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APPLIED COGNITIVE PSYCHOLOGYAppl. Cognit. Psychol. 16: 97115 (2002)

DOI: 10.1002/acp.759

Domain Specicity of Spatial Expertise:The Case of Video Game Players

VALERIE K. SIMS1* and RICHARD E. MAYER2

1University of Central Florida, USA

2University of California, Santa Barbara, USA

SUMMARY

Two experiments examined whether video game expertise transfers to performance on measures ofspatial ability. In Experiment 1, skilled Tetris players outperformed non-Tetris players on mentalrotation of shapes that were either identical to or very similar to Tetris shapes, but not on other testsof spatial ability. The pattern of performance on those mental rotation tasks revealed that skilledTetris Players used the same mental rotation procedures as non-Tetris players, but when Tetris shapeswere used, they executed them more quickly. In Experiment 2, non-Tetris players who received 12hours of Tetris-playing experience did not differ from matched control students in pretest-to-posttestgains on tests of spatial ability. However, Tetris-experienced participants were more likely to use analternative type of mental rotation for Tetris shapes than were Tetris-inexperienced participants. Theresults suggest that spatial expertise is highly domain-specic and does not transfer broadly to otherdomains. Copyright# 2002 John Wiley & Sons, Ltd.

The search for transfer of expertise to novel tasks has a long and somewhat disappointing

history in educational and cognitive psychology (Mayer, 1987; Mayer and Wittrock,

1996). In eld studies and laboratory studies, students who learn cognitive skills in onedomain rarely are able to use those skills in another domain (e.g., Chase and Simon, 1973;

Chi et al., 1988; Larkin et al., 1980; Chi, 1978). Similarly, modern theories of intellectual

ability no longer view intelligence as a monolithic skill that determines performance on all

cognitive tasks (Sternberg, 1990). In the present two studies, we examine the nature of

cognitive transfer by focusing on the relationship between video game expertise and

performance on measures of spatial ability.

Consider a scenario in which a student spends many hours in front of a computer screen

playing a popular video game called Tetris (Gustafsson, 1988). This game begins with an

empty playing eld. On each trial of the game, one of seven possible shapes (see Figure 1)

appears at the top of the screen and descends toward the bottom as shown in Figure 2. Each

of the shapes is composed of four squares, and may be used to create walls below. The

player is allowed to press keys which will rotate the shape counterclockwise in increments

of 90 or move the shape to the right or left in increments of one column. The player's goal

is to stack the shapes such that their components create horizontal lines across the playing

eld. Whenever a line is created, it will disappear, and any blocks above it will drop down

to that level. The game continues, with shapes descending at increasingly faster rates, until

the bricks pile up to the top of the playing eld. Because this game involves speeded

Copyright # 2002 John Wiley & Sons, Ltd.

Correspondence to: V. K. Sims, Psychology Department, University of Central Florida, P.O. Box 161390,Orlando, FL 32816-1390, USA. E-mail: [email protected]

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rotation of shapes, it reasonable to examine the relationship between Tetris expertise and

spatial ability. Transfer of Tetris ability could take place on several levels. For instance, a

Tetris expert could become more skilled at performing mental rotation tasks in general, or

he or she could simply become highly familiar with the shapes presented in the game.

THREE VIEWS OF TRANSFER

To examine the transfer of Tetris expertise to performance on measures of spatial ability,

we consider three views of problem-solving transfer derived from Mayer and Wittrock's

(1996) analysis of transfer theories: transfer of general skills, transfer of specic skills, andtransfer of specic skills in context. Each of these theories also corresponds to specic

predictions about the nature of spatial ability and its susceptibility to change.

First, according to the general-skills view of transfer, learning to solve problems in

certain domains, such as video game playing, serves to improve the mind in general. Thus,

Tetris expertise should be related to performance on all tests of spatial ability, regardless of

their similarity to the game. Under this view, spatial ability is a unied ability that can be

altered through various spatial experiences. Identied as one of seven primary mental

abilities more than 50 years ago (Thurstone, 1938), spatial ability remains widely

Figure 1. Examples of shapes in Tetris

Figure 2. Example screen from Tetris. As the piece continues to fall, it will ll in the hole at thebottom, and the entire bottom row will disappear

98 V. K. Sims and R. E. Mayer

Copyright# 2002 John Wiley & Sons, Ltd. Appl. Cognit. Psychol. 16: 97115 (2002)

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recognized as one of the most basic cognitive abilities (Carroll, 1993; Lohman, 1994).

When viewed as a unied single entity, spatial ability is the ability to `generate, retain,

retrieve, and transform well-structured visual images' (Lohman, 1994, p. 1000).

