How Neuroscience Can Elevate Learning and Amplify Impact

Introduction

Nolan: Hello everyone, and welcome to the Learning and Development podcast sponsored by Infopro Learning. As always, I’m your host, Nolan Hout. Joining me today, we have a very special guest: Stella Collins, known as the “Brain Lady” for her pioneering work in applying neuroscience to learning and development. This topic of neuroscience and learning is always a fascinating one for me; I’m so excited to have Stella on.

She has over 25 years of experience in this field, training professionals worldwide. She’s the author of a best-selling book called Neuroscience for Learning and Development, and she’s taught over 50,000 people on LinkedIn Learning. Today, we’re going to talk with Stella a little bit about a lot of things, but it’s all going to be centered around this idea of elevating learning and amplifying impact. And to help us amplify that impact, let’s actually meet Stella. Stella, welcome to the podcast.

Stella: Thank you very much. Lovely to meet you, Nolan.

Nolan: Likewise. And thanks for joining later in your day, because you know we’re on probably completely different time zones. So, Stella, thanks again for joining.

Stella’s Journey: From IT to Neuroscience in Learning

Nolan: You know how we always start with this, Stella, is learning a little bit more about how you got into this field in the first place. You know, you’re a best-selling author, you’ve taught 50,000 people, and you’re widely known as a subject matter expert in learning. But where did you start? Where did this flame that has been burning for the past 25 years begin, and where was the kindling?

Stella: The kindling was probably when I was a kid. My parents were teachers, and I swore I would never be a teacher. Having said that, I did a psychology degree, I did a master’s in human communication, and I became really interested in the brain. So, my final project in my degree was about the brain. Then, I worked in IT for many years. I coded and was a typical IT person, and then took on a role that was IT support and training manager. I thought, “Great, I can do the IT support management bit, no problem. Learning manager, training manager? No idea.” I took on a very inspirational young woman who kept saying to me, “Stella, you’d be good at this. You’d like this. It’s psychology in action. It’s psychology in motion.”

That kind of inspired me. I got really interested in the brain and learning. I went to an HR conference where there were lots of people in great suits, and there was a pirate ship. I spoke to the pirate ship, and they were teaching finance training but using a really different kind of methodology; really using a much more brain-friendly methodology. So, I kind of joined up with them. I ran away from home, joined a pirate ship—well, not literally—and then have been in learning and development ever since. I just keep on evolving my knowledge about the brain, but also, it’s very much around the practical application of what we can take from neuroscience and psychology to make learning better. It’s a passion to make sure that when people are learning at work, they’re able to get impact and results from it.

How the Brain Learns: The G.E.A.R. Model

Nolan: Yeah, that’s really interesting. The neuroscience and psychological factor has always been really interesting to me. My degree is in marketing, but I always found a lot of the interesting components were more about psychology. A lot of our professors actually had that background, helping you understand, you know, when you say this, why do people resonate with it? What actually makes it stick to them? There’s a reason that they say, “Miller, if you’ve got the time, we’ve got the beer,” kind of stuff.

I’ve always found it fascinating that it’s that same principle as I started in my learning career. The more you actually understand the psychological component of why you’re doing it, the way that you say it, and why you design your instruction, the bigger impact it has. The more you understand the core tenets of it, the better you can do in your job. So, speaking of that, let’s start with that very conceptual idea of how our brains and bodies really learn.

Stella: So, it’s all down to neuroplasticity. It’s down to the fact that our brains naturally develop new connections. I think the easiest way to describe it is if I ask you, how did you learn to ride a bike? Tell me how you learned to ride a bike.

Nolan: I think my dad pushed me, and I fell like four or five times. Then one time he pushed me and I didn’t fall, and that’s what I did.

Stella: So that’s really how we learn most things. We want to do it. We get some guidance; you know, your dad pushes you or helps you. You ride in a structured environment, like your backyard rather than on the highway. Then you start experimenting for yourself. You let go, you fall off a few times, and then eventually, you kind of get it. Because you keep repeating it, then you learn it. You’ve learned to do it at a very basic level at the age of four or five, but then as you go through your life, you learn to ride bigger bikes, better bikes, faster, and different types of bikes. You keep mastering that skill, and that’s how we learn all skills.

One of the things I think is really useful in terms of learning is to have a process that helps people remember the stages of learning. That’s why I came up with the GEAR model, which very much represents that story. First of all, think about what’s the end result; the end result is you want to be riding a bike, able to code, have an in-depth conversation, or sell a product. Keep people motivated because learning is quite hard work; it’s effortful and uses brain and body energy. Give people some guidance at the first part, so that’s the ‘G’ of GEAR. Then allow them to experiment, the ‘E’; get them to experiment, fall off, and get some feedback. Then they need to apply it in the real world, the ‘A’. If you’re riding a bike, you need to eventually get onto the road. That application requires support, organizational context, the right environment, and the opportunity to do it.

The final piece of that GEAR is the retention piece, the ‘R’, which is how do you help people remember information for the long term. How do you help people go from riding a small, wobbly bike to turning it into your natural way of behaving and embedding it as a habit? That involves huge amounts of practice and repetition, making sure it goes from being cognitively demanding prefrontal cortex work into something habitual.

Common Missteps in L&D and the Importance of Culture

Nolan: Yeah, so I mean that’s a really simple model. It’s the GEAR model: G for guide, E for experiment, A for apply, and R for retain. Are you seeing a similar application being applied for how people can acquire a skill versus a specific job, especially soft skills?

