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

Authors:
Ting-Yi Chang;You-Fu Shiu
Affiliations:
Graduate Institute of e-Learning, National Changhua University of Education, Changhua City, Taiwan, ROC;Graduate Institute of e-Learning, National Changhua University of Education, Changhua City, Taiwan, ROC
Venue:
Applied Intelligence
Year:
2012

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Abstract

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.