Journal of Intelligence (Oct 2023)

Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory

  • Mitchell E. Munns,
  • Chuanxiuyue He,
  • Alexis Topete,
  • Mary Hegarty

DOI
https://doi.org/10.3390/jintelligence11110205
Journal volume & issue
Vol. 11, no. 11
p. 205

Abstract

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Spatial ability is important for success in STEM fields but is typically measured using a small number of tests that were not developed in the STEM context, have not been normed with recent samples, or have not been subjected to modern psychometric analyses. Here, an approach to developing valid, reliable, and efficient computer-based tests of spatial skills is proposed and illustrated via the development of an efficient test of the ability to visualize cross-sections of three-dimensional (3D) objects. After pilot testing, three measures of this ability were administered online to 498 participants (256 females, aged 18–20). Two of the measures, the Santa Barbara Solids and Planes of Reference tests had good psychometric properties and measured a domain-general ability to visualize cross-sections, with sub-factors related to item difficulty. Item-level statistics informed the development of the refined versions of these tests and a combined measure composed of the most informative test items. Sex and ethnicity had no significant effects on the combined measure after controlling for mathematics education, verbal ability, and age. The measures ofcross-sectioning ability developed in the context of geology education were found to be too difficult, likely because they measured domain knowledge in addition to cross-sectioning ability. Recommendations are made for the use of cross-section tests in selection and training and for the more general development of spatial ability measures.

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