Content balancing is often required in the development and implementation of computerized adaptive tests (CATs). In the current study, we propose a modified a-stratified method, the a-stratified method with content blocking. As a further refinement of a-stratified CAT designs, the new method incorporates content specifications into item pool stratification. Simulation studies were conducted to compare the new method with three previous item selection methods: the a-stratified method; the a-stratified with b-blocking method; and the maximum Fisher information method with Sympson-Hetter exposure control. The results indicated that the refined a-stratified design performed well in reducing item overexposure rates, balancing item usage within the pool, and maintaining measurement precision, in a situation where all four procedures were forced to balance content.
|Original language||English (US)|
|Number of pages||20|
|Journal||British Journal of Mathematical and Statistical Psychology|
|State||Published - Nov 2003|
ASJC Scopus subject areas
- Statistics and Probability
- Arts and Humanities (miscellaneous)