Computer Software Review: Conducting Automated Test Assembly Using the Premium Solver Platform Version 7.0 With Microsoft Excel and the Large-Scale LP/QP Solver Engine Add-In

Cor, Ken; Alves, Cecilia; Gierl, Mark J.

doi:10.1177/0146621608316603

Cited by 13 publications

(10 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, cheaper alternatives are rapidly becoming available. Two quite affordable solvers available as add‐ins for Microsoft Excel have recently been evaluated for different types of test assembly in Cor et al (2008, 2009). Also, a new, much more powerful version of the classical solver lp_solve (version 5.5) is now available as freeware.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Automated Test-Form Generation

Linden¹,

Diao²

2011

Journal of Educational Measurement

View full text Add to dashboard Cite

In automated test assembly (ATA), the methodology of mixed‐integer programming is used to select test items from an item bank to meet the specifications for a desired test form and optimize its measurement accuracy. The same methodology can be used to automate the formatting of the set of selected items into the actual test form. Three different cases are discussed: (i) computerized test forms in which the items are presented on a screen one at a time and only their optimal order has to be determined; (ii) paper forms in which the items need to be ordered and paginated and the typical goal is to minimize paper use; and (iii) published test forms with the same requirements but a more sophisticated layout (e.g., double‐column print). For each case, a menu of possible test‐form specifications is identified, and it is shown how they can be modeled as linear constraints using 0–1 decision variables. The methodology is demonstrated using two empirical examples.

show abstract

Section: Resultsmentioning

confidence: 99%

“…1–9). In addition, introductions to ATA and a few worked examples can be found in Cor, Alves, and Gierl (2008, 2009). For readers not familiar with the methodology, a brief example is given in the .…”

mentioning

confidence: 99%

Automated Test-Form Generation

Linden¹,

Diao²

2011

Journal of Educational Measurement

View full text Add to dashboard Cite

show abstract

“…Although free-version solvers are available, such as the standard solver built in to Microsoft Excel 2007 (Cor, Alves, & Gierl, 2008, limits on decision variables and constraints make them unsuitable for handling most real test assembly problems. Moreover, while researchers can write their own MIP code in any programming language, such an undertaking is usually very complicated and time consuming.…”

Section: A Brief Review Of Optimization Approaches In Atamentioning

confidence: 99%

Item Selection for the Development of Parallel Forms From an IRT-Based Seed Test Using a Sampling and Classification Approach

Chen

Chang

Wu³

2012

Educational and Psychological Measurement

View full text Add to dashboard Cite

Two sampling-and-classification–based procedures were developed for automated test assembly: the Cell Only and the Cell and Cube methods. A simulation study based on a 540-item bank was conducted to compare the performance of the procedures with the performance of a mixed-integer programming (MIP) method for assembling multiple parallel test forms. The study investigated the statistical equivalence of the forms generated by the three test assembly methods (Cell Only, Cell and Cube, and MIP) in terms of test information functions, test characteristic curves, mean square deviations, and practical constraints, such as content balancing and nonoverlap among forms. The results indicated that the 13-point MIP method outperformed the other two methods in terms of the “closeness” test information functions between the reference form and the assembled parallel tests. Regarding test characteristic curves, the Cell Only and Cell and Cube methods yielded more similar test characteristic curves than the MIP method. Constraining test information functions apparently does not guarantee that the assembled forms will yield similar test characteristic curves. Overall, the Cell Only and Cell and Cube methods have the potential to provide results similar to the optimization approach.

show abstract

“…The Premium Solver Platform with the Large-Scale LP Solver Engine is used as the LP solver tool [8]. However, since the test specification for the parallel tests with the identical test specification is more difficult and the item bank size is up to 4000, the experimental results show that LP takes a week to construct a single Table 3.…”

Section: The Random Test Specification For the Absolute Tif Problemmentioning

confidence: 99%

Simultaneously construct IRT-based parallel tests based on an adapted CLONALG algorithm

Chang

Shiu

2011

Appl Intell

View full text Add to dashboard Cite

The simultaneously construct IRT-based (Item Response Theory) parallel tests problem requires large numbers of variables and constraints, which leads to high computational complexities and now there is no polynomial time algorithm that exists for finding the optimal solution. This article proposes an adapted CLONALG algorithm to simultaneously construct IRT-based parallel tests. Based on the CLONALG features, the proposed scheme can use a single test construction model to simultaneously construct multiple parallel tests. At the same time, it avoids the inequality problem in the sequential construction and solves the drawback of larger numbers of variables and constraints in the simultaneous construction. The serial experiments show that the proposed scheme has a lower deviation in simultaneously constructing parallel tests than the Linear Programming (LP) and the Genetic Algorithm (GA). It is also able to construct parallel tests with identical test specifications from a large item bank.

show abstract

Computer Software Review: Conducting Automated Test Assembly Using the Premium Solver Platform Version 7.0 With Microsoft Excel and the Large-Scale LP/QP Solver Engine Add-In

Cited by 13 publications

References 3 publications

Automated Test-Form Generation

Automated Test-Form Generation

Item Selection for the Development of Parallel Forms From an IRT-Based Seed Test Using a Sampling and Classification Approach

Simultaneously construct IRT-based parallel tests based on an adapted CLONALG algorithm

Contact Info

Product

Resources

About