New Learning Impulses

For a long time I felt that if we wanted to answer questions such as ‘how do we design learning experiences?’, ‘how do we measure learning?’, ‘what is our pedagogy based on?’ - or even just explain to stakeholders what it is that we do - then it would help to have an understanding of learning. Thanks again to Ben Gallacher and the #Inrehearsal team for creating this series. #learning #pedagogy #learningdesign #education #training

'You can’t accomplish anything if your stakeholders aren’t on board.' After delivering hundreds of Human Centred Design (5Di©) workshops, ‘Stakeholders’ is one of the topics that comes up time & time again: L&D want to do one thing, the business another. What’s required is a consultative approach rather than an adversarial one - partnering not pushback. In response, I added new resources into the latest version version of the 5Di© toolkit released a few months back (https://lnkd.in/eacUSAbc) - here are a couple of them: #learning #education #consulting #learninganddevelopment #HR #stakeholders | 11 comments on LinkedIn

𝗙𝘂𝘁𝘂𝗿𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: 𝗪𝗮𝘀 𝘄𝗶𝗿𝗱 𝗮𝘂𝘀 𝗱𝗲𝗿 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗲𝗻𝘁𝘄𝗶𝗰𝗸𝗹𝘂𝗻𝗴? In der aktuellen Wirtschaftswoche (1) plädieren Julian Kirchherr und Cawa Younosi für „NO HR“, d. h. die Abschaffung des gesamten Personalbereiches mithilfe Generativer KI und die Rückverlagerung von HR-Aufgaben ins Management. Alles, was besonders viel Fingerspitzengefühl verlangt, insbesondere die Entwicklung ihrer Mitarbeitenden, gehört danach in die Verantwortung der Führungskräfte. Routinetätigkeiten wie das Erstellen von Arbeitsverträgen, Schulungszertifikaten oder die erste Sichtung von Bewerbungen übernimmt die Maschine. Ihre Hauptargumente sind:  • Die Führungskräfte sollen Personalaufgaben direkt verantworten, um eine engere Verknüpfung der strategischen Unternehmensziele mit dem Personalmanagement zu erreichen.   • Traditionelle HR-Abteilungen sollten in ihren Strukturen überdacht oder sogar abgeschafft werden, um mehr Agilität zu ermöglichen. Nicht nur administrative Aufgaben wie Arbeitsverträge, werden automatisiert, auch Arbeitszeugnisse oder Umfragen werden mit Hilfe der KI bearbeitet. Was auf den ersten Blick sehr radikal wirkt, beinhaltet aus meiner Sicht diskussionswürdige Aspekte. Mit diesem Vorschlag rücken viele Aufgaben wieder dorthin, wo sie eigentlich schon immer hingehörten, zur Führungskraft. Zu ihrer Verantwortung rechnen danach Onboarding, Nachfolgeplanung oder die gezielte Skillsentwicklung im Team sowie Fragen von Kultur und Transformation. Sie entwickeln sich zu „𝗣𝗲𝗼𝗽𝗹𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗿*𝗶𝗻𝗻𝗲𝗻“. Ich bin der Überzeugung, dass weiterhin eine HR-Funktion benötigt wird, aber mit relativ wenigen, hoch spezialisierten Expert*innen, z. B. für die mittelfristige Personalbedarfsplanung und insbesondere für 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁. Im Future Learning stehen nämlich die Mitarbeitenden im Mittelpunkt, die mit Unterstützung der KI selbst ihre Lernpfade planen und im Arbeitsprozess umsetzen. Ihre Führungskräfte werden deshalb zu ihren Entwicklungspartner*innen, die ihre personalisierten Lernpfade ermöglichen. Die Personalentwicklung wandelt sich folglich zum 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝘀𝗰𝗵𝗲𝗻 𝗟𝗲𝗿𝗻𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗸𝘁𝗲𝗻, zu 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁. Diese baut und optimiert laufend das "Lernhaus" als Ermöglichungsraum für selbstorganisiertes Lernen im Dialog mit der generativen KI , begleitet Lernprojekte sowie die notwendigen Veränderungsprozesse und evaluiert den Lernerfolg. 𝗟&𝗗 𝘄𝗶𝗿𝗱 𝗱𝗮𝗺𝗶𝘁 𝘇𝘂𝗿 𝘇𝗲𝗻𝘁𝗿𝗮𝗹𝗲𝗻 𝗨𝗺𝘀𝗲𝘁𝘇𝗲𝗿𝗶𝗻 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝘀𝗰𝗵𝗲𝗿 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻. Daraus ergibt sich folgende Rollenverteilung im Future Learning. (1) https://lnkd.in/eiupSJae

Nichts vergessen und alles schnell finden: Seit einigen Monaten nutze ich ein einfaches System, um wichtige Daten und Informationen aus meinem Leben besser zu speichern und zu organisieren. So funktioniert es.

