When do spatial abilities support student comprehension of STEM visualizations?

Scott R. Hinze, Vickie M. Williamson, Mary Jane Shultz, Kenneth C. Williamson, Ghislain Deslongchamps, David N. Rapp*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Spatial visualization abilities are positively related to performance on science, technology, engineering, and math tasks, but this relationship is influenced by task demands and learner strategies. In two studies, we illustrate these interactions by demonstrating situations in which greater spatial ability leads to problematic performance. In Study 1, chemistry students observed and explained sets of simultaneously presented displays depicting chemical phenomena at macroscopic and particulate levels of representation. Prior to viewing, the students were asked to make predictions at the macroscopic level. Eye movement analyses revealed that greater spatial ability was associated with greater focus on the prediction-relevant macroscopic level. Unfortunately, that restricted focus was also associated with lower-quality explanations of the phenomena. In Study 2, we presented the same displays but manipulated whether participants were asked to make predictions prior to viewing. Spatial ability was again associated with restricted focus, but only for students who completed the prediction task. Eliminating the prediction task encouraged attempts to integrate the displays that related positively to performance, especially for participants with high spatial ability. Spatial abilities can be recruited in effective or ineffective ways depending on alignments between the demands of a task and the approaches individuals adopt for completing that task.

Original languageEnglish (US)
Pages (from-to)129-142
Number of pages14
JournalCognitive Processing
Issue number2
StatePublished - May 2013


  • Learning
  • STEM
  • Spatial cognition
  • Visualizations

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence


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