Mental animation: Inferring motion from static diagrams of mechanical systems.

Hegarty, M. (1992). Mental animation: Inferring motion from static diagrams of mechanical systems. Journal of Experimental Psychology: Learning, Memory and Cognition, 18(5) 1084-1102

Reaction-time and eye-fixation data are analyzed to investigate how people infer the kinematics of simple mechanical systems (pulley systems) from diagrams showing their static configuration. It is proposed that this mental animation process involves decomposing the representation of a pulley system into smaller units corresponding to the machine components and animating these components in a sequence corresponding to the causal sequence of events in the machine's operation. Although it is possible for people to make inferences against the chain of causality in the machine, these inferences are more difficult, and people have a preference for inferences in the direction of causality. The mental animation process reflects both capacity limitations and limitations of mechanical knowledge.

Following the theme of yesterday's post this is another non-PL research paper that explores cognitive factors that might be relevant to programming language design.

The research in the paper nicely illustrates how different accounts of the cognitive processes involved in reasoning about the behavior of a mechanical system or model can be compared experimentally. The results suggest the types of inferences that are involved in mental animation of the type requested from the subjects, and how they are orchestrated.

The first section of the paper provides the general framework, and explains the notion of mental animation. A discussion of the generality of the results can be found at the end of the paper.

Those who find my last two posts too far removed from PL issues need not worry; I am not going to post more research of this type soon. Those who are intrigued by this research will be happy to know that a lot more is available where this came from.

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if there is a problem

If there is a problem with PL's, maybe its that language designers haven't been able to incorporate research of this type. I think the machine side is is much better understood than the person side, so there is at least an outside chance the next good big idea targets the brain rather than the code. This is great stuff, thanks.