Multidimensional Test Assembly Using Mixed-Integer Linear Programming: An Application of Kullback-Leibler Information.

ABSTRACT: Many educational testing programs require different test forms with minimal or no item overlap. At the same time, the test forms should be parallel in terms of their statistical and content-related properties. A well-established method to assemble parallel test forms is to apply combinatorial optimization using mixed-integer linear programming (MILP). Using this approach, in the unidimensional case, Fisher information (FI) is commonly used as the statistical target to obtain parallelism. In the multidimensional case, however, FI is a multidimensional matrix, which complicates its use as a statistical target. Previous research addressing this problem focused on item selection criteria for multidimensional computerized adaptive testing (MCAT). Yet these selection criteria are not directly tr

SUBMITTER: Debeer D 

PROVIDER: S-EPMC6906390 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature