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

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, re...

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Autores principales: Munns, Mitchell E., He, Chuanxiuyue, Topete, Alexis, Hegarty, Mary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672093/
https://www.ncbi.nlm.nih.gov/pubmed/37998704
http://dx.doi.org/10.3390/jintelligence11110205
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author Munns, Mitchell E.
He, Chuanxiuyue
Topete, Alexis
Hegarty, Mary
author_facet Munns, Mitchell E.
He, Chuanxiuyue
Topete, Alexis
Hegarty, Mary
author_sort Munns, Mitchell E.
collection PubMed
description 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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spelling pubmed-106720932023-10-28 Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory Munns, Mitchell E. He, Chuanxiuyue Topete, Alexis Hegarty, Mary J Intell Article 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. MDPI 2023-10-28 /pmc/articles/PMC10672093/ /pubmed/37998704 http://dx.doi.org/10.3390/jintelligence11110205 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Munns, Mitchell E.
He, Chuanxiuyue
Topete, Alexis
Hegarty, Mary
Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory
title Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory
title_full Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory
title_fullStr Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory
title_full_unstemmed Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory
title_short Visualizing Cross-Sections of 3D Objects: Developing Efficient Measures Using Item Response Theory
title_sort visualizing cross-sections of 3d objects: developing efficient measures using item response theory
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672093/
https://www.ncbi.nlm.nih.gov/pubmed/37998704
http://dx.doi.org/10.3390/jintelligence11110205
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