Get Your Bot Running
Setup walkthrough. Pair the Cutebot Pro, flash the starter program, confirm the bot drives.
Open makecode.microbit.org on each laptop. Load the Skills Arena project (Here is a no-copy version). Plug in USB, confirm the micro:bit mounts as a drive, hit Download. Minor code editing — open, edit, connect, flash, verify.
Phase 1 · Launch
Receive the constraint S + P + E + T = 20. Read the driving question — How do you build a winning robot when every stat is a trade-off? Connect to prior experience, then restate the driving question in your own words.
Phase 2 · Build Knowledge
Five formulas. Each one starts with a structured mini-lesson, then a hands-on test, then a data record. Speed → First Bot Drive → Teacher Hat #1 → Endurance → Distance → Turning→ Scoop Build → Power.
Bridge · Budget
See all four stats as one system. Speed is flat, Power rewards going high, Endurance and Turning sit between. Frame the 20 points as an optimization, not a preference list.
Match Code Setup
Find the code at Makecode to edit. This is where you upload the program to the bots.
Two things to locate in your project.
SPEED, POWER, ENDURANCE, TURNING. They must add to exactly 20. Use placeholder values for now.// ← YOUR CODE HERE.Teacher Hat #2 · The Facilitator Draft
3 sets of 6 Protocol Cards face up. 12 Trigger Cards face down. Four rounds: each teacher selects a partner to play Maya. After Maya draws a trigger card and enacts the situation, the teacher selectes the protocol and respons. A third teacher observes. Closes with a Steal Round — name one move you want to steal from another round.
Phase 3 · Iteration Cycle
Match 1 → Adjust → Match 2. Write a predicted result before pressing start. Run a 3-minute match. After the match, change exactly one stat — and write the formula reason before touching the code. One change, not a rebuild. Re-run and compare.
Teacher Hat #3
Write 2 minutes on the exact moment allocation got hard and the one piece of information you wished you had. Discuss: what the one-change rule does to reasoning quality, and the predict-adjust-rerun loop as the engine of all 16 days.
Four-Week Arc · Meta-Debrief
Dashboard Reveal — see what students open on Day 5 (Simulation Lab + Match Log). Then map today to the full 16-day arc, M–Th × 4 weeks: learned it · tested it · argued with it · taught it. Identify the hardest anticipated facilitation moment.
Spreadsheets & Research Data
Every recall check, diagnostic, and interleaved problem set your students submit lands in a Google Sheet shared with you. That same data flows — anonymized — to the research team. Here's how it works.
Score column.
S-XXXX token in place of each student's name. First name, last initial, and team data drop out.
Practically: grade what you want in the Score column on each source sheet — that's the number researchers see. Leave it blank and the AI's total flows through. Either way, the per-question AI scores and rationales reach the Researcher Export so the research team can analyze where students struggled, not just the final grade.
Close
Review classroom prep before you leave. "The one teaching move I am committing to in Week ___ is ____ because today I learned that ____."