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. After a short delay, they were asked to detect a change (colors swapping positions) within a rotated second view. In change trials, the second display always had an asymmetrical structure. The presence of symmetry in the initial view improved change detection, and performance also declined with angular disparity of the encoding and test displays. People with higher spatial ability performed better on the change-detection task, but there was no evidence that they were better at leveraging symmetry than low-spatial individuals. The results suggest that leveraging symmetrical structures can help people of all ability levels exceed typical working memory limits by constructing more efficient representations and substituting resource-demanding mental rotation operations with alternative orientation-independent strategies.

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. Science, technology, engineering and mathematics (STEM) experts are tasked with reasoning with representations of three-dimensional (3D) connected objects, raising questions about whether those stimuli would be subject to the same limits. Here, we use a color change detection task to examine working memory capacity for 3D objects made up of differently colored cubes. Experiment 1a shows that increasing the number of parts of an object leads to less sensitivity to color changes, while change-irrelevant structural dimensionality (the number of dimensions into which parts of the structure extend) does not. Experiment 1b shows that sensitivity to color changes decreases similarly with increased complexity for multipart 3D connected objects and disconnected 2D squares, while sensitivity is slightly higher with 3D objects. Experiments 2a and 2b find that when other stimulus characteristics, such as size and visual angle, are controlled, change-irrelevant dimensionality and connectivity have no effect on performance. These results suggest that detecting color changes on 3D connected objects and on displays of isolated 2D stimuli are subject to similar set size effects and are not affected by dimensionality and connectivity when these properties are change-irrelevant, ruling out one possible explanation for scientists' advantages in storing and manipulating representations of complex 3D objects.

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. Participants briefly saw 4 colored shapes, either all distinct or with repetitions of color, shape, or paired Color + Shape (e.g., two green squares among a blue triangle and a yellow diamond), with a concurrent verbal suppression task. Participants reported potential swaps (change/no change) in a rotated view. In Experiments 1a through 1c, repeating features improved performance for color, shape, and paired Color + Shape. Critically, Experiments 2a and 2b found that the benefits of repetitions were most pronounced when the repeated objects shared both feature dimensions (i.e., two green squares). When color and shape repetitions were split across different objects (e.g., green square, green triangle, red triangle), the benefit was reduced to the level of a single redundant feature, suggesting that feature-based grouping underlies the redundancy benefit. Visual compression is an effective encoding strategy that can spatially tag features that repeat. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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. Thus, many psychological researchers have embraced an interdisciplinary approach to studying spatial thinking with the aim of understanding the nature of this skill set as it occurs within STEM disciplines. In a parallel effort, discipline-based education researchers specializing in STEM domains have focused much of their research on understanding how to bolster students' skills in completing domain-specific spatial tasks. In this paper, we discuss four lessons learned from these two programs of research to enhance the field's understanding of spatial thinking in STEM domains. We demonstrate each contribution by aligning findings from research on three distinct STEM disciplines: structural geology, surgery, and organic chemistry. Lastly, we discuss the potential implications of these contributions to STEM education.

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. Here, we describe two studies that explore student accuracy at detecting color changes in visual stimuli from the discipline of chemistry. We demonstrate that both naive and novice chemistry students' encoding of visuospatial information is affected by how information is visually structured in "chunks" prevalent across chemistry representations. In both studies we show that students are more accurate at detecting color changes within chemistry-relevant chunks compared to changes that occur outside of them, but performance was not affected by the dimensionality of the structure (2D vs 3D) or the presence of redundancies in the visual representation. These studies support the hypothesis that strategies for chunking the spatial structure of information may be critical tools for transcending otherwise severely limited visuospatial capacity in the absence of expertise.

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. However, the chemical sciences have a unique problem in that chemists deal with the unseen world of the atomic-molecular level. Using sketches, chemists strive to develop causal mechanisms that emerge from the structure and behavior of molecular-level entities, to explain observations of the macroscopic visible world. Interpreting these representations and constructing sketches of molecular-level processes is a crucial component of student learning in the modern chemistry classroom. Sketches also serve as an important component of assessment in the chemistry classroom as student sketches give insight into developing mental models, which allows instructors to observe how students are thinking about a process. In this paper we discuss how sketching can be used to promote such model-based reasoning in chemistry and discuss two case studies of curricular projects, CLUE and The Connected Chemistry Curriculum, that have demonstrated a benefit of this approach. We show how sketching activities can be centrally integrated into classroom norms to promote model-based reasoning both with and without component visualizations. Importantly, each of these projects deploys sketching in support of other types of inquiry activities, such as making predictions or depicting models to support a claim; sketching is not an isolated activity but is used as a tool to support model-based reasoning in the discipline.