Using subject-matter experts to assess content representation: An MDS analysis
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Using subject-matter experts to assess content representation: An MDS analysis
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1995
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Abstract
Demonstration of content domain representation is
of central importance in test validation. An expanded
version of the method of content evaluation proposed
by Sireci & Geisinger (1992) was evaluated with
respect to a national licensure examination and a
nationally standardized social studies achievement
test. Two groups of 15 subject-matter experts (SMEs)
rated the similarity of all item pairs comprising a test,
and then rated the relevance of the items to the content
domains listed in the test blueprints. The similarity
ratings were analyzed using multidimensional
scaling (MDS); the item relevance ratings were analyzed
using procedures proposed by Hambleton
(1984) and Aiken (1980). The SMES’ perceptions of
the underlying content structures of the tests emerged
in the MDS solutions. All dimensions were germane to
the content domains measured by the tests. Some of
these dimensions were consistent with the content
structure specified in the test blueprint, others were
not. Correlation and regression analyses of the MDS
item coordinates and item relevance ratings indicated
that using both item similarity and item relevance
data provided greater information of content representation
than did using either approach alone. The
implications of the procedure for test validity are discussed
and suggestions for future research are
provided. Index terms: construct validity, content
validity, cluster analysis, multidimensional scaling,
subject-matter experts, test construction.
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Sireci, Stephen G & Geisinger, Kurt F. (1995). Using subject-matter experts to assess content representation: An MDS analysis. Applied Psychological Measurement, 19, 241-255. doi:10.1177/014662169501900303
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doi:10.1177/014662169501900303
Suggested citation
Sireci, Stephen G.; Geisinger, Kurt F.. (1995). Using subject-matter experts to assess content representation: An MDS analysis. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/118281.
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