Activity: Write a Machine-Learning Problem Brief
Activity ID: ML-M01-A01 Estimated active time: 35-50 minutes
Goal
Create a clear problem brief before any model is trained.
Case options
Choose one case.
Case A: Learner Support
An online course team wants to help learners who may stop during Module 1. The team can send a short optional support message, but mentors have limited time.
Case B: Support-Ticket Priority
A small education company receives support tickets from learners. The team wants to find tickets that may need a faster response.
Case C: Practice Recommendation
A course platform wants to recommend extra practice resources to learners who may benefit from more examples.
Instructions
Fill this table.
| Field | Your answer |
|---|---|
| Practical goal | |
| Task type | |
| Target | |
| Unit of analysis | |
| Prediction time | |
| Outcome window | |
| User | |
| Action | |
| Affected people | |
| Baseline | |
| Success criterion | |
| Unacceptable failure | |
| Feasibility decision |
Then write:
- A harm statement in 2-4 sentences.
- One reason a simple rule may be enough.
- One reason a model may be worth testing.
- One reason to revise or stop the project.
Quality checklist
Before submitting, check:
- The target is observable.
- The unit of analysis is one clear thing.
- The prediction time is before the action.
- The action is realistic.
- The affected people are named.
- The baseline is simpler than ML.
- The unacceptable failure is specific.
- The brief does not claim that prediction proves cause.
Example opening
Weak:
Predict urgent support tickets.
Better:
Within 10 minutes of a support ticket arriving, predict whether the ticket is likely to require same-day human response, so the support lead can review high-priority tickets first.
Submission format
Submit the completed table and short notes as plain text or Markdown. Do not include real names, emails, phone numbers, employer data, private learner data, or sensitive information.