Big Lever
Institute
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Outcomes

Learn what helps.
Make it better.

We want to understand whether free, practical AI education is useful. That starts with what we can observe—and what learners choose to tell us.

Our approach

Participation is visible.
Learning needs a voice.

Aggregate website analytics can help us understand which resources people visit. To learn whether someone tried a lesson, completed it, or used what they learned, we depend on voluntary student surveys.

There is no grading or individual outcome record. We don't connect a particular learner to a particular result, or collect demographic profiles to decide who is benefiting. Our programming is free and open to everyone.

What we can learn

Two sources. Different questions.

How information can help us improve the Institute

Website activity

How we obtain it
Aggregate page visits and use of website resources, once analytics is configured.
What it can tell us
Which pages attract interest and where access or navigation could improve. A visit is not evidence of lesson completion.

Starts & completions

How we obtain it
Voluntary surveys asking which lessons or courses respondents started or finished.
What it can tell us
Participation reported by respondents. It cannot establish a completion rate for everyone who visits or joins.

Satisfaction & usefulness

How we obtain it
Voluntary survey questions about what helped, what was unclear and what could improve.
What it can tell us
How respondents experienced the programming and where to focus improvements.

Applying what was learned

How we obtain it
Optional questions asking how respondents used a method or skill in their own work.
What it can tell us
Examples of usefulness reported by learners. These are self-reports, not independently verified assessments.

Your participation matters

A few questions.
A useful contribution.

We may invite you to a short survey about your experience. Participation is voluntary; your access to free learning doesn't depend on responding. We will use survey information in anonymized form to improve the programming.

Questions we might ask

  • Which lesson did you try?
  • Did you finish what you set out to do?
  • What helped—and where did you get stuck?
  • Have you used the approach on another task?
  • What would you like to learn next?

Being clear about evidence

Results with context.

When we share survey findings, we will say how many people responded, when the survey ran and what was asked. If we know how many were invited, we will include response coverage. We will distinguish reported experience from observed website activity.

Voluntary responses may not represent everyone who uses the Institute. We won't treat nonresponses as failures, infer individual results from page visits, or present planned measures as achievements. No survey findings are being reported on this page yet.

If our approach expands in the future, we will describe the new measures and update our privacy policy before introducing new data practices.

Help us improve

Tell us what would make learning more useful.

Share an unclear instruction, a helpful lesson, or an idea for what comes next.

Send us feedback →