What Great Instructional Designers Do Differently

One of the biggest challenges I’ve seen in my 25+ years in instructional design is that we’re still spending too much time on the wrong things.

Instructional designers are often working incredibly hard, but not always on the things that create real impact. A lot of effort still goes into storyboarding, polishing, and refining content-heavy courses, when the real value lies elsewhere.

That tension is becoming more obvious as expectations for learning outcomes increase. It’s no longer enough to deliver well-produced content. We need to design for adults, who need the right support where they need it to strengthen the foundations of great performance where needed.

The best learning helps people do, not just know

A lot of traditional learning design has approached content as the core problem to solve. But in reality, content is rarely the bottleneck anymore.

Most foundational knowledge is already accessible, and is becoming more accessible with the implementation of AI initiatives that connect that integrate proprietary knowledge and data within organizations. If someone wants to understand a coaching model like GROW, they can find it instantly. The challenge isn’t about having access to information, but knowing what to do with it in a real-world context.

This is where learning design has the opportunity to truly flex and shine. We get hung up on building explanations, when what people actually need is application.

The shift we need is from content delivery to true learning design, where we move the focus back to the real problem, and who needs what to overcome it without relying on a one-size-fits-all solution. This means:

• From explaining concepts to building scenarios that effectively demonstrate or model concepts
• From knowledge recall to decision-making practice
• From static information to contextualized performance support

Knowing something is very different from being able to use it, and the ability to apply knowledge in day-to-day roles requires a different approach to instructional design.

The best learning experiences are grounded in real context

If there is one thing I keep coming back to, it’s context.

Context is the environment the learner operates in, whether that’s their role, pressures, working relationships, constraints, and the decisions they actually have to make day to day.

A “feedback conversation” isn’t a single skill. It changes completely depending on whether you’re speaking to a peer, a senior leader, or someone under pressure. The same applies across almost every workplace capability. Without context, learning becomes abstract and fragile. With context, it becomes usable.

This is why generic, one-size-fits-all content often underperforms. It may be useful for someone completely new to a topic, but adult learners rarely need novelty. They need relevance that complements the experience and expertise they already have. In fact, research suggests that expertise matters, and learning can have a negative impact on these learners if the exercises and content aren’t appropriately challenging.

The more closely learning mirrors real situations and fits the learner’s expertise appropriately, the more likely it is to transfer into real behavior.

Engagement goes beyond clicks and completions

We also tend to think too narrowly about what learner engagement actually means, and why it matters.

It’s well documented that measuring surface-level engagement, such as completion rates, clicks, and satisfaction scores, is not useful on its own. Just like how learning needs context, metrics and what you measure needs context too.

Deeper engagement looks very different. It may involve measuring application of learning in decision-making, analysis, and evaluation performance exercise both in practice and as applied in a real work context. That’s where learning starts to connect to performance.

There is a progression that matters here:

• Motivation to engage with the problem
• Attention and cognitive fit (too easy and learners will lose interest, too hard and learners may get frustrated and give up)
• Deliberate practice with feedback
• Reflection and reinforcement
• Real-world application

Learning is a chain that extends beyond the course itself. If we only think about the learning content, we miss the rest of the system entirely, which means we also miss out on a lot of potential engagement and impact.

Strong instructional design starts with the right problem

Too many learning projects start with a solution already in mind, which usually means the actual problem gets shoehorned into a predetermined course or resource.

But if the problem isn’t clearly understood and kept front of mind throughout the instructional design process, everything downstream becomes diluted.

The strongest learning experiences usually include:

• Opportunities for learners to make decisions and test ideas
• Feedback that helps learners improve in the moment
• Reinforcement beyond the course itself
• Clear alignment to real performance outcomes
• Prompts that promote reflection and awareness of the learners’ own thinking, learning needs, and knowledge gaps

That reinforcement might include coaching, reflection prompts, performance support, or structured on-the-job application. Simulations are often a particularly effective middle ground because they give learners a safe space to practice before applying new skills in real situations.

And finally, great instructional designers stay focused on what success looks like in performance terms, not just learning metrics. That’s what makes learning relevant to business leaders and meaningful to learners.