Stella: Yeah, absolutely. It’s how we learn pretty much everything. A job is a set of skills that you string together in different ways to be able to do your job. Once you master an ability and feel confident and competent, you stop seeing it as a skill; you just see it as something you do.

Nolan: Help me understand, when designing complex learning programs, where do people get it wrong? What are the common missteps, and what is the science behind what they’re doing that makes it less ideal?

Stella: That’s a really interesting meta-question. Where are we getting it wrong? We’re not starting in the right place. L&D are often well-meaning, but they’re creating courses because they think people need them. They’re not questioning what the business needs in order for people to thrive and keep the organization profitable. We tend to measure if people enjoyed the training or if they turned up, neither of which tells you whether they’ve actually applied the skills back in the work. Organizations focus too much on content.

They work hard on motivation and often do the experiment part through workshops or AI simulations, but where they struggle is the application—helping people actually take it into the workplace. The person who has the most impact on whether you apply your new wobbly skills is your manager. Are managers supporting that, and are they empowered to do it? Then there’s the retention piece. Training is often a one-off event where you’re expected to remember and apply it as a skill. Taking people on the full journey is where things fall apart.

Nolan: I like the context you applied to the business. What is the culture of learning or acquiring that skill? A lot of that drives from the manager. If you understand the business world and ecosystem you operate in, you can get them on the bike a lot faster.

Stella: Yes, the culture in which you’re trying to learn is hugely important. If people come to training because they were sent, they’re not going to learn very much. If failure is not tolerated within the organization, they’re not going to practice.

Nolan: You know, it’s an interesting thing; I was just talking with Dr. Karl Kapp, who has done a lot in the gamification world, and he has a new book coming out called “Action First Learning.” I was chatting with him about this idea of how you tell them why they need to know how to ride a bike. He says it’s right to start with why this is important for them, but the lens through which you tell people is important. If you can help them engage and uncover their ‘why’ early on, it makes a big difference.

Stella: I thought that was a really interesting perspective. What’s important there is understanding the stage of learning your people are at. When people are new to something, you need a lot more scaffolding and structuring. If you’re building on skills you already have, that needs less structuring and it works better to let them expand on experimenting and testing their common-sense knowledge. The context of the individual learner is important, and unless they can find their own ‘why’, it’s wrong.

Nolan: Yeah, that point is to help people uncover that ‘why’ with some scaffolding.

The Role of AI in Amplifying Learning

Nolan: One of the things I’ve been wanting to talk about is this idea of artificial intelligence. AI is obviously a really good way for the apply or experiment phase, like creating a customer agent for people to practice with, which takes the burden off the manager. How are you seeing AI apply, amplify, and support what this GEAR model is doing?

Stella: I think AI can really amplify if you’ve elevated the learning in the first place. It can help you analyze problems and business trends. It gets used in the guide part to build content fast and adapt it quickly. It gives learners an opportunity to practice, so that’s the experiment part. AI can also support people in the workplace to effectively coach them to apply what they’re learning. For the retention piece, AI can be used for spaced learning to check whether you’re genuinely learning. AI can also collect and analyze evaluation data.

Nolan: Application and retention is a huge one. If an employee can go to an agent for conflict resolution help later on, it acts almost as application and retention. But I wanted to pick your brain on this: I was listening to a podcast with Werner Herzog, who mentioned that kids today use AI like a calculator without first learning the basic concepts, like the square root of 81. Are we doing a disservice by giving these AI tools immediately without basic knowledge? What advice do you have for L&D professionals to develop their skills while leveraging AI?

Stella: I posted on LinkedIn about this yesterday. We know that if you make it really easy for people to find information, they’ll just find it and won’t learn it. The challenge is if AI is rubbish at math and tells you the square root of 821 is 7, without basic concepts, you just accept it. I think it’s about helping people develop critical thinking as a skill. We are deputizing AI to do some work for us, meaning we’re not building information. I’m not entirely sure of the answer, but my optimistic take is we’ll find a way. The way the world functions may change so much that maybe basic knowledge doesn’t matter anymore.

Nolan: If I know I can get the answer within a couple of seconds on Google, I never think to remember it because our goal is to conserve energy. My advice to those leveraging AI is to just ask it, “How did you come up with that answer?” That one question helps you understand the logic and remain curious.

Stella: That’s a really valuable piece of advice, but you have to remember that AI has no logic. Large language models literally string together words that seem the most likely; they do not understand square roots at all, they just make it sound good.

Closing Thoughts

Nolan: What’s next for you? Are you writing anything new or coming out with any new research?

Stella: I’m definitely writing a new book, and I would really urge people to get in touch with me because I want case studies from companies. The new book is called The Learning Organization. It’s about how we create and support a self-directed learning environment within the workplace. Having people be curious and finding out for themselves is more effective than top-down information delivery. The book is about how to create an environment in which self-directed learning can happen. I am looking for people who’ve got great stories about what they’ve done in their organization or experienced themselves.

Nolan: Lovely. Listeners, reach out to Stella on LinkedIn; you can search for Stella Collins or the “Brain Lady”. Thank you so much for joining us for this remarkable session. I appreciate you staying up later in Belgium. We look forward to catching up with you again once that book comes out.

Stella: Thank you very much, Nolan, and thank you for listening, everybody.

Nolan: Thanks.