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Printable student investigation and teacher guide
Ride-Hailing Driver Simulator Worksheet
Plan a fair trip-selection experiment, calculate net earnings and earnings per hour, compare a baseline shift with one changed rule, and defend a recommendation using financial, time, fuel, rating, and fatigue evidence.
1. Frame one useful dispatch question
Start with a decision question, not “How can I earn the most?” A useful question names one acceptance rule and the connected results it may change. Example: How does rejecting pickups longer than 4 km affect net earnings, earnings per hour, completed trips, fuel cost, fatigue, and rating?
My investigation question:
Why this question matters to a simulated driver:
Choose one main rule to test:
2. Plan a controlled shift comparison
Keep the income or trip goal, challenge mode, starting setup, and main decision rules stable. Complete a baseline shift, then change only the selected rule. Because dispatches vary, use a repeat run and make a cautious claim when the runs face different demand or random events.
Prediction: If I change __________ from __________ to __________, then __________ will change because:
Guardrail: I will pause or reject the rule even if simulated net earnings rise when it causes this unacceptable fatigue, rating, fuel, time, or service result:
3. Evaluate a dispatch before accepting it
Use the information visible on the simulator phone. “Estimated” values support a choice; final shift values support the result analysis. A long pickup consumes time and fuel even though it is not the passenger's trip distance.
Decision check: Does this dispatch satisfy the rule written in section 2? ☐ Yes ☐ No. If your choice breaks the rule, record why before clicking.
4. Calculate the shift measures before judging the rule
Use figures from the same completed shift and include units. The simulator reports these measures, but recalculating them reveals whether a strategy raised gross fares while weakening retained earnings.
Reconciliation check: Does gross minus all listed costs equal reported net earnings after rounding? ☐ Yes ☐ No. If no, recheck signs, units, and copied values.
5. Record baseline, test, and repeat evidence
Copy each result at the same stopping rule: goal reached, agreed clock time, or manual end. A repeat does not erase an inconvenient run; it shows whether the pattern is stable enough for a bounded recommendation.
| Run | Acceptance rule | Gross | Fees | Fuel + other costs | Net | Net / hour | Trips | Net / trip | Distance | Hours | Rating / fatigue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Baseline | |||||||||||
| Test | |||||||||||
| Repeat |
6. Diagnose the result before changing the rule
Choose the closest pattern and support it with the evidence table. More than one pattern can apply.
- Gross rose but net barely changed: platform fees, fuel, other costs, or extra distance absorbed much of the additional fare.
- Net rose but earnings per hour fell: the shift produced more money by using more time. The rule may not have improved efficiency.
- Net per trip rose but the goal was missed: waiting for unusually strong dispatches may have reduced trip volume and left productive time unused.
- Trips rose while rating weakened: a volume-focused rule, high fatigue, or rushed service may have traded quality for output.
- Fuel cost or distance rose quickly: long pickups, long trips, or poorly timed refuelling may be the constraint even when fares look attractive.
- The repeat changed the conclusion: time of day, dispatch mix, traffic, or random variation may be stronger than the tested rule. Narrow the claim and collect another matched run.
Which pattern best explains my result, and which numbers support it?
What competing explanation or missing evidence should I investigate?
7. Write an evidence-bounded recommendation
Claim: Which acceptance, refuelling, or rest rule should the simulated driver test next?
Evidence: Cite at least three numbers, including one earnings measure and one time, fuel, rating, or fatigue measure.
Reasoning: Explain the path from the changed rule through accepted dispatches, pickup distance, time, fuel, fees, fatigue, or rating to the result.
Tradeoff and uncertainty: What became worse, what remains unknown, and which simulation assumption limits the claim?
Next test and stop rule: What will you test next, and which simulated safety or performance result would make you pause or reverse the rule?
Teacher guide: a 50-minute trip-selection lab
- Launch—5 minutes: distinguish gross earnings, net earnings, earnings per hour, and average net per trip. Ask why the highest-fare dispatch may not be the strongest choice.
- Plan—7 minutes: pairs select the same goal and challenge mode, write one acceptance rule, identify controls, make a prediction, and set a fatigue or rating guardrail.
- Baseline—8 minutes: students use the baseline rule, explain dispatch choices aloud, end at the agreed stopping point, and copy all result fields.
