The multistage testing (MST) has drawn increasing attention as a balanced format of adaptive testing that takes advantages of both fully-adaptive computerized adaptive testing (CAT) and paper-and-pencil (P\&P) tests. Most previous studies on MST have focused on purely dichotomous or polytomous item formats although the mixture of two item types (i.e., mixed-format) provides desirable psychometric properties by combining the strength of both item types. Given the dearth of studies investigating the characteristics of mixed-format MST, the current study conducted a simulation to identify important design factors impacting the measurement precision of mixed-format MST. The study considered several factors-namely, total points (40 and 60), MST structures (1-2-2 and 1-3-3), the proportion of polytomous items (10%, 30%, 50% and 70%), and the routing module design (purely dichotomous and a mixture of dichotomous and polytomous items) resulting in 32 total conditions. A total of 100 replications were performed, and 1,000 normally distributed examinees were generated in each replication. The performance of MST was evaluated in terms of the precision of ability estimation across the wide range of the scale. The study found that the longer test produced greater measurement precision while the 1-3-3 structure performed better than 1-2-2 structure. In addition, a larger proportion of polytomous items resulted in lower measurement precision through the reduced test information during the test construction. The interaction between the large proportion of polytomous items and the purely dichotomous routing module design was identified. Overall, the two factors of test length and the MST structure impacted the ability estimation, whereas the impact of the proportion of polytomous items and routing module design mirrored the item pool characteristic. / text
Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/31011 |
Date | 08 September 2015 |
Creators | Park, Ryoungsun |
Contributors | Dodd, Barbara Glenzing |
Source Sets | University of Texas |
Language | English |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
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