generalized mental rotation or other stages of image processing. Thus, for example, we do not know whether the expertise of an architect at visualizing buildings from different perspectives and in various configurations would transfer to skill at visualizing molecular structures or geological structures.

The research most relevant to this question focused on video game experts (Greenfield et al., 1994; Sims and Mayer, 2002). Sims and Mayer compared college students highly skilled at Tetris with those who were not so skilled. Tetris is a computer game in which success depends on rotating shapes so that later-appearing shapes interlock cleanly with earlier-appearing shapes. The game begins with a blank screen; one of seven shapes appears at the top of the screen and descends toward the bottom. During its descent the goal is to rotate and translate the shape, so that when it reaches the bottom of the screen it is in position to fit nicely with the shapes that follow in a continuous series. Speed is a critical factor; players have to anticipate how much to rotate shapes to fit them together.

Experts are rapid and accurate in deciding how much to rotate shapes to optimize fit. Sims and Mayer (2002) wanted to find out whether high levels of skill at mentally rotating Tetris shapes would transfer to rotating other shapes in the Tetris context. Results show a limited amount of near transfer: experts were better able than novices to play a Tetris-like game in rotating shapes that—although not identical to the shapes used in Tetris—were very similar to them. However, there was no evidence for far transfer. That is, experts did not show the same advantage in rotating shapes that were unlike those used in Tetris (even when those shapes were familiar from another context such as capital letters).

Based on laboratory studies, pattern learning and spatial transformations such as mental rotation are relatively domain specific. Learning to recognize and classify types of spatial patterns that characterize one field of expertise does not transfer when trying to learn other types of spatial patterns from another field. The benefits of practicing transformations of spatial patterns that characterize one field of study do not seem to transfer to other fields.

4.2.5 A Model of the Acquisition of Expertise in Spatial Thinking

A model of the acquisition of expertise in spatial thinking involves at least four components:

  1. Domain-specific long-term memory of patterns: in order to learn to identify patterns in a knowledge domain more rapidly and accurately, one needs to study those particular shapes. There is little or no benefit from studying one set of shapes in perceiving another set of shapes.

  2. However, perceptual learning of patterns goes hand in hand with the meta-cognitive knowledge that (a) patterns can be multiply classified and (b) studying patterns and practicing pattern identification makes those patterns come faster and more readily to mind when they are relevant to a task.

  3. Domain-specific mental transformations of patterns in working memory: in order to learn to imagine how molecular structures will appear when rotated or expanded, one needs to practice mentally transforming those structures and highly similar ones. In order to learn to imagine the cross sections resulting from folds and structural events theorized within plate tectonics, one needs to practice those mental transformations for those types of patterns.

  4. However, practice in mental transformation goes hand in hand with the meta-cognitive knowledge that such practice (a) pays off and (b) makes it easier to think and reason within that domain.

This position on the acquisition of expertise in spatial thinking has two possible sets of implications for the design of K–12 programs to foster spatial thinking. One approach builds on the first

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