Cultivating A Culture Of Learning

Kirkpatrick is often criticized. But rarely fully understood. Let's change this 👇 The model is simple. It describes four levels of evaluating learning impact: Level 1 — Reaction How participants experience the learning. Level 2 — Learning What knowledge and skills they acquire. Level 3 — Behavior How their on-the-job behavior changes. Level 4 — Results What organizational outcomes improve. That’s it. Four levels. And yet, it is frequently dismissed as outdated or simplistic. Why? Because we often treat it as a measurement checklist, instead of a design framework. Kirkpatrick is not just about evaluating training. It’s about thinking in cause-and-effect logic. Instead of asking, “Was the training good?” we should be asking a sequence of strategic questions. When designing: – What business outcome must change? – What behavior must shift to deliver that outcome? – What knowledge and skills are required? – What learning experience will enable mastery? And when evaluating: – How did participants evaluate the experience? – How well did they acquire the knowledge and skills? – How did behavior change at work? – What changed in the targeted business indicators? Planning must start from the top (Results). Measurement must begin from the bottom (Reaction). Think forward. Measure backward. Of course, the model has nuances - leading and lagging indicators, performance environment, manager accountability, isolation factors. But beneath the complexity lies a simple and powerful logic. The pyramid is not a hierarchy of surveys. It’s a chain of impact. That’s why I created this visual, to show the model not as theory, but as a practical thinking framework. How do you approach Kirkpatrick in your projects? #designforclarity #LearningAndDevelopment #InstructionalDesign #LearningStrategy #Kirkpatrick #LearningImpact #LXD #CorporateLearning

𝐌𝐲 𝐩𝐚𝐫𝐞𝐧𝐭𝐬 𝐡𝐚𝐝 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐩𝐥𝐚𝐧𝐬 𝐟𝐨𝐫 𝐦𝐞. My father, a lawyer, wanted me to follow him into law. My older sister beat me to it. And candidly, we don’t need more lawyers, at least in my family 😊 My mother worked for Bhabha Atomic Research Centre (under the Department of Atomic Energy) for years and wanted me to become a scientist like the ones she supported and worked alongside. She’d take me to work with her, and I was fascinated by the isotope facility. So I became a Chemistry major spending half my days in a lab wearing a lab coat that permanently smelled like rotten eggs (hydrogen sulfide, for those keeping score). The one class I loved: Drugs and Dyes, where we learned to synthesize things like aspirin. Making something tangible, something useful from raw materials. That’s what hooked me. Turns out, my life’s calling wasn’t the lab. But those years, from watching scientists to running my own failed experiments, shaped a few things that I have continued to build upon. Here are my 3 “𝐋𝐞𝐬𝐬𝐨𝐧𝐬 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐋𝐚𝐛” in honor of the United Nations 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐃𝐚𝐲 𝐨𝐟 𝐖𝐨𝐦𝐞𝐧 𝐚𝐧𝐝 𝐆𝐢𝐫𝐥𝐬 𝐢𝐧 𝐒𝐜𝐢𝐞𝐧𝐜𝐞. 1️⃣ 𝐏𝐫𝐨𝐠𝐫𝐞𝐬𝐬 𝐜𝐨𝐦𝐞𝐬 𝐟𝐫𝐨𝐦 𝐝𝐢𝐬𝐜𝐢𝐩𝐥𝐢𝐧𝐞𝐝 𝐞𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧. In chemistry, the first experiment never works. You don’t expect it to! You test, observe, adjust, and try again. Failure is failure, it's data. That's exactly how we approach transformation. Start small, learn fast, and scale what works. The best innovations rarely emerge from the first attempt. 2️⃣ 𝐒𝐭𝐚𝐲 𝐜𝐮𝐫𝐢𝐨𝐮𝐬 𝐥𝐨𝐧𝐠𝐞𝐫 𝐭𝐡𝐚𝐧 𝐲𝐨𝐮'𝐫𝐞 𝐜𝐨𝐦𝐟𝐨𝐫𝐭𝐚𝐛𝐥𝐞. The moment you assume you know the answer in the lab, you stop seeing what's actually happening. You miss the signal in the noise. As leaders navigating rapid change, curiosity is our competitive advantage. It keeps us from locking into the wrong solution too soon and opens doors we didn't know existed. Success requires a bottomless well of curiosity, even when it feels like everyone around you is demanding certainty. 3️⃣ 𝐁𝐫𝐞𝐚𝐤𝐭𝐡𝐫𝐨𝐮𝐠𝐡𝐬 𝐡𝐚𝐩𝐩𝐞𝐧 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐝𝐢𝐯𝐞𝐫𝐬𝐞 𝐭𝐞𝐚𝐦𝐬. In the lab, different perspectives spot different variables. Same in business. The best outcomes come from teams that see the problem from multiple angles. Diverse thinking isn’t a nice to have. It’s how you actually solve problems. To every woman and girl in STEM: stay curious, trust the process. And remember: you absolutely belong here. The future is being built and it needs your perspectives. What lessons from your early curiosity still guide you today?

