A Study of a Network-Flow Algorithm and a Noncorrecting Algorithm for Test Assembly

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Abstract
The network-flow algorithm (NFA) of Armstrong, Jones, & Wu (1992) and the average growth approxi mation algorithm (AGAA) of Luecht & Hirsch (1992) were evaluated as methods for automated test assem bly. The algorithms were used on ACT and ASVAB item banks, with and without error in the item parameters. Both algorithms matched a target test information function on the ACT item bank, both before and after error was introduced. The NFA matched the target on the ASVAB item bank; however, the AGAA did not, even without error in this item bank. The AGAA is a noncorrecting algorithm, and it made poor item selec tions early in the search process when using the ASVAB item bank. The NFA corrects for nonoptimal choices with a simplex search. The results indicate that reason able error in item parameters is not harmful for test as sembly using the NFA or AGAA on certain types of item banks.

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