How Interactive Data Visualization Helps Students Learn

Some studies indicate that 83% of human learning is visual. That’s one of the reasons why interactive data visualization is such an effective method for helping students learn and retain complex concepts.

Data visualization expert Dr. Anselm Spoerri recently wrote a white paper entitled, Using Interactive Data Visualization to Promote an Active Learning Experience for Engineering Students. In it, he describes how the overall goal of data visualization is to guide users to interesting and meaningful patterns in a data set.

As Dr. Spoerri explains, the human visual system first detects edges in a visual scene that correspond to significant changes in terms of light intensity, color, texture, and motion. Next, it uses grouping principles, such as proximity, similarity, and continuity, to group these edges into objects. The human visual system is able to infer the three-dimensional structure of the visual scene, although it has as its initial input a two-dimensional array of sensory measurements that are changing over time. It is able to achieve this feat by exploiting the structure of the physical world, in which object surfaces tend to change smoothly or objects move in mostly rigid ways, to compute what we “see” in our conscious mind.

The Walking Dots animation illustrates the ability of the human visual system to compute structure from motion based on how a set of dots are moving, even when at times a “snow storm” of random dots is shown as well. The human visual system needs to solve the correspondence problem by determining where the dots have moved and it cannot just apply the proximity principle. The dots shown in the animation represent the joints (i.e. shoulder, elbow, knee, etc.) of a walking person. For example, upper and lower arms move like a pendulum and so the motion of the joints is constrained to a plane. This constraint and the fact that the human body moves in a semi-rigid way can be used to solve the correspondence problem mathematically.

This example demonstrates the amazing computational capabilities of the human visual system to perceive the structure inherent in visual patterns.

To find out more about how interactive data visualization can make it easier for your students to learn and understand complex concepts, download this free white paper: Using Interactive Data Visualization to Promote an Active Learning Experience for Engineering Students.

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