Second, according to the specic-skills view of transfer, learning to play a video game

serves to improve component skills required in the game. Thus, Tetris ability should be

related to performance on all tests involving mental rotation, because mental rotation is acomponent skill required in playing Tetris, but not on tests involving non-related spatialability skills. Under this view, a given spatial skill such as mental rotation could be altered

through experience. Consistent with this view, factor-analytic studies have shown that

spatial ability consists of a collection of spatial information-processing skills including

spatial relations (SR), such as measured by mental rotation tests; visualization (VZ), such

as measured by paper folding or form board tests; closure speed (CS), such as measured by

gure-completion tests; exibility of closure (CF), such as measured by hidden gures

tests; and perceptual speed (P), such as measured by scanning or clerical checking tests

(Carroll, 1993). Thus, mental rotation may be seen as a distinct cognitive skill (Shepardand Metzler, 1971; Cooper and Shepard, 1973; Shepard and Cooper, 1982).

Third, according to the specic-skills-in-context view of transfer, experience in videogame playing serves to improve component skills using the same mental representations as

are required in the game. Thus, Tetris expertise should be related to performance on all

tests involving mental rotation of Tetris shapes, but not to mental rotation involving non-

Tetris shapes or to other tests of spatial ability. This hypothesis also suggests that spatial

skills such as mental rotation are not altered generally, but instead are able to be used more

efciently because of stored mental representations of familiar stimuli. Consistent withthis view, research has indicated that performance of mental rotation may be speeded when

familiar stimuli are used (Koriat and Norman, 1985; Mumaw et al., 1984; Tarr and Pinker,

1989). According to Mumaw et al. (1984) the familiar shapes can be processed as a whole

and therefore create less cognitive load, whereas Tarr and Pinker (1989) argue that people

store representations of familiar shapes at specic orientations which can be compared

against presented targets.

COGNITIVE EFFECTS OF VIDEO-GAME PLAYING

The empirical study of video game playing is a relatively new eld that has generally

concentrated only on the transfer of general skills and has produced somewhat mixed

results (Greeneld and Cockling, 1996). Gagnon (1985) failed to nd overall differences

on pretest-to-posttest gains in spatial ability skills between adults who received ve hours

of video game playing experience (Targ and Battlezone) and those who did not. In

contrast, Dorval and Pepin (1986) found that adults who learned to play Zaxxon across

eight sessions showed pretest-to-posttest gains on spatial relations tests whereas childrendid not. McClurg and Chaille (1987) found that playing computer games (The Factory &

Stellar 7) across 12 sessions enhanced children's mental rotation skills. Subrahmanyam

and Greeneld (1994) found that children who played a spatially oriented video game

(Marble Madness) across three sessions improved more on spatial ability tests than did

control children who played a non-spatial computer game (Conjecture).

In a study involving Tetris playing, Okagaki and Frensch (1994) found that male

undergraduates who played Tetris for six hours produced larger pretest-to-posttest gains

on two out of four spatial ability tests than did controls who did not play Tetris, whereas

Domain specicity of spatial expertise 99


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Tetris playing did not affect performance for females on any of the four spatial ability

tests. In a follow-up study, both male and female undergraduates who played Tetris for 6

hours showed greater reductions than controls in their speed of mental rotation and in their

speed on a Tetris-like form board task both for Tetris shapes and non-Tetris shapes.

Okagaki and Frensch (1994, p. 53) concluded that `the ndings presented here replicate

Subrahmanyam and Greeneld's (1994) nding that practice on a spatially oriented videogame positively affects closely related spatial skills'.

In this study, we compared the spatial ability skills of students who have high skill in

Tetris playing with those who have low skill in Tetris playing (Experiment 1) and of non-

Tetris players who received 12 hours of Tetris-playing experience and non-Tetris players

who received no Tetris-playing experience (Experiment 2).

EXPERIMENT 1

In Experiment 1, students who were skilled in playing Tetris (high-skill group) or who had

never before played Tetris (low-skill group) took a battery of nine spatial tests thatrepresent near to far transfer of Tetris expertise. The general-skills hypothesis predicts that

the high-skill group will outperform the low-skill group on all tests of spatial ability; the

specic-skills hypothesis predicts that the high-skill group will outperform the low-skill

group on mental rotation tests but not on non-related tests of spatial ability; and the

specic-skills-in-context hypothesis predicts that the high-skill group will outperform the

low-skill group on mental rotation of Tetris shapes but not on mental rotation of non-Tetris

shapes nor other non-related tests of spatial ability. A second goal of Experiment 1 was to

investigate the nature of the specic representations that a skilled Tetris player may have

acquired. Specically, we tested whether highly skilled Tetris players showed evidence of

storing mental representations of familiar stimuli. This was accomplished by examining

individual reaction time patterns to determine whether experts were particularly fast formental rotation trials involving Tetris shapes presented at the orientations presented in the

game.