Sie möchten Ihre L&D-Karriere vorantreiben? Diese Auswahl an Fachressourcen bringt Sie auf den richtigen Weg.

„Nicht wer du bist, sondern was du kannst, entscheidet über deine Rolle.“ – Ein Paradigmenwechsel, der gerade dabei ist, unsere Arbeitswelt auf den Kopf zu s...

But Google is not representative of most companies. Not even of tech companies. They can (and should!) be AI-first in every respect—yesterday. Virtually all other companies will take a slower approach, maintaining their learning content and systems, for now. So don’t think you need to drop everything immediately. Instead, work out what a more measured approach looks like for your organisation. Think about how you’re preparing your data, metadata, internal and external content—and your people—for this not-so-distant future when agents are doing more and more of the work, multiplying productivity. Help your company lead the way—don’t await instructions! That said, I think most three-year horizons will include the other big pull quote from this piece: Google will “focus on teaching employees how to use modern artificial intelligence tools in their daily work routines.” That, I believe, is where the most worthy—and therefore sustainable—L&D efforts lie: not in creating courses and force-feeding them to people, but in enabling people to work better with AI. ♻️ Please REPOST if people you’re connected to may like this. ➕ Follow Marc Zao-Sanders for more of this kind of thing. #AI #learning #filtered.com #acelo.ai https://lnkd.in/ehA2pB_R ps: I'm working fractionally for both acelo.ai (sales x AI) and filtered.com (learning content x AI). If you're interested in talking about either, DM me)

An Introduction to Training from the Back of the Room (TBR) where we use brain-based accelerated learning to create engaging fun learning experiences.Trainin...

404: Bildung not found - Wie Lernen wieder berühren kannSchule soll aufs Leben vorbereiten. Einige fordern mehr Wissen über Steuern und Finanzen, KI liefert ...

