Marketing, UnlockedCreated at McCombs · UT Austin
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A section that runs itself once it's set up.

The whole job is six moves: set up a section, assign archetypes once, advance each period, read student work, grade on a league-relative Performance Index, and back up. Grades push to Canvas automatically. It's free to run alongside your existing syllabus — we host.

What you actually do

Each student plays solo as one of 20 business archetypes; one chapter unlocks one lever per period. Your weekly job is small.

Welcome — a section runs itself once it's set up

mu-sim is a 19-period marketing simulation. Each student plays solo as one of 20 business archetypes; one textbook chapter unlocks one decision lever per period.

Your job each week is small: make sure students have submitted, then advance the whole section one period. This tour covers the four things you actually do.

1. Create and set up a section

Create a section to get a 6-character join code students self-join with (no email or real name collected). Distribute the code; students pick a username and password.

Section setup lets you choose the archetype pool and league size (real students per league before AI phantoms fill the rest; default 4). Fewer archetypes concentrate students into bigger, more head-to-head leagues. Use "Preview composition" to see the split before saving.

2. Assign archetypes — once, early

After most students have joined, click "Assign archetypes." This deals businesses deterministically from your section seed. Leagues then form automatically from those assignments — there's no separate button.

Do this exactly once, before Period 1. Re-running it after students have built a strategy swaps their business out from under them.

3. Advance the period

"Advance to Period N" simulates the entire section — every league — in one action, then (for Canvas-linked sections) pushes that period's grades automatically.

A student who didn't submit isn't zeroed: the engine carries their last decision forward as a "stand-pat." So check the Submitted/Not-submitted column in the drill-in when you're judging effort — "no result" never happens, but "no change" does.

4. See what students did

Standings group each league by archetype with a Performance Index per firm. Compare-by-period shows every student's decision for one period side by side. Drill into a student for their full 19-period submission history — your primary tool for grading decision quality.

Grade on Performance Index (league-relative), never on raw cash — absolute dollars just reflect which archetype a student was dealt.

Grades, backups, and the free tier

For Canvas/LTI-linked sections, grades push automatically on each advance, and you can re-push manually with "Push grades to Canvas." Performance Index (0–100) scales onto your Canvas assignment's point max.

Back up any time with Download CSV / JSON on the section page (roster, decisions, results, standings). A keepalive ping keeps the free-tier database from auto-pausing after inactivity — but the CSV/JSON export is your real safety net before anything destructive.

The practical reference

Setup, advancing periods, seeing student work, grading and Canvas grade push, and the free-tier safety net.

Set up a section

Create a section from the instructor home ("+ New section") — you'll get a 6-character join code to distribute. Students self-join at /join with a username and password; no email or real name is collected.

Open "Section setup" to choose the archetype pool and league size (real students per league before AI phantoms fill in; 2–8, default 4). Fewer archetypes → bigger, more head-to-head leagues. "Preview composition" shows the exact league split before you save. After saving, re-run "Assign archetypes" to apply it.

Assign archetypes (once)

After most students join, click "Assign archetypes." Deterministic from the section seed. Leagues form automatically from the assignment — no separate step.

This is irreversible in practice: re-running it reshuffles businesses students have already built strategies around. Do it once, before Period 1.

Advance periods

"Advance to Period N" simulates the entire section in one action — there is no per-team or per-league advance. You can advance once you've assigned archetypes.

Non-submitters are carried forward (stand-pat), not zeroed. Use the drill-in's Submitted/Not-submitted column to judge participation rather than inferring it from results.

Advancing is not designed to be "undone." Make sure the class has submitted before you advance.

See student work

Standings (/standings): each league grouped by archetype, with Performance Index, share, net income, brand, CX, and cash per firm. Phantom rows are computed live.

Compare-by-period: every student's decision for one period, side by side. Drill-in (tap a student): their full 19-period submission history and results — the primary grading tool.

Grading

Grade on Performance Index (0–100), never raw cash — dollars just reflect the archetype dealt. The design frames the sim as ~10% of a course grade; a common split is decision quality + completion + reflection carrying most of it, with a small league-relative outcome slice (e.g., PI ÷ 10).

Performance Index = ranks within a student's own league: net income 35%, market share 25%, brand equity 25%, CX 15%.

Grade push to Canvas (LTI)

For LTI-linked sections, grades push automatically on each period advance, and "Push grades to Canvas" re-pushes the latest completed period on demand. The Performance Index is scaled onto your Canvas assignment's point maximum.

The button only appears when the section is Canvas-linked. Failures are recorded in the audit log with per-student detail.

Backups & the free tier

Download CSV / JSON on the section page exports roster, every decision, results with Performance Index, and standings — enough for grading and FERPA right-to-access. Run it before finals and before anything destructive (re-assigning archetypes, re-forming cohorts).

A keepalive endpoint is pinged on a schedule so the free-tier database doesn't auto-pause after ~7 days of inactivity. Treat the CSV/JSON export (and a periodic full pg_dump — see docs/BACKUP.md) as the real safety net.

Pilot it in your section

Free for your class. Play through the demo to see what students experience, then set up a section in about 15 minutes.

Curious what students see? Read the student guide →