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Training example

Adapt the next practice step to the learner.

Adaptive learning changes the next task from evidence the learner just supplied. Answer the first call, review targeted teaching, and try a new case.

Press play and use the interactions in this published example.

Read the related guide

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How it was built

The viewer's choice controls the route

Mindstamp saves first answer and teaching path and followup answer, opens the matching scene, and keeps the response in the session recap.

  • Buttons
  • Video branching
  • Viewer variables

What it does

Your first answer changes the teaching scene. The same follow-up case checks the next decision.

This is explicit rule-based branching inside a video. It is not an AI diagnosis or a complete adaptive learning system.

Inside the experience

What the viewer does

The video gives each interaction a clear job in the route.

1. Review

Customer: “I have explained this twice, and the charge is still there.”

What should the agent say first?

2. Choose

Select an answer

Choose “I can see why repeating this is frustrating.”, “You need to calm down.”, or “I will transfer you.”.

3. Follow

See the result

The video opens the matching scene and carries first answer and teaching path and followup answer into the recap.

What it reports

Each interaction is measured

Viewer choice
The report stores the answer selected in the decision scene.
Result route
The session shows which result scene opened after the choice.
First Answer and Teaching Path and Followup Answer
The recap keeps the saved value with the viewer session.

Build one like it

Start from a video you already have

The interactions were added on top of an existing recording.