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Explaining and Controlling for the Psychometric Properties of Computer-Generated Figural Matrix Items

Westfälische Wilhelms-Universität Münster, Germany, pafreund{at}uni-muenster.de

Stefan Hofer

Bundesagentur für Arbeit, Nürnberg, Germany

Heinz Holling

Westfälische Wilhelms-Universität Münster, Germany

Figural matrix items are a popular task type for assessing general intelligence (Spearman's g). Items of this kind can be constructed rationally, allowing the implementation of computerized generation algorithms. In this study, the influence of different task parameters on the degree of difficulty in matrix items was investigated. A sample of N = 169 participants (all age groups) completed a set of 25 automatically generated 4 x 4 matrix items. Data collection was conducted through the World Wide Web. All items showed a good fit with the Rasch model, and item difficulty could be explained reasonably well through the implemented task parameters. The research indicated that matrix items can easily be generated using well-defined computerized algorithms. Their composite character explains item difficulty to a satisfactory degree and enables researchers to construct items with anticipated psychometric properties and Rasch model conformity. Practical advantages of these findings are pointed out.

Key Words: automatic item generation • figural matrix items • item task parameters • LLTM • Rasch model

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