*** 🚨 Discussion Piece 🚨 *** Is it Time to Move Beyond Kirkpatrick & Phillips for Measuring L&D Effectiveness? Did you know organisations spend billions on Learning & Development (L&D), yet only 10%-40% of that investment actually translates into lasting behavioral change? (Kirwan, 2024) As Brinkerhoff vividly puts it, "training today yields about an ounce of value for every pound of resources invested." 1️⃣ Limitations of Popular Models: Kirkpatrick's four-level evaluation and Phillips' ROI approach are widely used, but both neglect critical factors like learner motivation, workplace support, and learning transfer conditions. 2️⃣ Importance of Formative Evaluation: Evaluating the learning environment, individual motivations, and training design helps to significantly improve L&D outcomes, rather than simply measuring after-the-fact results. 3️⃣ A Comprehensive Evaluation Model: Kirwan proposes a holistic "learning effectiveness audit," which integrates inputs, workplace factors, and measurable outcomes, including Return on Expectations (ROE), for more practical insights. Why This Matters: Relying exclusively on traditional, outcome-focused evaluation methods may give a false sense of achievement, missing out on opportunities for meaningful improvement. Adopting a balanced, formative-summative approach could ensure that billions invested in L&D truly drive organisational success. Is your organisation still relying solely on Kirkpatrick or Phillips—or are you ready to evolve your L&D evaluation strategy?

Most L&D professionals learned the Kirkpatrick Model early on. Fewer have seen it applied beyond Level 1. Here's what each level can actually look like when you put it into practice, not just the textbook definition. ✨ Level 1: Reaction 🔹 Textbook version: Did learners find the training engaging and worth their time? ✅ In practice: Instead of "Did you enjoy this session?", ask "Was this relevant to the work you do?" and "Could you apply this right away?" ✅ Metric to track: Relevance and applicability ratings, not just satisfaction scores. ✨ Level 2: Learning 🔹 Textbook version: Did learners gain the intended knowledge or skills? ✅ In practice: Replace recall-based quizzes with scenario-based checks. Can the learner apply the concept to a situation they'd actually face? ✅ Metric to track: Pre/post assessment scores on scenario-based questions, not just "did you pass the quiz." ✨ Level 3: Behavior 🔹 Textbook version: Are learners applying what they learned on the job? ✅ In practice: 30/60/90-day check-ins, manager observations, or peer feedback on whether the new behavior is showing up in real work. ✅ Metric to track: % of participants demonstrating the target behavior, based on manager or peer input, not self-reported confidence. ✨ Level 4: Results 🔹 Textbook version: Did the training impact business outcomes? ✅ In practice: Pick one business metric the program was meant to influence, before you build it, not after, and track the change. ✅ Metric to track: Movement in that specific KPI (error rates, time-to-productivity, conversion rates, retention) compared to a baseline. Most programs are measured thoroughly at Level 1 and barely at all beyond it. But Levels 3 and 4 are where the "did this actually matter" conversation happens, and they are also where L&D earns a seat at the table. Which level does your organisation measure consistently, and which one do you wish you could measure better? #LearningAndDevelopment #LnD #KirkpatrickModel #TrainingEvaluation #InstructionalDesign #LearningMeasurement #TrainingAndDevelopment #LnDStrategy

