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AI agent for curriculum developers

Learner Feedback to Course Fix Agent

Each recurring learner complaint is tied to a lesson fix, and the agent verifies whether the complaint went away.

DecisionsAnalysisEducation
See how it worksGet access
Learner Feedback to Course Fix Agent: what goes in, what the agent does and what you get

What it does

Learners leave comments in surveys, forums and support tickets, but those comments rarely lead to a named change in the course. The agent reads new feedback, groups it by lesson and by issue, such as unclear steps or broken links, and counts how many people raised each one. For the biggest groups it proposes a specific fix and who should make it. Later it reads new feedback after the fix is released and checks whether complaints about that lesson dropped. If they did not, it loops back and proposes another change. The developer approves every change. Edge case: a lesson with high complaints that are really about a tool update outside the course.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
ApprovedYes, continueNo 1 STARTS WHEN Weekly run 2 USES A TOOL Read new feedback from surveys, forums and tickets 3 DOES Group comments by lesson and issue type 4 DOES Rank groups by count and severity 5 DOES Propose a specific fix and owner for each top group 6 YOU APPROVE Developer approves the fixes to make 7 USES A TOOL Create tasks for the fixes 8 USES A TOOL Wait for release and read new feedback 9 CHECKS THE RESULT Did complaints about the fixed lesson drop below thetarget? If not: Regroup the new comments and propose a differentfix. Back to step 4. 10 DOES Update the feedback record with results 11 RESULT Fix and results report
Read the steps as a list
  1. Weekly run
  2. Read new feedback from surveys, forums and tickets
  3. Group comments by lesson and issue type
  4. Rank groups by count and severity
  5. Propose a specific fix and owner for each top group
  6. Developer approves the fixes to makeThe agent waits here for your OK.
  7. Create tasks for the fixes
  8. Wait for release and read new feedback
  9. Did complaints about the fixed lesson drop below the target?If not: Regroup the new comments and propose a different fix. Back to step 4.
  10. Update the feedback record with results
  11. Fix and results report

How it decides

It ranks issues by how many learners raise them and how much of the lesson they affect, and judges a fix by the change in complaints after release.

  • Raise an issue when 5 or more learners mention it in a month
  • Count a fix as working when complaints drop by half
  • Separate course problems from tool or platform problems
  • Send safety or legal comments straight to the developer

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Complaint count that triggers a fix (default 5)
  • Feedback sources to read
  • Review schedule
  • Target drop in complaints (default 50%)

What keeps you in control

It always asks you first

  • Developer approves each proposed change before it is made

Hard limits

  • Never change course content itself
  • Do not quote learners by name

It stops when

  • Done: top issues fixed and complaint trend confirmed
  • Stop: feedback volume is too small to judge a trend

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn a month the agent groups 120 comments and finds 18 about unclear steps in Lesson 6. It proposes adding a screenshot and a worked example, and the developer approves. After release, new feedback shows 11 complaints in two weeks, still high. The agent rereads them and finds most mention a menu name, so it proposes renaming it.

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