Education · teacher professional development
Can You Just Fix It?
A student's line-following robot broke before the qualifying run. Help them find the cause without taking over, while another student waits.
Your role: Classroom teacher
Helps students debug one-on-one. Takes over when time is short.
Gap: Execution under time pressure. Knows asking matters, but defaults to fixing.
Support: Hints only if you ask. Hints are recorded.
Objective
Elicit the student's evidence before choosing a next step, then have the student predict, test and explain, including when another student needs you.
Before you start
- This is a fictional practice interaction. Jordan and Maya are not real students.
- Do not enter real student names, records or identifying incidents.
- Respond as you would in class. Your aim is to help Jordan find the cause and take an evidence-based next step, not only to get the robot working.
- Some choices are trade-offs, not right or wrong. The debrief shows what each one cost.
- Hints are available and recorded separately from independent performance. You can pause at any time. Nothing is timed.
- Free-text replies go to an AI model (Anthropic's Claude, through the Anthropic API) to be matched to a response type. This app keeps no transcript, no account and no analytics. Your results disappear when you close the tab. What happens to your data
For designers: how this scenario was scoped
Three questions came before any dialogue: how long the practice should take, the moment the skill breaks down on the job, and what learners already know. Each answer set a limit on what the scenario tries to do.
- How long should this be?
- 10 to 15 minutes. That's enough time for one skill: responding to a request for a fix without taking over, under time pressure.
- When does the skill break down?
- The skill breaks down in the last minutes of a work period, with a deadline and other students waiting. Fixing it yourself is the fastest way to get the robot working.
- What's the learners' experience level?
- Teachers who already help students debug one-on-one but take over when time is short. The scenario recalibrates an existing habit, so it starts right away.