B𝘦𝘵𝘳𝘪𝘦𝘣𝘭𝘪𝘤𝘩𝘦𝘴 𝘓𝘦𝘳𝘯𝘦𝘯 𝘨𝘪𝘯𝘨 𝘣𝘪𝘴𝘩𝘦𝘳 𝘷𝘰𝘯 𝘧𝘰𝘭𝘨𝘦𝘯𝘥𝘦𝘯 𝘗𝘳𝘢𝘮𝘪𝘴𝘴𝘦𝘯 𝘢𝘶𝘴: • 𝘞𝘪𝘴𝘴𝘦𝘯𝘴- 𝘶𝘯𝘥 𝘘𝘶𝘢𝘭𝘪𝘧𝘪𝘬𝘢𝘵𝘪𝘰𝘯𝘴𝘻𝘪𝘦𝘭𝘦 𝘴𝘪𝘯𝘥 𝘧𝘶𝘳 𝘢𝘭𝘭𝘦 𝘨𝘭𝘦𝘪𝘤𝘩 𝘪𝘯 𝘦𝘪𝘯𝘦𝘮 𝘊𝘶𝘳𝘳𝘪𝘤𝘶𝘭𝘶𝘮 𝘷𝘰𝘳𝘨𝘦𝘨𝘦𝘣𝘦𝘯.  • 𝘋𝘪𝘦𝘴𝘦 𝘡𝘪𝘦𝘭𝘦 𝘸𝘦𝘳𝘥𝘦𝘯 𝘪𝘯 𝘧𝘳𝘦𝘮𝘥𝘰𝘳𝘨𝘢𝘯𝘪𝘴𝘪𝘦𝘳𝘵𝘦𝘯 𝘓𝘦𝘩𝘳𝘢𝘳𝘳𝘢𝘯𝘨𝘦𝘮𝘦𝘯𝘵𝘴 „𝘷𝘦𝘳𝘮𝘪𝘵𝘵𝘦𝘭𝘵“.  • 𝘋𝘪𝘦 𝘈𝘶𝘧𝘣𝘢𝘶 𝘥𝘦𝘳 𝘏𝘢𝘯𝘥𝘭𝘶𝘯𝘨𝘴𝘧𝘢𝘩𝘪𝘨𝘬𝘦𝘪𝘵 𝘪𝘯 𝘥𝘦𝘳 𝘗𝘳𝘢𝘹𝘪𝘴 (𝘒𝘰𝘮𝘱𝘦𝘵𝘦𝘯𝘻𝘦𝘯) 𝘸𝘪𝘳𝘥 𝘥𝘶𝘳𝘤𝘩 𝘛𝘳𝘢𝘯𝘴𝘧𝘦𝘳𝘢𝘶𝘧𝘨𝘢𝘣𝘦𝘯 𝘨𝘦𝘴𝘪𝘤𝘩𝘦𝘳𝘵. Wir erleben aktuell, verstärkt durch die Künstliche Intelligenz, einen Paradigmenwechsel, der diese betriebliche Didaktik auf den Kopf stellt:  • Formelle Bildungsangebote auf Basis von Curricula werden nach und nach durch „𝗙𝗹𝗶𝗽𝗽𝗲𝗱 𝗖𝘂𝗿𝗿𝗶𝗰𝘂𝗹𝗮“ (vgl. Sabine Seufert 2024) ersetzt. Danach bilden Werte und Kompetenzen – Soft Skills – die Ziele des Corporate Learning. Wissen und Qualifikation sind natürlich weiterhin notwendig, sind aber nicht mehr das Ziel des Lernens, sondern die notwendige Voraussetzung. Dies bedeutet, dass das erforderliche Wissen beispielsweise auch kuratiert durch die KI zur Verfügung gestellt werden kann.  • Der wichtigste Lernort wird der 𝗔𝗿𝗯𝗲𝗶𝘁𝘀𝗽𝗿𝗼𝘇𝗲𝘀𝘀, weil Werte und Kompetenzen nur selbstorganisiert bei der Bewältigung von realen Herausforderungen aufgebaut werden können. Daraus ergibt sich folgender Planungsrythmus. 1. Am Anfang steht die Frage, in welcher 𝗣𝗿𝗮𝘅𝗶𝘀𝗵𝗲𝗿𝗮𝘂𝘀𝗳𝗼𝗿𝗱𝗲𝗿𝘂𝗻𝗴 die angestrebten Soft-Skills aufgebaut werden können. In Abstimmung mit ihren Führungskräften vereinbaren die Mitarbeitenden auf Basis ihrer Skills Diagnostik personalisierte Lernpfade im Arbeitsprozess.   2. Im zweiten Schritt ist zu klären, welche 𝗙𝗹𝗮𝗻𝗸𝗶𝗲𝗿𝘂𝗻𝗴 die selbstorganisierten Lernprozesse der Mitarbeitenden benötigen. Dabei spielt das soziale Lernen eine zentrale Rolle. Begleitet werden diese Prozesse durch die Beratung und Begleitung durch Lernbegleitende und Expert*innen.  3. Erst im dritten Schritt werden diese Lernmaßnahmen bei Bedarf durch 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴𝘀 ergänzt. Beispielsweise bieten sich Methodentrainings, z. B. zu SCRUM, an, wenn die ausgewählten Praxisaufgaben nach agilen Prinzipien erfolgen sollen.   4. In unterstützenden 𝗪𝗲𝗶𝘁𝗲𝗿𝗯𝗶𝗹𝗱𝘂𝗻𝗴𝘀𝗺𝗮ß𝗻𝗮𝗵𝗺𝗲𝗻 können Basiswissen und Grundqualifikationen aufgebaut oder Anstöße für die selbstorganisierten Lernprozess gegeben werden. Lernen erfolgt von Anfang an in der Praxis, indem Arbeiten und Lernen zusammenwachsen. Damit erübrigen sich Konzepte zur Förderung des Lerntransfers weitgehend. Die Verantwortung für das Lernen wandert damit zu den Mitarbeitenden, die dabei von der Personalentwicklung und Ihrer Führungskraft unterstützt werden.

