Improving measurement quality and efficiency with adaptive theory
1982
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Improving measurement quality and efficiency with adaptive theory
Authors
Published Date
1982
Publisher
Type
Article
Abstract
Approaches to adaptive (tailored) testing based on
item response theory are described and research results
summarized. Through appropriate combinations
of item pool design and use of different test
termination criteria, adaptive tests can be designed
(1) to improve both measurement quality and measurement
efficiency, resulting in measurements of
equal precision at all trait levels; (2) to improve
measurement efficiency for test batteries using item
pools designed for conventional test administration;
and (3) to improve the accuracy and efficiency of
testing for classification (e.g., mastery testing). Research
results show that tests based on
item response theory (IRT) can achieve measurements
of equal precision at all trait levels, given an
adequately designed item pool; these results contrast
with those of conventional tests which require
a tradeoff of bandwidth for fidelity/precision of
measurements. Data also show reductions in bias,
inaccuracy, and root mean square error of ability
estimates. Improvements in test fidelity observed in
simulation studies are supported by live-testing
data, which showed adaptive tests requiring half the
number of items as that of conventional tests to
achieve equal levels of reliability, and almost one-third
the number to achieve equal levels of validity.
When used with item pools from conventional tests,
both simulation and live-testing results show reductions
in test battery length from conventional tests,
with no reductions in the quality of measurements.
Adaptive tests designed for dichotomous classification
also represent improvements over conventional
tests designed for the same purpose. Simulation
studies show reductions in test length and improvements
in classification accuracy for adaptive vs.
conventional tests; live-testing studies in which
adaptive tests were compared with "optimal" conventional
tests support these findings. Thus, the research
data show that IRT-based adaptive testing
takes advantage of the capabilities of IRT to improve
the quality and/or efficiency of measurement
for each examinee.
Keywords
Description
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Weiss, David J. (1982). Improving measurement quality and efficiency with adaptive theory. Applied Psychological Measurement, 6, 473-492. doi:10.1177/014662168200600408
Suggested citation
Weiss, David J.. (1982). Improving measurement quality and efficiency with adaptive theory. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/101549.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.