Collaborative Research: Cognitive and Neural Indicators of School-based Improvements in Spatial Problem Solving

Principal Investigator: 
Project Overview
Background & Purpose: 

This behavioral and neuroimaging study investigates the effects of spatial education embedded in a science class (Geospatial Semester; GSS) on the core spatial abilities and STEM-relevant spatial thinking of high school students. Cognitive and neural indicators will be examined for evidence of change in students participating in GSS relative to students in other advanced science courses, and to address whether integrating spatial cognition into STEM lessons can mitigate commonly identified sex differences in spatial thinking.


The study will take place with students from schools in two districts in Virginia; one diverse urban district and one large suburban district.

Research Design: 

The project uses a longitudinal, cross-sectional, and comparative research design and will generate evidence that is descriptive [observational], associative/correlational [quasi-experimental], and causal [quasi-experimental, statistical modeling, difference-in-difference]. Original data are being collected on 90 high school students enrolled in the Geospatial Semester program (and a comparison group) using school records, assessments of learning, observation [videography], and survey research [self-completion questionnaire, structured interviewer-administered questionnaire, semi-structured or informal interview] and brain imaging. Geospatial Semester (GSS), a dual enrollment high school course that uses GIS technology to teach spatial thinking, is being compared to advanced high school science courses.

Instruments or measures being used include:

  • Mental Rotation Task (Shepard & Metzler, 1971): Participants judge whether a complex figure is a rotated version of another figure. Measures dynamic spatial reasoning.
  • Embedded Figures Task (Witkin et al., 1971): A measure of static spatial reasoning in which participants identify which of two complex structures contains a presented figure element.
  • Transfer and Scientific Reasoning Assessment: Scenario-based assessment of STEM reasoning and problem solving.
  • Geospatial Thinking Scale (Huynh & Sharpe, 2013): Measurement of expertise in geoscience using real-world problems that require reasoning about spatial relations and patterns.

The difference-in-difference approach and regression models will be used to examine change in core spatial abilities and STEM-based spatial reasoning. MRI analysis will compare pre- and post-test activation in the ROIs and use machine learning classifiers. Sex differences will be examined using these methods for the behavioral and fMRI data.


Findings will be posted as they become available.