-- Task criticality and risk are central considerations in performance support design. When there's high consequence for error (safety risks, costly damage, or life-or-death stakes) the skill guide design needs to be highly intentional, context-aware, and tightly integrated into the environment of use. -- A skill guide is great in high-risk situations (we were in an airline context). In a low-stakes context a pre-flight checklist is great for trained pilots. It supports memory recall for the essential steps in a high-risk task. -- In a context such as de-icing a plane, a diagram-based skill guide is great to illustrate the basic controls of the machine. This helps build mental models. -- In flight simulation training, skill guides can walk a novice through tasks like starting the engine, adjusting trim, or responding to a warning light. These guides scaffold learning and reduce cognitive load in a controlled environment. -- Of course, skill guides can't always replace training. Real-time control of a plane requires deeply embodied skill: fine motor control, situational awareness, and rapid decision-making. You can't guide someone through that just in time with a single page or even a tablet-based tool. -- In life-critical systems, there’s a threshold beyond which skill guides must give way to rigorous training, simulation, and certification. Performance support becomes a supplement, not a substitute in these contexts. Bob and Con have had immeasurable impact on my career and perspective when it comes to human performance. I even asked Bob to write the foreword of my most recent book. Their 5 Moments of Need framework enables direct alignment to real-time needs of workers. The moments of need are: 1. New (When learning something for the first time) 2. More (When there's a need to deepen or expand knowledge or skills) 3. Apply (When performing a task or applying knowledge in real situations) 4. Solve (When encountering a problem or unexpected challenge) 5. Change (When adapting to change such as a new process, tool, or an organizational shift) When learning is designed against these moments of need, job performance not only becomes more effective, but the worker gets more done quicker and with minimal disruption and frustration. By addressing these moments effectively, you can optimize learning outcomes and drive tangible results.

Welche Interventionen können menschliches Verhalten wirksam verändern? Die Meta-Analyse von Albarracín et al. (2024) ist eine Meta-Analysen von Meta-Analysen. 147 Meta-Analysen wurden zusammengefasst. Krass. Das Paper ist 106 Seiten lang und ein echtes Brett. Die Kolleg:innen haben über viele verschiedene Bereiche (z. B. Gesundheits- und Organisationsverhalten) hinweg untersucht, was das Verhalten von Menschen verändern kann. Die Ergebnisse zeigen meiner Interpretation nach: - es gibt keinen Interventionsbereich mit starken Effekten. Wir müssen demütig bleiben. Das Verhalten von Menschen zu beeinflussen, bleibt schwierig. Vielleicht ist das auch gut so. - es existieren sowohl strukturelle als auch individuelle Interventionen, die erfolgreich sind. Mit einem Fokus auf nur "structure first" oder nur "people first" verschenkt man viel Potential. - Menschen mit Wissen zu versorgen und hoffen, dass sie durch Einsicht ihr Verhalten verändern, bringt eher nichts. - Sanktionen zeigen ebenfalls zu vernachlässigende Effekte - nahezu keinen Verhaltenseffekt haben im Schnitt auch Mindsetinterventionen (beliefs) - mittelstarke Effekte zeigt die Bereitstellung des Zugangs zu Ressourcen, die für das Zielverhalten wichtig sind - auch wirksam sind Interventionen, die auf Gewohnheiten abzielen. Also solche, die Verhaltensgewohnheiten etablieren oder sie verändern. - zumindest kleine Effekte bieten soziale Unterstützung, soziale Normen, Verhaltenstrainings und die Arbeit an und mit Emotionen. Das sind natürlich "nur" Mittlerwerte von Mittelwerten aber das Studienfundament ist echt der Hammer. Was könnte das für die Verhaltensveränderungen in Organisationen bedeuten? Gebt den Menschen Zugang zu Ressourcen und unterstützt sie bei Veränderungen. Versucht an den Gewohnheiten zu arbeiten und trainiert Verhalten statt Wissen. Da vieles ein bisschen wirkt, braucht man wohl viele unterschiedliche Ansätze, um größere Effekte zu erreichen. Die immer wieder gestellte Frage Mensch oder Organisation ist nicht zielführend. Strukturen und Menschen gehören gemeinsam gedacht und bearbeitet. Die Studie ist frei verfügbar. Bei Interesse und Nachfragen gerne mal in die Studie reinschauen. Albarracín, D., Fayaz-Farkhad, B., & Granados Samayoa, J. A. (2024). Determinants of behaviour and their efficacy as targets of behavioural change interventions. Nature Reviews Psychology, 3(6), 377-392. #Verhalten #Macht #Transformation #Entwicklung | 175 Kommentare auf LinkedIn

