Using subject-matter experts to assess content representation: An MDS analysis

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 con-tent domains listed in the test blueprints. The similar-ity ratings were analyzed using multidimensional scaling (MDS); the item relevance ratings were ana-lyzed 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 repre-sentation than did using either approach alone. The implications of the procedure for test validity are dis-cussed and suggestions for future research are provided. Index terms: construct validity, content validity, cluster analysis, multidimensional scaling, subject-matter experts, test construction. Adequate representation of the content domain measured is a fundamental requirement of educational and psychological testing. To evaluate content domain representation, subject-matter experts (semes) are typi-cally required to rate the relevance of test items to one or more of the content domains comprising a test blue