isr.adaptive.select: Returns the next items that should be assigned to the...
In yuehmeir2/CATSimulator: Library for Simulation of Adaptive Item Selection

Description Usage Arguments Value Examples

The 'adaptive' algorithm uses content balancing and item exposure algorithms to select the best item in the item pool for the given simulee.

1	isr.adaptive.select(simuleeOut, simulation)

`simuleeOut`	A tibble containing the in-progress simulee test output.
`simulation`	An object defining the test that is being run.

A list containing the selected moduleIndex, plus other values useful for understanding the selection.

1
2
3

  simulation = initSimulation(readRDS(system.file("example/passage-adaptive-wpm.rds", package = "CATSimulator")))
  simuleeOut = initSimulee(generateSimuleesByTrueTheta(-2, 10001), simulation)
  selection = isr.adaptive.select(simuleeOut, simulation)