Erfahrungswerte aus der aktuellen MIT Sloan Management Review (Bahnhofsbuchhandel). „Gehe langsam, wenn Du es eilig hast.“ Diese Erkenntnis war es, die zwei weltbekannte dänische Unternehmen – LEGO und VELUX (Dachfenster) – dazu brachte, ihren Umgang mit Veränderung zu überdenken. Inmitten digitaler Umbrüche und wachsender Komplexität stießen beide an die Grenzen ihres bisherigen Erfolgsmodells: Was früher als effizient galt, erwies sich plötzlich als zu starr und zu oberflächlich. Workshops sind oft Strohfeuer. Externe Berater kamen und gingen. Also die Erkenntnis: Veränderung muss von innen kommen – durch Führung. LEGO und VELUX machten etwas Ungewöhnliches: Sie bildeten ihre Führungskräfte nicht zu besseren Projektmanagern aus, sondern zu besseren Frage-Stellern. Sie machten sie zu Coaches. Zu Lernbegleitern ihrer eigenen Mitarbeitenden. Zu Menschen, die nicht mit Antworten glänzen, sondern mit klugen Fragen Orientierung geben. ⸻ Element 1: Probleme neu denken – mit A3 Beide Unternehmen führten die A3-Methode von Toyota ein – ein strukturiertes Denkformat, das ein Problem auf einer einzigen DIN-A3-Seite abbildet. Klar. Visuell. Jeder arbeitet damit. Das dazugehörige Modell: 🍍 Finding: Das richtige Problem entdecken. 🍍 Facing: Sich ihm mutig stellen. 🍍 Framing: Die eigentliche Herausforderung erkennen. 🍍 Forming: Lösungen entwickeln. Diese vier Phasen führten zu einem neuen Problembewusstsein: Nicht Symptome bekämpfen. Ursachen verstehen. Nicht sofort handeln. Erst gemeinsam denken. Teams lernten langsamer und nachhaltiger. ⸻ Element 2: Lernen im Kollektiv – Gruppen-Coaching als Mikrokosmos Individuelles Lernen reicht nicht. Also bauten LEGO und VELUX einen Raum für kollektive Reflexion: Gruppencoaching. Dort trafen sich Teams aus Führungskräften in festen Rollen: ein Moderator, eine Fallgeberin, ein Coach und stille Beobachter. In 30 Minuten wurde ein reales Problem durchdacht – mit klugen Fragen, ehrlichen Perspektiven, geteilten Einsichten. Diese Sessions stärkten nicht nur die Problemlösefähigkeiten – sie schufen psychologische Sicherheit. Menschen konnten sich verletzlich zeigen. Fehler besprechen. Ideen testen. Und gemeinsam wachsen. ⸻ Element 3: Coaching-Hierarchie – Lernen strukturell verankern Um all das nachhaltig zu machen, entwickelten beide Unternehmen eine dreistufige Coaching-Struktur: 🍓 First Coach: Die direkte Führungskraft begleitet das tägliche Lernen. 🍓 Second Coach: Bereichsleiter coachen die Coaches – und verbessern deren Fragekompetenz. 🍓 Third Coach: Das Top-Management reflektiert die Metaebene und sichert strategische Ausrichtung. So wurde Innovation nicht zur Aufgabe von Externen, sondern zur DNA der Organisation. Lernen wurde nicht delegiert – sondern verkörpert. Erfordert erst Zeit und Geduld, zahlt sich langfristig jedoch aus. | 96 Kommentare auf LinkedIn

“In times of change, the learners inherit the earth, while the learned find themselves beautifully equipped for a world that no longer exists.” – Eric Hoffer In a world of swirling uncertainty, waiting for perfect information is the fastest path to irrelevance.

Are you optimizing for learning, or just chasing certainty? In today’s world, waiting for perfect information is the fastest way to fall behind. True leadership isn’t about always having the answers; it’s about building teams and systems that learn faster than the world changes. In this latest post (Part 2 of 3), I explore why learning, not knowing, is the real driver of performance. Neuroscience shows that in uncertain times, our ability to adapt and learn together is what sets successful organizations apart. How does your organization balance “doing” and “learning”? Are you cultivating a culture where learning is the soil, not just a one-off event? I’d love to hear your experiences and strategies in the comments! Let’s build a conversation around how we can all adapt, grow, and thrive in uncertainty. #Leadership #OrganizationalLearning #ContinuousImprovement #ChangeManagement #FutureOfWork #LearningCulture #Adaptability #HumanCorps | 19 comments on LinkedIn

