Record:   Prev Next
Author Song, Tian
Title The effect of fitting a unidimensional IRT model to multidimensional data in content-balanced computerized adaptive testing
book jacket
Descript 74 p
Note Source: Dissertation Abstracts International, Volume: 72-01, Section: A, page: 0167
Adviser: Mark Reckase
Thesis (Ph.D.)--Michigan State University, 2010
This study investigates the effect of fitting a unidimensional IRT model to multidimensional data in content-balanced computerized adaptive testing (CAT). Unconstrained CAT with the maximum information item selection method is chosen as the baseline, and the performances of three content balancing procedures, the constrained CAT (CCAT), the modified multinomial model (MMM), and the modified constrained CAT (MCCAT), are evaluated in terms of measurement precision, item pool utilization and item exposure control. Three simulation factors are considered: (1) multidimensional structure; (2) ability distribution; and (3) difficulty level of content areas. Simulation results show that overall the content balancing methods are similar to or even better than the maximum information method in terms of measurement precision, especially when the content areas have uneven difficulty levels. However, there is no significant difference in item pool usage and item exposure control. Finally, overall the three content balancing methods perform very similarly, but MMM has the most efficient item pool usage
School code: 0128
Host Item Dissertation Abstracts International 72-01A
Subject Education, Tests and Measurements
Education, Technology of
0288
0710
Alt Author Michigan State University
Record:   Prev Next