- Controlled test—10 minutes: change only the selected rule and complete a matched shift. Repeat if time permits or the dispatch mix makes comparison weak.
- Calculate and diagnose—8 minutes: reconcile net earnings, calculate unit measures, and select the closest diagnosis pattern.
- Recommend—7 minutes: each student writes an individual claim with three numbers, a tradeoff, a limitation, and a stop rule.
- Debrief—5 minutes: compare strategies that raised net but reduced hourly earnings or rating. Reinforce that no earnings target overrides safety.
Suggested answers and teacher look-fors
Why can a high fare be weak? It may require a long pickup, more fuel and time, or greater fatigue and rating exposure. Strong answers compare estimated net and total distance or time instead of repeating the gross fare.
Is a strict rejection rule always better? No. A strict rule can protect fuel and unit economics but create idle time, fewer completed trips, and a missed goal. Students should explain the tradeoff with matched shift evidence.
What makes a recommendation strong? It names the tested rule, cites comparable financial and nonfinancial measures, explains a mechanism, acknowledges variable dispatches, protects a safety guardrail, and proposes a smaller next test. One simulated shift does not prove a universal strategy.
Access and participation options
When devices are limited, project one simulator and assign dispatch, finance, time-and-distance, safety, and evidence roles. Pause at each dispatch so students can calculate and vote before the operator clicks. Allow typed, dictated, or oral recommendations with the same evidence requirements, and use the accessible classroom planning guide for equivalent participation routes.
Quick 12-point assessment rubric
- Experiment design (0–3): names one changed rule, useful controls, matching stopping points, a prediction, and a safety guardrail.
- Calculations and evidence (0–3): records comparable results and correctly interprets gross, fees, costs, net, hourly return, trips, distance, rating, and fatigue.
- Business reasoning (0–3): explains a plausible rule-to-result chain and distinguishes total earnings from unit and time efficiency.
- Recommendation (0–3): supports a bounded claim with numbers, a tradeoff, model uncertainty, and a useful next test or stop rule.
For a longer assignment, use the complete 16-point simulation rubric, controlled experiment guide, and one-page decision brief template.
Safety, legal, privacy, and real-world limits
The Ride-Hailing Driver Simulator is a fictional learning model, not earnings, tax, employment, legal, insurance, vehicle, or safety advice. It omits many real costs and requirements, including vehicle depreciation, maintenance, financing, licensing, commercial or ride-hailing insurance, taxes, accessibility duties, worker classification, platform terms, local permits, background checks, and changing demand.
Never interact with a phone or worksheet while operating a real vehicle. No fare, rating, dispatch, goal, or platform incentive justifies speeding, driving while fatigued, unsafe stopping, distracted driving, unlawful discrimination, or ignoring rest and vehicle-safety needs. In real work, follow current local law and platform rules, use lawful hands-free or parked interaction, and put people’s safety ahead of income.
The classroom activity requires no account, location history, real trip record, passenger information, or personal earnings data. Use fictional names and simulation outputs. Do not ask students or workers to disclose real financial, immigration, health, employment, or platform-account information.
Ride-hailing worksheet FAQ
What should students change in the Ride-Hailing Simulator experiment?
Change one trip-acceptance rule, such as a pickup-distance limit, minimum estimated net fare, or fatigue cutoff. Keep the goal, challenge mode, and other major conditions as stable as possible.
What is the difference between gross earnings and net earnings?
Gross earnings are rider fares before deductions. Net earnings subtract platform fees, fuel cost, and other costs. The simulator's net figure is still simplified and is not the same as take-home pay in real work.
Is the trip with the highest fare always the best trip?
No. A high fare can require a long unpaid pickup, more fuel, more time, or greater fatigue and rating risk. Compare expected net contribution and time, not fare alone.
How long does the ride-hailing worksheet activity take?
A focused baseline-and-test activity takes about 30 minutes. A 50-minute lesson allows a repeated run, calculations, comparison, written recommendation, and safety debrief.
Can this simulation predict real ride-hailing income or safe driving decisions?
No. It cannot predict local demand, expenses, taxes, insurance, platform rules, legal status, accessibility duties, or safe choices. Real drivers must follow current law and put safety ahead of a simulated earnings target.