We used to rely on each other, but then it went a bit sour. Or did it? AI has helped ramp that up too. The context of work ie hybrid and remote has also driven the need for providing digital learning solutions. So what happened to face to face training? It was the staple of L&D pre-Covid but now it is hardly talked about. Have you seen articles or conference sessions on the topic? Latest research from Hemsley Fraser suggests the in-person training is far from forgotten. Indeed, it is the number one learning approach, according to its survey of 822 L&D, HR and talent practitioners, followed by coaching and virtual instructor-led training. The research shows that there has been a 17% year on year growth in in-person training in the US. According to the research, the learning approaches used by L&D are: ⦿ In-person training 87% ⦿ Coaching 62% ⦿ Virtual instructor-led training 60% ⦿ Free online resources 56% ⦿ Learning hub/portal 54% ⦿ Blended learning 51% The report authors say, "When L&D is expected to not only grow skills but boost engagement and experiences, coming together, when structured effectively, can simply make people feel good. It becomes a strategic tool with benefits beyond training alone." This sentiment is reflected in the latest Fosway Group 9-Grid for Digital Learning. One of its trends is titled "The desire to learn together gains momentum". The report, says: "Amongst all this talk of AI, the desire to actually learn together (with other people) remains, arguably, valued more highly. The need for learning solutions for high-value or large-scale transformation programmes is enduring. The best solutions bring cohorts to learn and work together over time. And maybe unsurprisingly, live events are still an important part of the desired blend, as well as virtual and hybrid approaches, led by experts that can interact in real time with their audience. In-group facilitation and collaboration is another core capability." So what is the reality for L&D teams? Is in-person training evolving to find its place alongside learning technology? And is the in-person experience evolving away from content delivery to focus on the value of people being together, sharing and working and learning collaboratively? 🔗 Read the Hemsley Fraser Learning & Development Impact Survey 2025 https://lnkd.in/e33fuTp2 🔗 Read the 2025 Fosway 9-Grid for Digital Learning https://lnkd.in/ebAbqd_x Picture credit: ElisaRiva https://lnkd.in/epFrUtXd #learninganddevelopment #research | 23 comments on LinkedIn

Didaktische Schieberegler der ISH Manufaktur

In diesem Experiment reagiere ich auf Josh Bersins Impuls "The Revolution in Corporate Learning begins" und reflektiere, wie diese Themen auf unsere Realität...

No, you're not a "visual learner." Or an "auditory learner." Or a "kinesthetic-scent-triggered-by-smooth-jazz" learner. You’re a brain — and brains don’t work like that. There’s zero scientific evidence that teaching people in their so-called “preferred learning style” helps them learn better. In fact, it often hurts by giving people permission to avoid the real work of processing knowledge deeply, by engaging in an objectively more appropriate exercise for the topic at hand. Don’t get me wrong — personalized learning is still awesome. But that just means adjusting the difficulty, pacing, or topic sequence to how well you know something — not whether you "like" podcasts better than diagrams. What most people call “learning styles” are really just learning preferences. Sure, someone might like to watch a video instead of doing flashcards — but that doesn’t mean it’s the better learning experience. In fact, the easier or more “comfortable” something feels… the less likely it is to stick. Real learning = effortful. Uncomfortable. Active. Often annoyingly repetitive. And unfortunately, not optimized around your vibes. So let’s keep pushing for personalized learning that works — based on science, not zodiac signs. #LearningScience #EdTech #CognitivePsychology #Brainscape | 110 comments on LinkedIn

