Let’s leverage perception science to our advantage! (updated)

• Ever get frustrated with your students’ struggles to see patterns in the data?

• Looking for some strategies to set them up for success with seeing patterns?

• Wondering what else you can try for them to better find the pattern you want them to see?

Have to fear! It turns out there is a lot from perception science that we can leverage to our advantage to help our data users — be they K-12+ learners or our bosses or general audiences — to more easily and quickly see patterns in data that we want them to see. Let’s explore what this means.

What Perception Science has to offer…

While there are a wide range of things that we can use from Perception Sciences when creating and communicating with data, one of the easiest things to leverage to our advantage are the Gestalt Principles of Visual Perception. In the early 1900s, the Gestalt School of Psychology, which grew out of the Berlin School of Experimental Psychology, set out to discover how humans “perceive pattern, form, and organization in what we see” (Few, 2012; Andrews, 2019). Gestalt is German for “pattern.” Across numerous research studies then, and continuing to this data, researchers demonstrated that there are common ways in which we tend to group information or visuals to make sense of it all. While not all of the original conclusions have held up over time, there are many that are relevant to how we approach working with data.

There are a range of these principles, but I find that eight are particularly relevant to much of the work we do with data in the K-12+ space. First, I will explain what each of those principles are (as a note, the order in which they are presented here does not imply a hierarchy of importance but rather just an order that I was thinking about them this morning). Then I will provide some examples of how these principles can make our lives harder and easier with data.

PROXIMITY 

The proximity principle identifies our tendency to perceive objects that are physically close to each other as belonging to part of the same group, whether or not that is true or relevant to the data at hand. For example, our eyes often connect the nine dots in the 3x3 box on the left together, the three dots in the upside-down triangle on the right together, and the three dots in the triangle on the bottom right together. Our eyes group these dots together before we even know what we are looking at in the dots.

SIMILARITY

The similarity principle outlines our tendency to perceive objects of similar color, shape, size, and/or orientation as related or belonging to part of the same group, whether or not that is true or relevant to the data at hand. For example, our eyes group the blue dots together and the yellow dots together as presuming that they have something in common with one another because of their shared color. We do this before we even know what the blue and yellow colors means.

ENCLOSURE

The enclosure principle reflects our tendency to perceive objects physically enclosed together in a ways that seems to create a boundary around that which is related or belonging to part of the same group, whether or not that is true or relevant to the data at hand. For example, our eyes see the yellow dots within the blue rectangle as having something in common with one another as they are all “in the box” together. We attribute meaning to the “box” whether that is accurate or not given what we are looking at.

 CLOSURE

The closure principle points out our tendency to perceive a set of individual components as a single, recognizable shape whenever possible, whether or not that is true or relevant to the data at hand. Meaning rather than perceiving something as open and incomplete, we “fill in the space” to make things closed and complete. For example, our eyes connect the dashed lines to create a hexagon, rather than seeing the unusual nature of different dashes in space. They jump to these closed and complete shapes before we actually know what we are looking at often.

CONTINUITY

The continuity principle identifies our tendency to perceive objects that are in line with one another or seem to be a continuation of one another as part of a single whole or group, whether or not that is true or relevant to the data at hand. Our eyes search for the smoothest path to follow, thus looking for continuity among objects. For example, our brains presume that all of these blue bars share a common baseline, our eyes see that the left side of each bars aligns together. Also, our eyes perceive that the blue bars are decreasing as you go down and presume meaning to that.

CONNECTION

The connection principle points out our tendency to perceive objects that are physically connected are part of the same group, whether or not that is true or relevant to the data at hand. For example, our eyes connect the group of three shapes in the lower left together and the three shapes in the upper right together, before connecting the dots and squares together. In fact, the connection principle often is stronger than proximity or similarity principles, but not as strong as enclosure.

FIGURE & GROUND

The figure & ground principle outlines our tendency to perceive objects either in the foreground or in the background with the background having less implied meaning, whether or not that is true or relevant to the data at hand. Specifically, the figure is considered the object, shape, or person that is in focus of the visual field and where we “should” pay attention, and the ground is what is in the background and “should” be ignored. For example, our eyes perceive the yellow dots being “in front of” the blue rectangle and perceive that “in front of” quality as indicating more importance. We either ignore or downplay what is in the background, without knowing what is there.

COMMON FATE

The common fate principle reflects our tendency to perceive objects that share a direction of placement together, or seem to be moving together, as a unified group, whether or not that is true or relevant to the data at hand. For example, our eyes see the five top yellow dots from left to right as being a group increasing from left to right, and the bottom five dots as being a group staying the same from left to right. Before we know if the data are related, we begin to group these dots together in our minds.

Original data visualization published by C Chan at Reuters. Available at: https://www.businessinsider.com/gun-deaths-in-florida-increased-with-stand-your-ground-2014-2. Revised data visualization by P.A. Fedewa at Reuters. Available at: https://www.businessinsider.com/gun-deaths-in-florida-increased-with-stand-your-ground-2014-2.

So, that was an example where Gestalt Principles resulted in it being harder to make sense of the actual data, but there was no malicious intent to mislead the reader. Let’s look at an example where the Gestalt Principles can be applied to purposefully mislead a reader of what the data actually indicate. For example, the continuity and proximity principles are at play here when we make sense of these two graphs. We see a larger difference and disconnect between the grey and red bars with the graph on the left than the right and thus would start to make conclusions of differences and similarities accordingly. The trouble is that the data values of the grey and red bars are the same across both graphs, but the y-axis scale is what differs, not the actual data. The graph on the left was built and used to communicate a large difference between the grey and red bars, this is misleading from the data values at hand.

The people are grouped together to leverage the proximity principle. Available at: https://www.dummies.com/programming/big-data/big-data-visualization/applying-gestalt-theory-to-data-visualization/

The data value dots and countries are grouped together by color to leverage the similarity principle. Available at: https://vizzendata.com/2020/07/06/utilizing-gestalt-principles-to-improve-your-data-visualization-design/

The SBI, Indian Oil, and HDFC Bank are grouped together in an orange box to leverage the enclosure principle to specifically draw your eye to those data (and ordered in descending order for continuity principle). Available at: http://daydreamingnumbers.com/concepts/gestalt-laws-data-visualization/

The products are ordered in descending order to leverage the continuity principle (and the same color for the similarity principle). Available at: https://datasavvy.me/2017/12/18/design-concepts-for-better-power-bi-reports-part-3-gestalt-principles/

What are other ways that you can leverage these 8 Gestalt Principles of Visual Perception to make creating, analyzing, and communicating with data easier?