Optimal testlet pool assembly for multistage testing designs

Computerized multistage testing (MST) designs require sets of test questions (testlets) to be assembled to meet strict, often competing criteria. Rules that govern testlet assembly may dictate the number of questions on a particular subject or may describe desirable statistical properties for the test, such as measurement precision. In an MST design, testlets of differing difficulty levels must be created. Statistical properties for assembly of the testlets can be expressed using item response theory (IRT) parameters. The testlet test information function (TIF) value can be maximized at a specific point on the IRT ability scale. In practical MST designs, parallel versions of testlets are needed, so sets of testlets with equivalent properties are built according to equivalent specifications. In this project, the authors study the use of a mathematical programming technique to simultaneously assemble testlets to ensure equivalence and fairness to candidates who may be administered different testlets.