Developing Training for New Technologies

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 And yet, it is frequently dismissed as outdated or simplistic.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

How to Actually Get Experience in Cybersecurity I see a lot of advice on how to “get hands-on experience” in cybersecurity, especially for those struggling to land their first role. People say: ➡ Configure a firewall ➡ Analyze network traffic with Wireshark ➡ Set up a SIEM ➡ Do penetration testing All great advice. But here’s the issue—most of these lack context and applicability. You’re not just going to walk into an organization and start configuring firewalls or setting up security tools randomly. Security in the real world doesn’t work like that. The Missing Piece: Organizational Context It’s not just about what you’re doing; it’s about why you’re doing it. For example, instead of simply “configuring a firewall,” ask: - What specific threats are we trying to mitigate? - What business needs or compliance requirements are influencing firewall rules? - How does this fit into the organization’s overall security strategy? This is why case study-based project learning is more valuable than just running through random technical tasks. Instead of just “configuring a firewall,” imagine this: Company X suffered a recent ransomware attack that led to unauthorized access. Your task: Improve their security posture using network segmentation and firewall rules. Now you’re thinking like a cybersecurity professional. You’re not just configuring a firewall—you’re implementing a security control based on a real-world scenario. Cybersecurity is not just about doing technical tasks alone—it’s about solving real security problems. In a different post I'll talk about how to gain practical and contextual experience. Share this to your network so others can learn #CybersecurityCareerGrowth #Cybersecurity

Not all soft skills training is created equal. A few months ago, I was working with a group of managers from a large manufacturing company. They had been through plenty of training programs before- the kind where you take notes and then go right back to doing things the old way. When I walked into the room, I could see it in their faces: Let’s see if this is any different. So instead of starting with slides or theory, I took them straight into a live simulation: - A crisis scenario that could actually happen in their business. - Conflicting priorities, tough personalities, and limited time to decide. - Every move they made in real time had visible consequences. To begin with, I saw a lot of resistance in experimentation, voices which were not too loud and over powering were ignored leading to loss of critical information- the room was tense. People hesitated. Some stuck to their usual patterns. But as it got deeper, they started communicating much more effectively, this led to them collaborating, noticing blind spots, and eventually testing new ways to lead. By the end, they weren’t asking- Will this work? They said that they wanted to cascade it to their teams. Weeks later, I got an email from one of the managers. He told me he used the exact process from our simulation to navigate a real customer crisis and not only avoided a major fallout, but actually strengthened the client relationship through this crisis. That’s the difference between training that’s forgotten by the time you’re back at your desk, and training that rewires how you think, act, and lead. The secret? Immersion. When participants practice real scenarios, solve actual challenges, and see the impact of their decisions in the room, learning sticks. Priya Arora #immersivelearning #trainingdesign #employeeengagement #learningthatsticks #corporatelearning #leadershipdevelopment #upskilling #skillbuilding #workplacetraining #experientiallearning #Learningdeisgn #corporatetrainer #softskillstrainer #simulation #experintialtraining

🎓 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

Most training programs create excitement. Very few create measurable business impact. A few months ago, I worked with an organization that had a very specific challenge. Their frontline teams were attending workshops, feeling motivated, taking notes but when it came to actual performance on the field, their sales conversion was very low. Great energy. Poor execution. Something was missing. So before designing the learning intervention, I asked one simple question: “What’s the real context in which your people operate daily?” Not the role. Not the job description. Not the competencies. The context. What pressures do they face? What conversations are toughest? Where do deals collapse? Who influences decisions? What behaviours matter most on the ground? The organization opened up. We mapped real scenarios. We shadowed calls. We watched interactions. We decoded customer psychology. We understood the reality behind the numbers. Only then did we build the training journey. Not generic content. Not textbook concepts. Not motivational theory. But a program designed exactly around their on-ground realities. The impact. Over the next eight weeks, something changed. Sales conversations became sharper. Objections were handled with more confidence. Teams spoke value, not price. Managers reinforced learning consistently. The conversion saw a huge jump and this was created not by more training, but by the right training. The lesson is simple: Content informs. Context transforms. Workshops don’t create results. Relevance does. When learning mirrors the real world, people don’t just listen they apply. When they apply, organizations grow. What’s one area in your team where you feel content is high but context is missing? If your organization wants training that delivers real, measurable outcomes let’s talk.

Burning out an servo amplifier hurts. Both financially and professionally. You can have perfect ladder logic, but you can’t cheat physics. In Motion Control, an error rarely ends with a simple red "Error" LED. It usually ends with a bang. So, how do you master drives and encoders without risking the demo gear? Forget "trial and error" on live machinery. Leverage the software you already have: ➡️ Simulation is more than just logic. Many engineers use the simulator only to test bits. Big mistake. In the MELSOFT environment, you can simulate the entire axis behavior. Watch the Current Feedback during hard braking. A virtual collision costs $0. ➡️ Trace Monitor is your eyes. Stop guessing why the motor is "buzzing." Fire up the built-in oscilloscope. If you can’t read a Speed vs. Torque graph, you aren’t controlling the machine - you’re just hoping it works. ➡️ Start with the Compact PLC. You don’t need a massive PLC cabinet to learn. The Compact PLC comes with built in positioning features. Master ramps, Jerk, and Homing on your desk, in a safe micro-scale. A pro engineer doesn’t pray for the machine to run. They KNOW it will run because they verified it before plugging in the CC-Link IE TSN cable. 👇 Team "Adrenaline & Live Testing" or Team "Simulation First"? Let me know in the comments.

