A sampling and classification item selection approach with content balancing

Pei-Hua Chen*

*此作品的通信作者

研究成果: Article同行評審

6 引文 斯高帕斯(Scopus)

摘要

Existing automated test assembly methods typically employ constrained combinatorial optimization. Constructing forms sequentially based on an optimization approach usually results in unparallel forms and requires heuristic modifications. Methods based on a random search approach have the major advantage of producing parallel forms sequentially without further adjustment. This study incorporated a flexible content-balancing element into the statistical perspective item selection method of the cell-only method (Chen et al. in Educational and Psychological Measurement, 72(6), 933–953, 2012). The new method was compared with a sequential interitem distance weighted deviation model (IID WDM) (Swanson & Stocking in Applied Psychological Measurement, 17(2), 151–166, 1993), a simultaneous IID WDM, and a big-shadow-test mixed integer programming (BST MIP) method to construct multiple parallel forms based on matching a reference form item-by-item. The results showed that the cell-only method with content balancing and the sequential and simultaneous versions of IID WDM yielded results comparable to those obtained using the BST MIP method. The cell-only method with content balancing is computationally less intensive than the sequential and simultaneous versions of IID WDM.

原文English
頁(從 - 到)98-106
頁數9
期刊Behavior Research Methods
47
發行號1
DOIs
出版狀態Published - 1 1月 2015

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