Simpler learning often performs better

One of the most consistent patterns I’ve seen is that simpler learning often outperforms highly polished content.

A well-designed job aid, a short focused walkthrough, or a clear one-page guide can be far more effective than a highly produced course because it is accessible at the moment of need, and the gap you are closing is one where this strategy fits the best.

I’ve seen this play out repeatedly. A simple video for setting up a Gmail inbox, for example, can outperform formal training that covers all the ways to use Gmail because it supports where the real need is, in real time. Nobody wants to sit through a full eLearning course explaining what Gmail is or how email evolved if they just need a quick answer.

This is where learning design becomes less about production value and more about usability. A 30-second screen recording could easily be more useful than a slick, polished course. If learning content doesn’t support action, it doesn’t matter how polished it is.

The best instructional designers involve stakeholders early

Most learning projects go off track for two predictable reasons:

• The problem was never clearly defined
• Stakeholders (including the learner audience) were not involved early enough

Teams often move too quickly into solution mode without fully understanding what is actually driving the need. This can lead to redesigns, scope changes, and unnecessary complexity later on.

At the same time, when key decision-makers are not engaged early, alignment breaks down. By the time they see the final output, the risk is that it may not reflect what they needed, triggering costly, frustrating rework.

The most successful projects are the ones where everyone understands the challenge from the start, not just the deliverable. That shared understanding becomes the anchor for every design decision that gets made.

Taking the time upfront to define the problem you’re trying to solve will save far more time later. Keeping stakeholders involved throughout the process also helps maintain alignment and investment in the success of the learning program.

AI should free instructional designers to focus on higher-value work

There is a lot of discussion right now about how AI can speed up learning design, and I think that’s absolutely true, but only if we use it well.

AI can support analysis, generate scenarios, accelerate drafting, and reduce time spent on repetitive tasks. But the real opportunity isn’t just about doing things faster. It’s about focusing more attention on the work that actually improves learning outcomes.

If we remove some of the manual overhead, we can spend more time:

• Designing better practice
• Improving contextual relevance
• Testing learning effectiveness
• Refining real-world application

The goal isn’t to remove humans from the process. The value of AI is to help instructional designers spend more time on higher-value design and learning strategy work.

Technology should support good instructional design

Tools matter, but they should never lead the design.

The best platforms support the way learning teams actually work. Increasingly, that means supporting collaboration, version control, structured workflows, and the ability to maintain and improve content over time.

These operational details become especially important when teams are managing large volumes of learning content, multiple reviewers, and frequent updates. In my experience, platforms that reduce administrative friction make it much easier for teams to focus on learning effectiveness and learner performance.

Platforms like dominKnow are designed around the realities of modern instructional design work, especially when it comes to collaboration, content management, and maintaining consistency across large learning ecosystems.

Where instructional design is heading next

The direction of learning design is becoming clearer.

We’re moving away from:

• Static, content-heavy courses
• Isolated learning systems
• One-off training events

And we’re moving toward:

• Connected learning ecosystems
• Embedded practice and feedback loops
• Data-informed design
• AI-supported development workflows
• Real-world performance integration

The focus is shifting from delivering learning to enabling performance.

The goal for instructional designers today is no longer just to create learning content. It’s to create conditions where people can perform better in their jobs, whether that’s through a year-long learning program, a knowledge bank, a short video, or a single job aid.

If there is one idea I keep coming back to, it’s this: we don’t need more content for the sake of more content. We need better design strategies for supporting performance needs in an environment that is changing faster than we can keep up. 

For instructional designers, that means refocusing our time and efforts on understanding our learners, their challenges, and the environment they are performing in to drive success.

That’s where the real impact is, and that’s where instructional designers create the most value, and always have – lifted from the noise and shadows of a 100% content-focused approach.

About the Author

Amy Parent is an experienced designer of high-quality training and skill development programs, with a focus on scenario-based and performance-based learning relevant to real job contexts. She draws on learning engineering and learning science principles to support self-directed, digital, and blended learning models — spanning e-learning, webinars, face-to-face collaboration, and one-to-one support. She also specializes in defining and measuring instructional data to assess learning impact against business goals. Connect with Amy on LinkedIn.

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