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A Comparison of Constraint Programming and Mixed‐Integer Programming for Automated Test‐Form Generation
Author(s) -
Li Jie,
der Linden Wim J.
Publication year - 2018
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/jedm.12187
Subject(s) - disk formatting , computer science , constraint (computer aided design) , variety (cybernetics) , integer programming , constraint programming , constraint satisfaction , process (computing) , shadow (psychology) , integer (computer science) , constraint logic programming , programming language , algorithm , mathematical optimization , artificial intelligence , mathematics , psychology , geometry , probabilistic logic , stochastic programming , psychotherapist , operating system
The final step of the typical process of developing educational and psychological tests is to place the selected test items in a formatted form. The step involves the grouping and ordering of the items to meet a variety of formatting constraints. As this activity tends to be time‐intensive, the use of mixed‐integer programming (MIP) has been proposed to automate it. The goal of this article is to show how constraint programming (CP) can be used as an alternative to automate test‐form generation problems with a large variety of formatting constraints, and how it compares with MIP‐based form generation as for its models, solutions, and running times. Two empirical examples are presented: (i) automated generation of a computerized fixed‐form; and (ii) automated generation of shadow tests for multistage testing. Both examples show that CP works well with feasible solutions and running times likely to be better than that for MIP‐based applications.