A learning organization is one where learning is BUILT INTO how people work, solve problems, share knowledge, and improve. Many companies claim to be learning organizations, but in reality, they often confuse training with true learning. They focus on courses and workshops but neglect the daily habits that drive growth... like reflection, feedback, knowledge-sharing, and collaborative problem-solving. Sound familiar? If so... Here are some ways to move toward becoming a true learning organization: 💡 Make learning visible. Start weekly team meetings with one question: What did we learn this week? Whether it’s from success or failure, small experiments or major projects-capture it, name it, and make it part of the conversation. 📢 Encourage challenges. Let people respectfully question the way things are done. Leaders need to show that it’s not only okay to ask “why?”- it’s welcomed. This is a great approach to build into your daily Gemba Walk! ⚠️ Use problems as lessons. Don’t jump to blame when something goes wrong. Instead, ask, What can we learn from this? What will we do differently next time? Make this a habit, not a once-off response in your 1:1's and everyday interactions. 📋 Make reflection routine. At the end of a project or during quality meetings, take 10 minutes as a team to ask: What went well? What didn’t? What did we learn? What should we change? 🗣️ Share learning across teams. Too often, learning stays stuck in silos. Create simple ways to pass it on like learning libraries, book clubs or monthly learning huddles across departments. ✨ Lead by example. Leaders who regularly admit they’re still learning create a culture where learning is normal. Asking questions instead of always having the answers is a key behaviour to set the tone. Do you agree it's more important than ever to create learning organizations? Any tips on creating a learning organization? Share them below and let's chat!

Are we realising the potential of our networks to make change happen? Most innovation emerges from collaborative projects where teams openly “borrow” & adapt each other’s (often small but powerful) ideas. Many networks & communities of practice could achieve so much more by experimenting together around collective priorities to generate & share new solutions. This is beyond spreading known “best” or “good” practices. It is about innovating to design new solutions collectively. So I appreciated this piece from Ed Morrison about three different kinds of networks: - Advocacy networks are communities that seek to mobilise people, creating pressure to shift policies, priorities or messages in a particular direction. Their aim is to connect & influence rather than to change how they themselves work. - Learning networks are communities of practice. They share knowledge, compare practice & build shared capability. Learning networks often excel at spread & improvement of existing practice, but only sometimes move into structured innovation work. - Innovating (or transforming) networks are communities that combine their assets - ideas, relationships, data, capabilities - to create new value that none could produce alone. They manage collaboration as a process of experimentation: agreeing a shared outcome, running multiple connected tests of change, learning by doing & amplifying what works across the network. https://lnkd.in/edbbexiG. Every learning network has the potential to become an innovating/transforming network. Some actions to enable this: 1. Build a foundation of strong, trusting relationships within the network, understanding each member’s starting point & motivation for change 2. Focus on helping each other to succeed; listen to each others’ stories & plans, co-coach, give advice to each other & build shared inquiry 3. Move from “sharing” or “raising awareness” to some concrete outcomes the network want to change together through collective experimentation 4. Agree some simple norms for the network so that members help each other to make progress, make it safe to try things, fail fast & share incomplete work 5. Encourage multiple, parallel tests of change around similar outcome so projects can “steal with pride” from one another & quickly refine promising ideas 6. Put simple routines in place for noticing patterns (what is shifting where & why), capturing these insights & amplifying them across the network 7. Add additional success metrics including innovations tested, adapted & adopted in multiple places Graphic by Ed Morrison. Content with added inspiration from June Holley.

We're focusing on completely the wrong skills in professional development. While companies invest billions in technical training, the true performance differentiator isn't technical knowledge—it's cognitive athleticism. Think about it: Most professionals know WHAT to do. They have access to the same information, tools, and techniques as their peers. Yet some consistently outperform others by orders of magnitude. Why? Cognitive athleticism—the ability to direct, sustain, and optimize your mental capabilities. After studying high performers across fields—from chess grandmasters to hedge fund managers to surgeons—I've identified a pattern that contradicts conventional wisdom: Technical expertise gets you in the game, but cognitive skills determine who wins. Specifically: • Attentional control (focus) • Decision quality under pressure • Mental resilience • Cognitive flexibility These aren't soft skills—they're the foundation of all performance. Here's what's truly controversial: Most organizations are measuring completely the wrong metrics. They track productivity, output, and technical competencies while ignoring the cognitive fundamentals that actually determine results. It's like measuring a quarterback's uniform cleanliness instead of their passing accuracy. I've worked with teams who transformed their performance not by learning more, but by implementing systems to optimize their cognitive processes. Their metrics improved dramatically: • Decision quality up 28% • Execution consistency up 32% • Innovation capacity up 41% What if we're all working on expanding our knowledge when we should be optimizing how we use what we already know? What cognitive skill do you think creates the biggest performance edge in your field? ♻️ Repost to help others see beyond technical skills to the cognitive foundations of performance ➕ Follow me for more evidence-based approaches to professional excellence

