jsCAT: Computer Adaptive Testing in JavaScript

A library to support IRT-based computer adaptive testing in JavaScript

Installation

You can install jsCAT from npm with

npm i @bdelab/jscat

Usage

// import jsCAT
import { Cat, normal } from '@bdelab/jscat';

// declare prior if you choose to use EAP method
const currentPrior = normal();

// create a Cat object 
const cat = new CAT({method: 'MLE', itemSelect: 'MFI', nStartItems: 0, theta: 0, minTheta: -6, maxTheta: 6, prior: currentPrior})

// update the abilitiy estimate by adding test items 
cat.updateAbilityEstimate(zeta, answer);

const currentTheta = cat.theta;

const currentSeMeasurement = cat.seMeasurement;

const numItems = cat.nItems;

// find the next available item from an input array of stimuli based on a selection method

const stimuli = [{difficulty: -3, item: 'item1'}, {difficulty: -2,  item: 'item2'}];

const nextItem = cat.findNextItem(stimuli, 'MFI');

Validations

Validation of theta estimate and theta standard error

Reference software: mirt (Chalmers, 2012)

Validation of MFI algorithm

Reference software: catR (Magis et al., 2017)

References

Chalmers, R. P. (2012). mirt: A multidimensional item response theory package for the R environment. Journal of Statistical Software.

Magis, D., & Barrada, J. R. (2017). Computerized adaptive testing with R: Recent updates of the package catR. Journal of Statistical Software, 76, 1-19.

Lucas Duailibe, irt-js, (2019), GitHub repository, https://github.com/geekie/irt-js

License

jsCAT is distributed under the ISC license.