Abstract
When we draw, we are depicting a rich mental representation reflecting a memory, percept, schema, imagination, or feeling. In spite of the abundance of data created by drawings, drawings are rarely used as an output measure in the field of psychology, due to concerns about their large variance and their difficulty of quantification. However, recent work leveraging pen-tracking, computer vision, and online crowd-sourcing has revealed new ways to capture and objectively quantify drawings, to answer a wide range of questions across fields of psychology. Here, I present a tutorial on modern methods for drawing experiments, ranging from how to quantify pen-and-paper type studies, up to how to administer a fully closed-loop online experiment. I go through the concrete steps of designing a drawing experiment, recording drawings, and objectively quantifying them through online crowd-sourcing and computer vision methods. Included with this tutorial are code examples at different levels of complexity and tutorials designed to teach basic lessons about web architecture and be useful regardless of skill level. I also discuss key methodological points of consideration, and provide a series of potential jumping points for drawing studies across fields in psychology. I hope this tutorial will arm more researchers with the skills to capture these naturalistic snapshots of a mental image.
Highlights
A key goal of psychological research is to understand the mind and brain through observations of behavior
There are fundamental questions that cannot be answered by single-value outputs, such as the content of one’s mental representations for an item
We have provided participants with colored pencils, and found that individuals with aphantasia use less color than those with typical imagery (Bainbridge, Pounder, et al, 2021a)
Summary
A key goal of psychological research is to understand the mind and brain through observations of behavior. You can track the movements they make before undoing or clearing data, which can capture drawing errors, or navigations away from the task Attached to this tutorial, we include code examples for four drawing experiments with increasing complexity, designed so that the code can be flexibly adapted for the reader’s uses, and designed to teach some basic principles about web programming and architecture (Fig. 3). Outside of the drawing task, I recommend collecting basic demographic questions about artistic experience (i.e., years of artistic training, ratings of one’s own drawing ability, occupation) in order to quantify individual variability in performance We used these measures to demonstrate that individuals with aphantasia showed memory-specific deficits in their drawings,. Drawings can often capture more vivid visual details than other methods such as verbal report
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