QuantumLearning Machines
LabPathDepth expansion

Mathematics LabPath

A full mathematics path where students learn by manipulating quantities, structures, graphs, proofs, and models until reasoning is visible.

10/10depth gate
8course units
24mission labs
8domain engines
What must be true

The course must teach, simulate, assess, and adapt.

Mode-native engines

Each domain gets its own controls, models, and evidence.

Number Sense Manipulative Lab

Make place value, fractions, ratios, and operations tactile.

Controls
compose unitssplit wholesdrag ratio blocksregroupcompare magnitude
rational-number and base-ten invariant checks

Algebra Transformation Engine

Show equations as balanced systems with legal transformations.

Controls
move termscale both sidesfactorexpandtest solution
symbolic equivalence, inverse operations, domain checks

Function Graph Dynamics Lab

Connect parameters, graphs, tables, stories, and rates.

Controls
drag parametermove pointanimate inputcompare functionstrace rate
function evaluation, transformations, finite differences, asymptote/intercept checks

Geometry Proof Studio

Make conjecture, construction, invariants, and proof dependencies visible.

Controls
drag vertexconstruct linemark congruenttest invariantbuild proof chain
constraint geometry, congruence/similarity invariants, proof graph validation

Statistics Simulation Lab

Turn sampling, variation, bias, inference, and causation into repeated simulations.

Controls
sample populationchange biasbootstraprandomizeinspect interval
sampling distributions, bootstrap/randomization approximation, correlation checks

Calculus Rate And Area Engine

Make derivative, integral, accumulation, and differential models visible.

Controls
move tangentshrink intervalaccumulate areachange rate lawsolve flow
finite-difference derivative, Riemann accumulation, Euler approximation

Discrete Network Lab

Represent counting, logic, graph theory, algorithms, and finite systems.

Controls
connect nodescount pathstoggle conditionrun algorithmfind counterexample
graph traversal, combinatorics counting, truth-table checks, recurrence simulation

Modeling And Optimization Lab

Turn messy situations into variables, constraints, objectives, and defended decisions.

Controls
choose variablesset constraintchange objectiverun scenariocompare tradeoff
linear/nonlinear objective scoring, sensitivity and constraint checks
Full course map

Eight units. Twenty-four labs. Evidence every week.

TeacherOS

Daily intervention CTA

  • Group students by structural misconception rather than wrong answer.
  • Recommend one targeted manipulative/proof/modeling task.
  • Create a Studio assessment that requires reasoning evidence.
  • Generate TeachProof practice for explaining the misconception Socratically.
District / university

Evidence rollup

  • Math growth by concept adjacency and prerequisite repair.
  • Reasoning evidence across representations.
  • Misconception resolution in algebra, functions, geometry, statistics, and calculus.
  • College readiness through modeling, proof, and transfer.