to focus on three things: 1️⃣ Design from/for culture, not touchpoints. If your values are not explicitly translated into behaviors, decision rules, and moments that matter, they’re just posters. Culture should inform how experiences are designed, not sit alongside them. 2️⃣ Design the employee experience before the customer experience. This is where many CX efforts quietly fail. You cannot design a seamless, empathetic customer journey on top of broken workflows, conflicting incentives, or under-supported employees. Map and design the employee journey that supports each critical customer moment. If employees experience friction, customers will too. Always. 3️⃣ Design for consistency, not for heroics. Great experiences should not rely on exceptional people doing extraordinary things in flawed systems. Experience design operationalizes the golden thread by embedding desired behaviors into processes, removing friction by design, and making the “right experience” the easiest one to deliver. When done well, experience design becomes the connective tissue between: 🔁 Culture (what we believe) 🔁 EX (how work feels) 🔁 CX (how customers experience us) 🔁 Business outcomes (what we achieve) This is where strategy stops being aspirational and starts being executable. Fix the culture. Design the experience. The outcomes will follow. For more details, see the link in the first comment. #culture #employeeexperience #customerexperience #leadership #fixtheculturefixtheoutcomes #builttowin

THE ART OF LEARNING DESIGN IN THE AGE OF AI Mastery is not a search for control. It is a balance of empathy, technical fluency, and imagination. As AI learns from us, the deeper challenge is to keep learning from it with intention and purpose. AI generated memes have become valuable learning assets because they translate complex ideas into simple visual cues that accelerate understanding. A well designed meme supports cognitive clarity, lowers resistance, and reinforces key concepts in ways that align naturally with Instructional Systems Design. When used with intention, meme content becomes a microlearning tool that captures attention, supports retention, and helps learners connect emotionally with the material. Instructional Systems Design becomes even more relevant when AI supports the alignment between purpose, learner, and performance. The goal is not faster production. The goal is a more thoughtful learning ecosystem where strategy guides tools, not the other way around. ▸ In Learning Strategy: AI prompts help map decisions that shape the learning experience before content is created, supporting clear outcomes and stronger alignment. ▸ In Instructional Systems Design: AI expands the designer’s reach by generating early drafts that free time for analysis, sequencing, and performance logic. ▸ In Learning Facilitation: AI generated scripts and visuals give facilitators stronger starting points for engagement while preserving their unique voice and judgment. ▸ In Content Creation: AI supports high volume without lowering quality by turning insights into structured materials ready for review and refinement. ▸ In Professional Growth: Mastery grows when technology becomes a partner in reflection, not a shortcut. The designer learns to think with the tool while staying grounded in purpose. YOUR INSIGHT MATTERS How do you see AI reshaping the way learning professionals design, facilitate, and deliver instruction in a world where attention is the new scarcity? __________ If this learning focused reflection resonated with you, keep it for future reference, share it with a colleague, like it, and follow me here on LinkedIn for more ideas on how learning strategy and ISD can strengthen training interventions.

Amazing! This is the present and the future of learning experience creation. I now have a fully working system that automatically personalizes learning based on learner data, data from the business, and learner actions. The cafe scenario based learning experience I created is supposed to mimick logging into a fake Point of Sale System (POS) and launching training alongside the POS. I created a system on the back end that pulls in data on who the cafe lead is, their store, scans multiple stores reviews to pull the matching data on their specific store reviews, generates a scenario tailored just to them with OpenAI, and sends it straight into my scenario template. The learning experience they load on their screen updates almost instantly. This means no more manually creating learning experiences for different audiences. I can now automatically create a dynamic, data driven learning experience that adapts itself the second the learner enters the system. Now that this is working, the next steps are to limit the scenarios to pull only from data in a specific time period. If current data is missing, the system will fall back to other priorities like safety goals or incidents at nearby stores that could happen here. I also need to update the visuals so the images match whatever scenario is generated or remove them when they are not needed. This is the type of system I deeply care about building. It uses learning sciences, automation, and AI to create scalable experiences that support business needs. What possibilities do you see when learning experiences can adjust immediately based on data and actions? #LearningDesign #VibeCoding #LearningSciences #GenerativeAI #AIinLearning #n8n #LearningEcosystems #EdTech #WorkplaceLearning #InstructionalDesign #PersonalizedLearning #FutureOfLearning #eLearning