All Things Learning Design

Introduction

Nolan: Welcome to the Learning and Development podcast sponsored by Infopro Learning. As always, I’m your host, Nolan Hout. Joining me today, we have Julie Dirksen, author of one of the best-selling instructional design books of all time, Design for How People Learn. It’s an incredibly popular book, although it was written maybe a decade ago or so. There’s been new releases and it continues to be popular today. She’s also an internationally recognized speaker and learning consultant on a wide range of topics, with a special focus on incorporating behavioral science into learning interventions.

Today, we’re going to talk about all things learning design, from diagnosing the problem, creating sound design strategy, reducing cognitive load, and more.

Julie: Thanks for having me.

Nolan: The first thing we like to do when we start is learn a little bit more about our guests. Obviously, as a best-selling author and international speaker, you didn’t start your career there. How did you get into the world of learning and development?

Julie: I feel like the origin story for a lot of people is something like this: you’re a good customer service rep, so they ask you to train the other customer service reps. People often come at it from domain knowledge. They know their topic well, they help others, and eventually they’re tapped to become the training person.

That’s basically how it happened for me. I was doing data entry for a finance company as a part-time job while I was in college. When I graduated in the early 90s the economy wasn’t great, and they asked if I wanted to train other people to do data entry. I also had been working on a certificate in teaching English as a foreign language, so I was already interested in the education side.

When I got into it, I discovered what I really loved was the design piece, how do we create courses, how do we structure them, how do we use technology to support learning. I still enjoy delivering workshops, but I realized I wasn’t enough of an extrovert to want to be a full-time trainer. The design aspect was what really grabbed me.

So, I went to graduate school in the late 90s at Indiana University for instructional systems technology. At the time it was one of the largest instructional design programs. A lot of my work there overlapped with what we now call user experience design, although at the time it was called human-computer interaction. The focus was on how technology and environments can support performance, not just training. That perspective stuck with me. Training can help people, but it doesn’t fix a bad system.

Diagnosing the Real Learning Problem

Nolan: When we talk about creating impactful learning experiences, we must start by diagnosing the real problem.

Julie: There’s a recurring theme in the learning industry about not being an order taker. Someone might come in and say, “We need customer service training.” But the real challenge is identifying the actual problem they’re trying to solve.

Sometimes stakeholders don’t even know the problem themselves. They might just say they’re unhappy with how things are going.

One of the first questions is whether you’re being given a problem to solve or a solution to implement. If someone says, “We need sales training,” that’s a solution. Instead, ask what behaviors aren’t working right now and what needs to change.

For example, maybe sales reps start pitching product features immediately instead of asking the customer questions first. That’s a behavior issue. Now we can focus the learning interventions around helping reps diagnose customer needs before presenting solutions.

But even then, it might not be only a training issue. Maybe the sales materials don’t support the behavior you want. Maybe incentives reward speed instead of consultative selling. Maybe reps are judged by number of calls instead of repeat business. In many cases, training is just one part of the solution.

Building Trust with the Business

Julie: A lot of success depends on the relationship you build with stakeholders. Do they see you as a partner solving business problems, or as a vendor delivering training? The questions you ask early on matter a lot. One helpful question is: what budget line item is paying for this work? That often reveals what success looks like to the stakeholder.

Another important consideration is understanding what success looks like for the person you’re working with. Sometimes their KPIs or pressures shape what they need from you.

For example, someone might want more interactive, scenario-based training. But their manager might say they need a quick win. If you ignore that constraint, you’re not really listening to the stakeholder’s reality. Effective solutions often involve negotiating between better learning design and the constraints stakeholders face.

Design for Real-World Application

Nolan: Once the problem is defined, the next step is matching the design strategy to the complexity of the problem.

Julie: When designing learning solutions, the key question is always: what will people do with this knowledge in the real world?

In workplace learning, the focus is almost always on application. If someone knows something, what behavior will it enable?

Instead of saying “programmers should understand when JavaScript is appropriate,” a better objective is: programmers will evaluate a project and determine whether JavaScript is the right tool. Once framed that way, the learning activity becomes clearer. Learners should practice evaluating projects and deciding which tools are appropriate.

A useful framework here is action mapping: identify the business goal, determine the behaviors that support that goal, design practice activities that develop those behaviors, and only then identify the information learners need.

Many traditional training programs start with information instead of starting with behavior. But real workplace learning happens through application.

The Role of AI in Learning Design

Nolan: Are you seeing AI play a role in how learning designers approach these challenges?

Julie: AI can be helpful in many design tasks. For example, it can generate plausible learning objectives or examples tailored to a specific context. Designers can then review and refine those outputs rather than starting from scratch. That can save significant time.

However, AI still requires human expertise to evaluate its outputs. Beginners often cannot judge whether AI responses are accurate or useful. In many ways AI functions like a productivity tool. It helps experts work faster, but it doesn’t replace expertise.

Foundational Knowledge vs. Tools

Nolan: There’s a lot of debate right now about whether people should memorize information or rely on tools.

Julie: Some foundational knowledge still matters.

For example, understanding multiplication tables supports higher-level mathematics. Without those foundations, it becomes harder to reason about more complex concepts. Similarly, workplace learners need enough background knowledge to evaluate AI outputs or apply tools effectively.

Knowledge works best when it’s learned in context. Memorizing facts in isolation tends to fade quickly unless learners repeatedly apply them.

Motivation, Habits and Behavior Change

Julie: Not every performance gap is a knowledge problem. Some gaps are skill problems that require practice. Others are habit problems where people know what to do but haven’t integrated the behavior into their routine.

Still others are motivational problems where people understand the desired behavior but aren’t motivated to do it. Behavioral science can help uncover the real reasons behind behavior.

For example, a project in Nigeria aimed to increase HIV screening among men. Initial assumptions focused on messaging about responsibility and protecting partners. But deeper research revealed that fear was the main barrier. People were afraid that a positive test result would completely change their lives.

Once the messaging shifted to emphasize that treatment is manageable and life can continue normally, participation increased. Understanding the true barriers behind behavior is often the key to designing effective interventions.

Curiosity and Self-Directed Learning

Nolan: Curiosity seems to play a big role in learning as well.

Julie: Many organizations want learners to be self-directed. But curiosity and motivation don’t appear automatically. People must see value in the resources available to them. They need to know that useful answers can be found quickly and reliably.

If internal knowledge systems are difficult to navigate, people will default to asking coworkers, searching the web, or using AI tools. Building effective learning ecosystems requires making helpful resources easy to find and worthwhile to use.

Closing Thoughts

Nolan: Designing effective learning experiences requires diagnosing the right problem, understanding behavior, and aligning solutions with real business goals.

Training alone rarely solves performance problems. Effective solutions often involve a mix of learning design, behavioral insights, and organizational changes.

And as tools like AI evolve, the importance of foundational knowledge, critical thinking, and curiosity will only grow. Thanks for joining the conversation.

Julie: Thanks for having me.