I love falling into research rabbit holes, especially outside our field. Some of the richest, most useful ideas I’ve found come from marketing, where attention, relevance, and action are the whole game. That has helped me rely less on instinct, make better learning design decisions, and think more clearly about what actually moves people. It’s also a big part of what led me to write "Think Like a Marketer, Train Like an L&D Pro". So I’m curious: where do you go to find the ideas and research that sharpen your work?

Thanks for reading!
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Supported by iSpring

More interactivity is not always the fix. If learners are dropping off, the real problem is often somewhere else in the experience. This free guide helps unpack where engagement breaks down and shares useful ideas for increasing learner buy-in in more meaningful ways.

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Your Course Has a Time-to-Value Problem

Think about the last course you launched.

When did your learner first get something useful from it?

Not when they finished. Not when they passed the quiz. When did they first experience something they couldn't do, know, or see before they opened module one?

If you're not sure, that's a problem. And it has a name.

In the SaaS world, it's called Time to First Value (TTFV) — the gap between when someone starts using a product and when they get their first real result. Product teams obsess over it because the pattern is clear: the longer that gap stretches, the more users quietly walk away before they ever reach it.

Your learners are doing the same thing.

The research backs this up — from inside L&D

A 2017 study in the Journal of Educators Online (Christensen & Spackman) analyzed 54,393 enrollments across 196 online courses and found something instructional designers need to sit with.

Learners weren't dropping off randomly. They were hitting "Course Walls" — specific points in a course where groups of students stopped progressing at the same lesson. The researchers measured this using a formula called the Student Momentum Indicator: the percentage of enrolled students who will eventually finish the course, calculated after each lesson. When you graph that number across your course, Course Walls show up as sudden drops.

Here's what made the findings uncomfortable. Those walls weren't random. They weren't caused by one difficult lesson here or there. They were structural — and they most often appeared in the first third of the course, before learners had gotten a single thing they could use.

That's your TTFV problem, made visible in your data.

The study identified nine distinct dropout patterns. The most damaging weren't single steep walls; they were back-to-back walls, where a learner clears one difficult section but hits another before recovering momentum. Each wall compounds the last. By the time a learner reaches the third obstacle without having gotten anything valuable yet, the math is simple: the cost of continuing outweighs what they've received.

Course Walls, it turns out, are what a long Time to First Value looks like in your LMS data.

What product designers figured out

Netflix doesn't make you sit through a welcome orientation before you can watch anything. They put something good in front of you immediately. Their whole philosophy is: earn the next 10 minutes before asking for more.

We do the opposite.

Most L&D design starts with a sensible question: What does the learner need to know before they can do anything? The instinct makes sense. But it produces courses where 20 minutes pass before anything genuinely useful happens. By then, many learners have already mentally checked out — and your LMS data will show exactly where.

Product designers call the turning point the "aha moment" — the first instant a user thinks this works. They design everything around getting you there fast. Content order. Navigation. Onboarding flow. All of it engineered to shorten the gap between "I started this" and "I got something from this."

We almost never ask the equivalent question. Here it is:

That's your TTFV. Find it. Then find out how many learners are hitting a wall before they reach it.

One thing to try this week

You can find your own Course Walls with data you already have. Pull your LMS completion data by lesson or module — not overall completion, lesson by lesson. Calculate what percentage of your enrolled learners made it past each one. Graph it. Where you see a sudden drop between two lessons, that's a wall.

You don't need to rebuild the course. You need to understand why momentum stopped at that specific point. Was the content too dense too early? Was there nothing useful yet? Was the cognitive load suddenly higher than what came before?

As a rule of thumb, if your first Course Wall appears before your learners have gotten anything genuinely actionable, you don't have a content problem. You have a sequencing problem. Move the value earlier and the wall often moves with it.

Also supported by Neovation

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Worth your attention
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Time to Value: The Metric You Can't Afford to Ignore.

Where the TTV concept originated. The formula is simple: TTV = Date of First Value Moment − Date of Start. Swap "user" for "learner" as you read it.

​Start with where the concept came from →​

Dropout Rates, Student Momentum, and Course Walls

The original study. Real data across 196 courses and 54,000+ enrollments. The Student Momentum Indicator formula is simple enough to run in a spreadsheet with your own LMS data.

​Read the study that names what you've been seeing for years →​

A Review of Online Course Dropout Research

Meta-analysis of 35 studies identifying 69 dropout factors. The key finding for IDs: while dropout is often blamed on learners, the solutions that actually work are almost entirely within the course design.

​See which dropout factors are actually in your control →​

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The Bottom Line

Learners aren't quitting because they're lazy or busy or resistant to change. They're quitting because the design asked them to invest time before it offered any return. Research makes clear that the factors within your control — course design, structure, relevance, early feedback — are exactly the ones most likely to move the needle on dropout. Course walls show you where in your course the damage is happening, lesson by lesson. And TTFV gives you the question that reframes everything: not "did they finish?" but "when did they first get something valuable?"

Change the question. The design follows.

🎵 Today I'm listening to Al Jarreau​

📍Where I'll be next

• ​LearnTec, May 5-7 (Karlsruhe, Germany)
• ​ATD International Conference, May 17-20 (Los Angeles, CA)
• ​Canadian eLearning Conference, May 29 (Niagara Falls, ON)
• ​ATD Core4, Sept 29-Oct 1 (Indianapolis, IN)

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