Method

Participants and design

The participants were 114 undergraduate students recruited from the Psychology Subject

Pool at the University of California, Santa Barbara, who participated in this experiment to

fulll a course requirement. Sixteen of these participants were not included in the analyses

because of missing data or because they failed to reach 80% accuracy on at least one test of

mental rotation. Of the remaining 98 participants, 17 females and 36 males were in thehigh-skill group whereas 26 females and 19 males were in the low-skill group. All high-

skill students scored 60 lines or above on a test game of Tetris, with an average of 90.1 and

standard deviation of 15.0; all low-skill students scored below 60 lines on a test game of

Tetris with an average of 30.3 and a standard deviation of 16.0.

Apparatus

Five Macintosh IIci computer systems were used to present the computerized cognitive

measures. MindLab software (Meike et al., 1988) was used to present stimuli and collect



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reaction times (with a temporal resolution of 16 milliseconds), and Super Paint (Aldus

Corporation, 1993) was used to create the stimuli.

Material

The materials consisted of the black-and-white Macintosh version of the video game Tetris

(Gustafsson, 1988), as well as six computerized tasks and three paper-and-pencil tasks thatwere designed to evaluate cognitive skills that varied in their similarity to Tetris.1 Table 1lists the nine spatial ability tests used in this experiment. For each test, the table indicates

whether or not the test taps the same cognitive processes (e.g., mental rotation) and

cognitive representations (e.g., Tetris shapes) as does playing the game. The table also

indicates whether or not performance on the test is expected to be related to Tetris

expertise according to each of three theories of transfer. Figure 3 shows examples of the

different cognitive measures, and Figure 4 the specic stimuli used in the four computer-

ized mental rotation tests.

There were four Shepard/Metzler (Shepard and Metzler, 1971) style computerizedmental rotation tasks: mental rotation of Tetris shapes, mental rotation of non-Tetris

shapes, mental rotation of Tetris-like letters, and mental rotation of non-Tetris-like letters.

Table 1. Characteristics of the nine measures of spatial ability

According to each theory,should Tetris expertise berelated to performance?

Shares cognitive Shares exact Specicprocesses with representations General Specic skills

Spatial measure Tetris with Tetris skills skills in context

Mental rotation ofTetris shapes Yes Yes Yes Yes Yes

Mental rotation ofnon-Tetris shapes Yes No Yes Yes No

Mental rotation ofTetris-like letters Yes No Yes Yes No

Mental rotation ofnon-Tetris-likeletters Yes No Yes Yes No

Computerized formboard with Tetrisshapes No Yes Yes No No

Computerized formboard with non-Tetris shapes No No Yes No No

Card rotations Yes No Yes Yes No

Form board Yes No Yes Yes No

Paper folding No Yes Yes No No

1In addition, two verbal tests were administered, namely, a paper-and pencil-vocabulary test and a computerizedsentence/picture verication task. These tests were not used in the analysis because our focus was on spatialability.



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Figure 3. Sample items from the nine measures of spatial ability



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On each mental rotation trial, two letters/shapes were presented in the middle of thecomputer screen. They were either at the same orientation, or the one on the right was

rotated. The participant's task was to decide if the two shapes/letters were identical

regardless of orientation (i.e., true), or if the shapes/letters were mirror-images of one

another (i.e., false). Four Tetris shapes and four non-Tetris shapes were used in the mental

rotation tasks, as shown in Figure 4. Both handedness versions of the `L' and `Z' shapes

from Tetris were used. The non-Tetris shapes were based on previous work (Sims, 1990,

unpublished thesis; Sims and Mayer, 1994, poster presented at the 102nd annual meeting

of the American Psychological Association, Los Angeles, California), and like those used

by Okagaki and Frensch (1994), involve the addition of a single square to an existing Tetris

shape. For mental rotation trials involving letters, `L' and `Z' were chosen to be physically

similar to the shapes in Tetris. The letters G and R were chosen because of their

dissimilarity to Tetris shapes.Mental rotation trials were designed along two dimensions: angular disparity of the two

shapes (0, 45, 90, 135, 180, 225, 270, or 315), and whether the trial was true or

false. The 112 trials involving Tetris and non-Tetris shapes were presented together in two

blocks of 56 trials each. The 56 individual trials involving Tetris-like and non-Tetris-like

letters were presented together in a single block.2 Within a block of trials, presentation was

randomized. There were three replications of each rotation task. Because participants

failing to correctly answer 80% of the mental rotation trials were not used, reaction time

(milliseconds) was considered the dependent measure of interest.

