This study investigated the effect of using
multidimensional items in a computerized adaptive
test (CAT) setting which assumes that all items are
unidimensional. Previous research has suggested
that the composite of multidimensional abilities
being estimated by a unidimensional IRT model is
not constant throughout the entire unidimensional
ability scale (Reckase, Carlson, Ackerman, &
Spray, 1986). Results of this study suggest that
unidimensional calibration of multidimensional
data tends to "filter out" the multidimensionality.
Items that measured a θ₁,θ₂ composite similar to
the composite of the calibrated unidimensional θ
scale had larger estimated unidimensional
discrimination values. These items thus had a
greater probability of being administered in a CAT
where only the most informative items are selected.
Results also suggest that if a CAT item pool
contains items from several content areas
measuring dissimilar θ₁,θ₂ composites, different
unidimensional abilities may receive disparate
proportions of items from the various content
areas. Index terms: adaptive testing, item response
theory, multidimensionality, parallel tests, test
Ackerman, Terry A. (1991). The use of unidimensional parameter estimates of multidimensional items in adaptive testing. Applied Psychological Measurement, 15, 13-24. doi:10.1177/014662169101500103
Ackerman, Terry A..
The use of unidimensional parameter estimates of multidimensional items in adaptive testing..
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital Conservancy may be subject to additional license and use restrictions applied by the depositor.