We are excited to announce the general availability of People Skills, a powerful new data layer in Microsoft 365 Copilot, Microsoft 365 and the Viva portfolio of apps and services. People Skills is the evolution of the service previously known as Skills in Viva.   Built on this new data layer, we’re also introducing the new Skills agent that helps leaders create dynamic skill-based teams to tackle any project, and lets employees find and connect with people with the skills they need.  People Skills enables Copilot and the Skills agent to understand the backbone of your company – your people. This innovative new grounding source augments the critical work context already built into Copilot to produce the first generative AI experience to deeply understand both your business and your people.   The People Skills data layer will start general availability rollout to Microsoft 365 Copilot and Viva customers at Microsoft Build in May 2025.  The Skills agent will become available starting in June 2025.   Overview  People Skills infers individuals’ skillsets derived from user profile and activity mapped to a customizable built-in skill taxonomy. This data layer fuels the Skills agent, and enhances Copilot Chat, Microsoft 365, and Viva services with contextualized information about the people in your organization.   With this advanced AI-based skills inferencing methodology built into everyday work tools, paired with robust privacy and visibility controls for both admins and end users, People Skills can equip leaders with critical workforce skill insights to prepare and accelerate their AI transformation while empowering employees with personalized skill profiles and career growth tools.   Skills agent  The new Skills agent helps leaders and employees across the organization stay informed, agile, and ready to thrive.   Employees can use the agent to easily explore their own skills and how to develop them, see how they can best leverage Copilot, find experts in the organization, and understand colleague’s skillsets.   Leaders can use the Skills agent to inform strategic workforce planning decisions, such as staffing for high-priority projects, with an up-to-date view of talent landscape strengths, gaps, and opportunities.    People Skills for leaders and organizations  To empower business leaders and analysts with detailed skills-based organizational insights, we’re introducing the new Skills landscape report in Copilot Analytics. This report can be filtered by organizational data - such as HR attributes – to allow leaders and analysts to customize views for relevant groups. The Skills landscape report data can also be exported for custom analysis.   The Skills landscape report will be available in Viva Insights starting in June 2025 and include four report pages detailed below.   The Skills introduction page explains how skill inferences are generated, allows for customization of report parameters, and displays a snapshot of organization progress towards confirmed skills on individual profiles.   The Top skills page shows commonly used skills and identifies areas of skill specialization in your organization.  The Deep dive page allows you to deep dive into a specific skill – including subskills and adjacent skills – to get a more complete view of talent in a specific area.     This Deep dive page also delivers insights focused on the number of people using selected skills by group, trending growth over time, and a heatmapped view of skill concentration across teams.    The Skills hierarchy page allows you to view the connection between skills and explore how your company’s skill taxonomy is structured. This view further allows you to drill down into granular skills that are critically important to your business.   People Skills for employees  People Skills improves the employee experience by improving expertise discovery, showcasing hard-earned talents, and accelerating career growth. As a core principle of People Skills, every person will have the ability to edit, update, customize – and if desired – opt out of sharing their skills or having their skills inferred.   People Skills enables multiple employee scenarios across a variety of apps and services, including: Microsoft 365 Copilot, Skills agent, Microsoft 365 profile card, Microsoft 365 profile editor, Org Explorer, People companion, and Viva Learning.   Watch the video below to see how People Skills creates a rich, connected experience in the flow of work across these endpoints.    Inference engine  The People Skills inference engine uses Microsoft 365 profile and activity signals from the Microsoft Graph like documents, emails, chats, and meetings to create personalized skill profiles for individuals within your organization.         Under the hood, the inference engine is powered by the latest OpenAI LLM models, with a proprietary inferencing approach based on principles of game theory and multi-agent frameworks executing multi-directional inference runs across relevant Microsoft Graph data. This skill extraction ecosystem leverages simulated agent personas that operate on bespoke logic to capture the right signals, optimize for a diverse and specific pool of skills, and improve predictability between input signals and output skills. Combined with the richness of underlying Microsoft Graph data, this proprietary approach produces accurate skill profiles for each user.   In addition to generating accurate skill profiles, the People Skills inference engine:  Has a frequent refresh cadence so inferences are always up-to-date and relevant  Requires zero action by end users (note that users always have control over their skills inferences, profile display, and visibility settings)  Takes <5 minutes to set up from Microsoft 365 admin center when using our recommended configuration  Includes robust privacy and visibility controls at both the admin and user level  By building a skills inference engine that is accurate, up to date, easy to set up, requires zero end-user action, and is embedded into everyday work tools – we believe we may have solved the core issues traditionally preventing companies from accessing relevant skills information.    Flexible taxonomy approach  People Skills includes a flexible approach to skills taxonomy management, designed to meet you at any stage along your journey to a skills-enabled organization.   Option 1 – Use the built-in skills taxonomy  People Skills includes a built-in skills taxonomy of 16,000+ skills produced in partnership with LinkedIn. Each of the 16,000+ skills in this taxonomy are surrounded by a semantic description of embedded data including skill name, skill description, related skills, where the skill fits in a skill hierarchy, roles that tend to have this skill, and more contextual information on how the skill gets applied at work. This information helps the People Skills inference model determine when the skill is demonstrated.  You can use this taxonomy out of the box, or customize as needed, with admin editing capabilities supporting both removal and addition of skills.  Option 2 – Use your own custom skill taxonomy  You may choose not to use the built-in skills taxonomy, and instead import your own custom skill taxonomy.      Privacy and visibility controls  We take responsible AI and privacy seriously to help you deploy with trust. People Skills includes robust privacy and visibility controls both at the admin and user level. Admins can set these controls for users, groups, or for their entire tenant to meet their needs.   As noted below, users are always in control of their Microsoft 365 profile and may turn skills inferencing and/or skills visibility off at any time.   Skills inferencing controls:  Admins can turn skills inferencing auto-on (individual users can opt out)  Admins can turn skills inferencing auto-off (individual users can opt in)  Admins can disable skills inferencing for their tenant  Skills visibility controls - this refers to the ability for users to see their colleagues’ skills on surfaces like the people card or in Copilot:  Admins can turn skills visibility auto-on (individual users can opt out)  Admins can turn skills visibility auto-off (individual users can opt in)  Admins can disable skills visibility for their tenant  People Skills also provides a framework for tagging sensitive skills that admins do not want the inference engine to capture.   Customer feedback  People Skills has already been enabled for over 100,000 Microsoft employees and 10 customers participating in our private preview. We thank our preview customers for all the deep dives, feedback, and iteration as we fine-tuned our inference engine. In their words:  “We’ve partnered with Microsoft to help our people gain the skills they need for the future. As we undertake one of the largest transformations in UK financial services, gaining deeper skills insights will be instrumental in unlocking the potential of our colleagues and equipping them with the capabilities they need now and in the future. Making the process for colleagues to record their skills simple and efficient has been a priority, enabling them to focus on the skills they want to develop to better serve our customers. The AI-powered suggestions within People Skills are thoughtfully aligned with the work our colleagues do, helping us accelerate progress in our transformation journey”.    - Sharon Doherty, Chief People & Places Officer, Lloyds Banking Group    "The future of work is increasingly about sk...

