Enhancing Pool Utilization in Constructing the Multistage Test Using Mixed-Format Tests

This study investigated a new pool utilization method of constructing multistage tests (MST) using the mixed-format test based on the generalized partial credit model (GPCM). MST simulations of a classification test were performed to evaluate the MST design. A linear programming (LP) model was applied to perform MST reassemblies based on the initial MST construction. Three subsequent MST reassemblies were performed. For each reassembly, three test unit replacement ratios (TRRs; 0.22, 0.44, and 0.66) were investigated. The conditions of the three passing rates (30%, 50%, and 70%) were also considered in the classification testing. The results demonstrated that various MST reassembly conditions increased the overall pool utilization rates, while maintaining the desired MST construction. All MST testing conditions performed equally well in terms of the precision of the classification decision.

[1]  IRTGEN: A SAS Macro Program to Generate Known Trait Scores and Item Responses for Commonly Used Item Response Theory Models , 2003 .

[2]  Richard M. Luecht,et al.  Implementing the Computer-Adaptive Sequential Testing (CAST) Framework To Mass Produce High Quality Computer-Adaptive and Mastery Tests. , 2000 .

[3]  Vicente Ponsoda,et al.  A Comparison of Item Exposure Control Methods in Computerized Adaptive Testing , 1998 .

[4]  Liane Nicole Patsula,et al.  A comparison of computerized adaptive testing and multi-stage testing. , 1999 .

[5]  Richard M. Luecht,et al.  A Testlet Assembly Design for Adaptive Multistage Tests , 2006 .

[6]  William R. Koch,et al.  An Investigation of Procedures for Computerized Adaptive Testing Using Partial Credit Scoring , 1989 .

[7]  Ellen Boekkooi-Timminga Simultaneous test construction by zero-one programming , 1986 .

[8]  Ryoungsun Park,et al.  JPLEX: Java Simplex Implementation With Branch-and-Bound Search for Automated Test Assembly , 2011 .

[9]  Willem J. van der Linden,et al.  Linear Models for Optimal Test Design , 2005 .

[10]  Richard M. Luecht,et al.  Some Practical Examples of Computer‐Adaptive Sequential Testing , 1998 .

[11]  Martha L. Stocking,et al.  A Method for Severely Constrained Item Selection in Adaptive Testing , 1992 .

[12]  Identifiers California,et al.  Annual Meeting of the National Council on Measurement in Education , 1998 .

[13]  F. Lord PRACTICAL APPLICATIONS OF ITEM CHARACTERISTIC CURVE THEORY , 1977 .

[14]  Kadriye Ercikan,et al.  Calibration and Scoring of Tests With Multiple-Choice and Constructed-Response Item Types , 1998 .

[15]  April L Zenisky,et al.  Evaluating the effects of several multi -stage testing design variables on selected psychometric outcomes for certification and licensure assessment , 2004 .

[16]  Anthony R. Zara,et al.  Procedures for Selecting Items for Computerized Adaptive Tests. , 1989 .

[17]  E. Muraki A GENERALIZED PARTIAL CREDIT MODEL: APPLICATION OF AN EM ALGORITHM , 1992 .

[18]  F. Samejima Weakly parallel tests in latent trait theory with some criticisms of classical test theory , 1977 .