Pre/Post Training Assessment

The problem this kills

Leadership keeps asking the same question after every training: "Did it actually work?" And all you can show them is an attendance sheet. Attendance proves people showed up. It does not prove anyone learned anything.

You suspect some modules land and others flop, but you have no clean way to see which. Pre-tests and post-tests live in scattered survey tools or spreadsheets, the matching of "before" questions to "after" questions is done by hand, and computing knowledge gain per topic is a weekend of error-prone copy-paste. Worse, if a learner peeks at the pre-test answer key, your whole measurement is contaminated.

This tool turns "they attended" into "scores rose 31% overall, and Module 3 is where it's still failing - here's the proof, approved and ready for the board deck."

What you'll build

A small, private web app for your L&D team and your learners:

• Learners log in and take a pre-test before training, then a matched post-test after.
• The tool scores both and computes knowledge gain for each person and for the whole cohort.
• Gain is broken out by topic, so a weak module shows up as a flat or negative bar instead of hiding inside a healthy average.
• The pre-test answer key never leaks - learners see questions, never correct answers, and never their pre-test results until after the post-test.
• The L&D manager gets a review-and-approve gate: nothing goes to leadership until a human signs off on the report.
• One click gives you a CSV export of pre/post scores and gains in the exact columns your LMS or reporting system expects.

What's inside the Implementation Plan

• It starts by interviewing you about your business. This is not a generic template. The very first thing the plan does is ask the AI agent to interview you - your current assessment process, your roster and SKU/employee-ID conventions, your topics and how pre maps to post, your typical and peak cohort sizes, your pass thresholds, and your messy edge cases (no-shows, retakes, late joiners). Then it reads a short tailored spec back to you and waits for your thumbs-up before building anything.
• A step-by-step build, each step ending in a ready-to-paste prompt for your AI coding agent.
• A data model shaped around learner + assessment + pre/post phase so the same person can't be double-counted.
• Handling for the real world: no-shows on one of the two tests, retakes, and topic-level gain math.
• A "No API yet?" fallback so you can build the whole thing today from a Google Sheet or CSV, with no integration to your existing LMS.
• A verification checklist so you know it actually works before you trust it.

The governance it includes (this is the point)

Measurement tools that feed leadership decisions have to be trustworthy. This plan bakes that in:

• Login so only your team and enrolled learners can use it.
• Row-level security so each organization (and cohort) only ever sees its own data.
• A complete audit trail - who took which test when, who approved which report.
• A human-in-the-loop approval gate - the tool drafts the gain report; the L&D manager reviews and approves before it's shared or used to judge a program.
• Duplicate guards keyed on learner + assessment + pre/post phase, so a refresh or a double-submit can't inflate the numbers.

Who it's for

L&D managers and training coordinators who need to show training impact to leadership beyond attendance - and who want a tool tailored to their own topics, roster, and reporting format rather than a one-size-fits-all survey.

You don't need to be a developer. You need your questions, your roster, and an afternoon or two. You've got this - paste the first prompt.