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Very few companies I've encountered have been so direct and clear on "How we expect you to use AI at x company". I think this move empowers and allays the fears of those who are already using AI on the side. That's a big hurdle already cleared. One which can really amplify adoption. There's some bits I'm not sold on (looking at you point 5), yet, what I really liked here is the focus on learning together. What's clear for Shopify employees is: - They have access to AI tools - They have the endorsement to experiment and explore - They're actively being given places to share ideas and lessons - They know leveraging is a key skill for today and the future If you want to build these mythical learning cultures we all talk abt, you need more action like this. Often, people know what to do but until you open the door to that path as a company, you'll probably stagnate. Anyway, that's my two cents. → How are you approaching the mandate of AI at work? Let's chat abt that in the comments ↓ #education #learninganddevelopment #artificialintelligence

I got a message last week that stopped me mid doom-scroll. "I just saw a video of an AI agent taking a test for someone. Aren't you worried about that?" Honestly? No. But probably not for the reason you'd expect. I've spent nearly 20 years in learning and education. I've seen trends, fads, and enough terrible multiple-choice quizzes to last a lifetime. The AI agent didn't scare me. The fact that this is still how we assess skills? That did. If your entire measurement of understanding relies on picking answers from lists, of course an AI can game it. So could a cheat sheet. So could your colleague who's got a memory like an elephant. This isn't about AI cheating the system. It's about the system being easy to cheat because it's broken. ❌ We don't need better tests. → We need a better approach. If we confirm 'skills' and 'understanding' through quizzes, then it's all just a game of who has the best memory, not who understands how to apply knowledge. I know millions of institutions and corporate learning experiences worship at the altar of the almighty multiple choice exam as the measurement stick for human intelligence, skills and expertise. ↳ Doesn't mean it's right. That's where AI can actually help. Not as a cheat code, but as a coach. To challenge, to question, to uncover the "how" behind your answer. In tomorrow's Steal These Thoughts! newsletter, I'll show you an AI-powered approach that could transform how we validate skills and knowledge, and help you build more meaningful assessment experiences. Join us by clicking 'subscribe to my newsletter' on this post and my profile. #education #learninganddevelopment #aritificialintelligence | 27 comments on LinkedIn

In this podcast I describe the massive AI-powered revolution starting in corporate L&D, and give you some history, context, and a mandate for the future. Thi...

*** 🚨 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? | 34 comments on LinkedIn

Early in my facilitation career, I made a big mistake. Spent hours crafting engaging activities and perfecting every little detail… Thinking that amazing… | 46 comments on LinkedIn

🎓 Neues Impulsvideo im New Learning Lab: Der Super-Flop!? Rabbit r1 🚀Ich habe mir das Rabbit R1-Gerät gegönnt und es ein paar Wochen getestet. Das kleine D...