I Visualization Strategies: Mental Simulations
These strategies set mental imagery in motion to help students think about a system.
Mental Simulations: Mental imagery that is animated and simulates some process in the real world. This imagery can include visual, tactile, and/or kinesthetic components (as when imagining how it would feel to exert a force).
There are several strategies teachers use to help students animate their mental imagery. Using this kind of imagery can help students visualize processes in a system, make predictions about what will happen next in a system, and visualize what kinds of behavior their models predict:
- Suggest that students imagine a system in motion.
- Describe forces or movements as though they were conducted by a person.
- Or simply ask students what will happen next, to elicit a prediction or explanation.
Example 1: Suggest that students imagine a system in motion Teacher: Can you imagine the blood moving through these capillaries? |
Example 1. |
Example 2: Describe forces or movements as though they were conducted by a person A faulty model of the human circulatory system was on the board in front of the room, parts of it drawn in colored chalk. (Re-created on the right.) It showed the lungs, the heart, and some blood vessels. At the bottom was a capillary bed, where the red and blue vessels meet. An enlarged version of a capillary bed was also drawn on the board (Example 1). A powerful way to reason about the pros and cons of such a model is to imagine how it would function as compared to other circulatory designs. There are multiple constraints: all cells in the body need the freshest blood possible, but this is counterbalanced by how much work the heart has to do to get the blood around the entire circuit. When talking about this figure, the teacher said the following (edited for clarity). Teacher: Imagine you were the heart pushing all that blood around the loop and back up through the lungs. And then the blood gets back to you and you push it around again. What if the vein went straight back to the heart instead of going through the lungs first? Do you think it would make your job easier or harder? Would it be easier or harder for you to push the blood all the way around?
Example 3: Ask students what will happen next Teacher: Imagine the blood in this diagram flowing down out of the heart ("mover") and back up. What do you think will happen to the speed of the blood as it goes through these tiny blood vessels at the bottom? (Points to “capillary bed” at bottom of diagram and then to the enlarged version on the board beside it (Example 1). Student 1: It will probably slow down. Teacher: Slow down? And what will it do next? Student 2: Go slowly back up. |
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The teacher who taught the lesson above describes trying to get his students to imagine movement so that they can predict the implications of their models. In this lesson, he used many strategies to help the students animate their imagery, including drawings, gestures, and sound effects (of blood whooshing through the heart). He asked them to predict the results of the heart pumping and the blood moving through the configurations they had drawn, and then use those results to critique and improve their models.
Mental simulation is a particularly powerful strategy among the Level I Visualization Strategies and can be used at multiple points during modeling to help make sense of systems under discussion, and to help students clarify their own thinking.
Background
For more on how the visualization strategies support the rest of the framework, see these pages:
Educator's Tour - Level I
Introduction to the Full Theory
Articles, Papers and Websites
More in-depth discussion of how students and experts use imagistic simulation to support scientific reasoning:
Using imagery support strategies to develop powerful imagistic models (Price, Stephens, Clement, & Núñez-Oviedo, 2017)
Identifying teaching strategies that support thinking with imagery during model-based discussions (Stephens, Clement, Price, & Núñez-Oviedo, 2017)
Four levels of scientific modeling practices in expert thinking (Clement, 2017)