50 Days of XR – Day 50: When VR Training Looks Like the Real Thing One question often comes up when discussing VR training: "How realistic can it actually be?" This comparison between a B767F cargo aircraft door operation in VR and the same procedure in real life provides a compelling answer. Platforms like AVIAR are helping aviation and logistics organizations train personnel on complex operational procedures in a safe, repeatable, and scalable environment. Companies such as DHL are already leveraging these types of immersive training solutions to prepare teams responsible for servicing large cargo fleets. What makes XR valuable here isn't just realism. It's the ability to: 1. Practice procedures repeatedly without operational downtime 2. Train safely before working on real equipment 3. Standardize training across distributed teams The closer a simulation gets to reality, the more effective the learning experience becomes. This is another example of XR delivering measurable value beyond the headset. Reference link in comments. That's a wrap on 50 Days of XR. Thank you to everyone who followed, engaged, and shared insights along the way. More XR content coming soon. #VirtualReality #XR #SimulationTraining #AviationTech #ImmersiveLearning #DigitalTransformation #EnterpriseXR #FutureOfWork #Innovation #Logistics #AviationTraining #WorkforceDevelopment #VRTraining

A new study examining the long-run effects of the One Laptop per Child program in rural #Peru provides important evidence for digital education policy. The program substantially increased students’ computer skills over time, but it did not translate into measurable improvements in academic achievement, school completion, or later educational transitions. The results underline a central consideration for digital transformation agendas: access to devices on its own is unlikely to generate sustained learning gains. Effective integration of technology requires complementary investments in teacher training, pedagogical support, and curriculum alignment. As countries expand digital initiatives, it is important to consider how technology can be leveraged more strategically to strengthen teaching and learning. Full study here: https://lnkd.in/eV-_73z7 National Bureau of Economic Research Santiago Cueto Caballero Diether Beuermann Julian Cristia Ofer Malamud  Francisco Pardo Pajuelo Sonia Suarez Enciso Gabriela Gambi Elena Arias Ortiz

There’s a reason training impact feels so hard to measure. It’s not because impact isn’t there. It’s because we look for it at the wrong time. Training impact doesn’t show up all at once. It unfolds in stages. Right after training, you won’t see behavior change yet. But you can see early signals: Do people understand it? Do they feel confident applying it? Do they see why it matters? These signals don’t prove impact. But they predict whether it’s even possible. A few weeks later, different things become visible: Early application Intent to use Where people get stuck This is where learning starts to show up at work. Months later, real change follows: Behavior shifts Adoption increases New habits form And only much later does it make sense to ask: Did this improve performance? Did it move the business? Was there ROI? Most training is evaluated far too early to see business impact. Good evaluation is about measuring the right things at the right time.

✈️ From PowerPoints to Simulations: How #Accenture and KLM Cargo Are Redefining Technical Trainings for Engineers with Mixed Reality. Several technologies, like AI and spatial computing, are converging now to transform how we use data in engineering: - AI now enables us to 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲, 𝗮𝗻𝗮𝗹𝘆𝘇𝗲 𝗮𝗻𝗱 𝗰𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹𝗶𝘇𝗲 large amount of data, previously reduced to 2D drawings, integrating it seamlessly into the entire product lifecycle - And Mixed Reality brings this data 𝘁𝗼 𝘁𝗵𝗲 𝗽𝗹𝗮𝗰𝗲𝘀 𝘄𝗵𝗲𝗿𝗲 𝗶𝘁'𝘀 𝗻𝗲𝗲𝗱𝗲𝗱, allowing us to simulate rare or dangerous scenarios more efficiently and safely. At Accenture, we work daily on use cases that involve multimodal models to analyze technical drawings, plans, and parts - but I'm excited by the tangible results we’re achieving with KLM in Engineering & Maintenance (E&M). Together, we’re transforming traditional training—replacing PowerPoint and manuals with interactive spatial models via mixed reality. In the video, you see the process of 𝗿𝗲𝗺𝗼𝘃𝗶𝗻𝗴 𝗮𝗻𝗱 𝗶𝗻𝘀𝘁𝗮𝗹𝗹𝗶𝗻𝗴 𝗮 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗮𝗶𝗿𝗰𝗿𝗮𝗳𝘁 called a "Variable Frequency Starter Generator" (VFSG), which usually takes a lot of steps and requires the mechanic to 𝗹𝗼𝗼𝗸 𝗮𝘁 𝗮 𝗺𝗮𝗻𝘂𝗮𝗹 often. 𝗪𝗵𝗮𝘁 𝘂𝘀𝗲𝗱 𝘁𝗼 𝘁𝗮𝗸𝗲 𝟰𝟱 minutes to explain can now be demonstrated 𝗶𝗻 𝘂𝗻𝗱𝗲𝗿 𝟯 𝗺𝗶𝗻𝘂𝘁𝗲𝘀, in one environment 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗮 𝘃𝗮𝗿𝗶𝗲𝘁𝘆 𝗼𝗳 𝗳𝗶𝗹𝗲𝘀, 𝗱𝗿𝗮𝘄𝗶𝗻𝗴𝘀, 𝗮𝗻𝗱 𝘃𝗶𝗱𝗲𝗼𝘀. Mechanics can view and interact with parts and manuals in real time, leading to faster, more effective training. Building on the success of this initial experiment, KLM Cargo and Accenture developed a simulation of the 𝗲𝗻𝘁𝗶𝗿𝗲 𝗰𝗮𝗿𝗴𝗼 𝗽𝗮𝗰𝗸𝗶𝗻𝗴 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 using Microsoft #HoloLenses. As AI and spatial computing converge, we’re paving the way for more efficient and accessible processes in complex fields like product engineering. with Jakob Albrecht, Thomas Reisenweber, Lucas Kempe, Ludwig Markwardt, Nick Rosa, FRSA, Maximilian Linner, Seroj de Graaf and many others. Accenture DACH