When you align learning strategy with how the brain actually learns you'll find that performance improves. In many organisations, learning still means content delivery - I battle this challenge regularly. L&D teams measure outputs like number of courses, completions, attendance rather than outcomes. But humans don’t learn by consuming information. They learn by connecting ideas, making meaning, and putting their knowledge and skills into practice over and over again until their brains physically change. If you want to genuinely change behaviour and performance in your organisation then your whole strategy needs to be designed with the brain in mind. Here are three practical principles to share with your design and delivery teams: 🧠 Space, don’t cram Learning needs time to settle. Encourage teams to design experiences that build over time rather than delivering everything in one go. The return on retention is remarkable. 💡 Engage peoples emotions People remember what feels relevant and real. Challenge your designers to stimulate learners emotions with hooks like stories, challenges and personal connections. Don't just design pretty slides. 🔄 Practice and retrieval Learning journeys, rather than one off events, give people time to apply, reflect, and test new skills where it matters - on the job. This doesn't mean repetition for its own sake; it's simply how neural pathways are strengthened. When your learning strategy aligns with how the brain naturally works key metrics like engagement, performance and business impact improve. How do you enable your teams to bring brain science into the way they design and deliver learning?

Nothing kills motivation faster than a leader who behaves like an employee’s effort doesn’t matter. Teams receiving regular, genuine recognition are significantly more likely to stay engaged and productive than those left unacknowledged. Giving meaningful feedback rather than only criticism consistently improves performance over time. Empowerment, autonomy, and opportunity for growth strongly correlate with higher job satisfaction and better retention. 6 Leadership Moves That Actually Motivate a Team 1. Listen & Encourage Feedback Encourage open feedback and ideas, then act on them. When voices are heard and valued, people feel respected and included. This builds trust and welcomes fresh thinking. 2. Recognise Good Work Publicly Make it a habit to call out achievements. Recognition boosts morale and tells people their effort matters. Teams receiving frequent praise show far higher motivation levels. 3. Challenge for Growth With Support Give meaningful tasks and stretch goals. Push the team to learn, grow and step out of comfort zones. But stay there to support them when they need it. Growth paired with guidance fuels confidence and drive. 4. Show You See the Human, Not Just the Work Caring about the person behind the role matters. Recognise that each team member has ambitions, fears, and strengths. When leaders show empathy and humanity, loyalty and trust deepen. 5. Help Build Their Career Path Learn what they aspire to. Offer opportunities to grow, learn, or lead. Make their ambitions part of the bigger vision. When work links with personal growth, engagement and long-term commitment rise. 6. Trust, Empower and Stand Behind Them Give autonomy. Let them take ownership. Trust in their abilities. Empowerment and not micromanagement build responsibility, creativity, and ownership. Employees grow stronger when they’re heard, valued, supported, trusted and empowered. Agree?

The shift toward #onlinelearning is enhancing #highered's ability to meet all students where they are. But much work still remains to educate all relevant stakeholders—including policymakers, institutional leaders, and even students’ families—about the potential benefits tech-enabled learning can yield. As the president of Western Governors University, I recognize the unique role I can play in elevating this discussion. Today, both innovative online universities and established brick-and-mortar institutions are leveraging technology to provide students with greater flexibility and personal ownership over their experience; recently it was reported that 70% of college students are enrolled in at least one online course. But offering online courses or even programs doesn’t necessarily mean an institution is fully capitalizing on technology’s potential. As with any innovation, its potential rests in how it’s deployed. Unfortunately, online learning is often deployed with the same artificial constraints that exist in traditional models of learning, ensuring its impact will be limited. (It's been said before, but I'll say it again: delivering lectures via Zoom is not quality online learning). In stark contrast, effective online learning design should be purposefully designed for the virtual environment, leveraging digital tools and approaches that would be difficult to replicate in-person, at scale. Thanks to advances in technology, for instance, readily available data on how students are doing can empower faculty to reach out to students in need—and critically before they fall too far behind and get discouraged. At WGU, we use machine intelligence to better understand our students’ momentum at a given moment, drawing on indicators such as how they’re interacting with learning resources, the extent to which they’re engaging with faculty, and how they’re progressing. By identifying when students have less momentum and are in greater need of support, our faculty are empowered to design personalized interventions when students need them the most, which we’ve shown improves retention and progression. Compiling this sophisticated level of actionable information simply would not be possible without the support of technology. I’d love to know—how else are you seeing online learning deployed deliberately and effectively?