Symmetry and spatial ability enhance change detection in visuospatial structures.

Science, Technology, Engineering, and Mathematics (STEM) domains require people to recognize and transform complex visuospatial displays that appear to vastly exceed the limits of visuospatial working memory. Here, we consider possible domain-general mechanisms that may explain this advantage: capitalizing on symmetry, a structural regularity that can produce more efficient representations. Participants briefly viewed a structure made up of three-dimensional connected cubes of different colors, which was either asymmetrical or symmetrical.

Visual working memory for connected 3D objects: effects of stimulus complexity, dimensionality and connectivity.

Visual working memory (VWM) is typically measured using arrays of two-dimensional isolated stimuli with simple visual identities (e.g., color or shape), and these studies typically find strong capacity limits.

Visual ZIP files: Viewers beat capacity limits by compressing redundant features across objects.

Given a set of simple objects, visual working memory capacity drops from 3 to 4 units down to only 1 to 2 units when the display rotates. But real-world STEM experts somehow overcome these limits. Here, we study a potential domain-general mechanism that might help experts exceed these limits: compressing information based on redundant visual features.

Situating space: using a discipline-focused lens to examine spatial thinking skills.

Spatial skills are an important component of success in science, technology, engineering, and math (STEM) fields. A majority of what we know about spatial skills today is a result of more than 100 years of research focused on understanding and identifying the kinds of skills that make up this skill set. Over the last two decades, the field has recognized that, unlike the spatial skills measured by psychometric tests developed by psychology researchers, the spatial problems faced by STEM experts vary widely and are multifaceted.

Visual chunking as a strategy for spatial thinking in STEM.

Working memory capacity is known to predict the performance of novices and experts on a variety of tasks found in STEM (Science, Technology, Engineering, and Mathematics). A common feature of STEM tasks is that they require the problem solver to encode and transform complex spatial information depicted in disciplinary representations that seemingly exceed the known capacity limits of visuospatial working memory. Understanding these limits and how visuospatial information is encoded and transformed differently by STEM learners presents new avenues for addressing the challenges students face while navigating STEM classes and degree programs.

Sketching the Invisible to Predict the Visible: From Drawing to Modeling in Chemistry.

Sketching as a scientific practice goes beyond the simple act of inscribing diagrams onto paper. Scientists produce a wide range of representations through sketching, as it is tightly coupled to model-based reasoning. Chemists in particular make extensive use of sketches to reason about chemical phenomena and to communicate their ideas.