On the computerized form board tests, the participant had to make true/false decisions

as to whether two shapes, a small shape (target shape) and a larger shape (base) would t

together to form an even larger shape (nal shape). A target shape appeared above a basein the top of the screen. In the bottom of the screen was a possible nal shape. Participants

were told to imagine that the target piece would fall straight down, and land on the base.

Twenty-four trials were constructed to vary along three dimensions: height of the target

shape, type of target shape used (Tetris shape or non-Tetris shape), and whether the trial

was true or false. Target shapes were presented at one of three heights above the base: low

Figure 4. Shape and letter stimuli

2For the `Z' like Tetris shape and for the letter `Z', only orientations up to 135 were used because these shapesrotate into themselves after that point.



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(2 cm), medium (4 cm), or high (6 cm). Half of the target shapes were the `L' shape found

in Tetris and half were the corresponding non-Tetris shape reminiscent of the `L' shape.

Both shapes appeared in black instead of in the patterns used in the game. This colouring

was used so that it would be difcult for participants to answer the questions simply by

counting squares. Furthermore, the task was designed such that false trials reected

common mistakes in the game Tetris. These common mistakes were compiled by expertplayers in a pilot experiment. On half of the false trials, the nal shape reected amisalignment of the target shape and the base. On the other half of the false trials, the nal

shape reected a misconception concerning the length of the target shape. Each trial

was presented three times. The dependent measure of interest was reaction time in

milliseconds.

The three paper and pencil measures were taken from the Kit of Factor-Referenced

Cognitive Tests (Ekstrom et al., 1976a,b). These included part 1 of card rotations, the form

board test, and the paper folding test. The card rotations test (S-1 revised) consisted of 80

mental rotation items to be completed in three minutes. The form board test (VZ-1)consisted of twenty-four items. On each item, participants were shown a large shape and

several sets of smaller shapes. For each set of smaller shapes, the participant had to decidewhich shapes could be put together to make the larger shape. Small shapes could be

rotated or slid around on the page, but they could not be ipped over or resized. Eight

minutes were allotted for the task. The paper-folding test (VZ-2) consists of ten items to

complete in three minutes. On each item, the participant was shown several pictures

depicting the folding of a square piece of paper. The last picture also showed a hole being

punched in the folded paper. Next to this series of pictures were ve choices depicting thepunched paper when unfolded. The task was to decide which of these ve choices

correctly depicted the unfolded paper.

Procedure

Groups of one to ve participants completed two sessions that were 1 to 7 days apart.

During session 1, participants completed the paper-folding task, the form board task, andthe card rotations task. This session lasted approximately 40 minutes. In session 2

participants rst completed the computerized form board task. This was followed by 10

practice mental rotation trials using numbers, and the letter and shape rotation tasks. The

order of the blocks for the two mental rotation tasks involving shapes was counterbalanced

such that approximately half of the participants received Block A rst, and approximately

half received Block B rst. After completing the cognitive measures, participants played a

two-minute practice game of Tetris followed by two performance games on which

participants were told to play as well and as long as possible. The second session lasted

approximately one hour.

Results and discussion

Do students with high versus low skill in Tetris differ on tests of spatial ability?

According to the general transfer hypothesis, the students with high skill in Tetris playing

will outperform students with low skill in Tetris playing on all tests of spatial ability. In

contrast, the specic transfer hypothesis predicts that the high-skill group will outperform

the low-skill group only on spatial ability tests that require the same cognitive processes as

Tetris, such as mental rotation. Finally, the specic transfer in context hypothesis holds

that the high-skill group will perform better than low-skill group only on mental rotation



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of Tetris shapes. Table 2 presents the mean scores of the two groups on each of the nine

tests of spatial ability. An analysis of variance (ANOVA) was conducted for each cognitive

measure, with reaction time as the dependent measure for all computerized tasks and

number correct as the dependent measure for all paper and pencil measure.3 Errors and

times over 6 seconds were not used in the reaction time analyses. The high-skill group

outperformed the low-skill group on mental rotation of Tetris shapes (F(1, 94) 7.81,

MSE1080567.30, p< 0.01) and non-Tetris shapes (F(1, 94) 4.55, MSE 724672.25,

p< 0.05), but not on any of the other measures. Similarly, a stepwise discriminant analysisrevealed that only one factor signicantly discriminated the two groups mental rotation

of Tetris shapes (F(1, 96) 10.82, p< 0.0014). These ndings are most consistent with

the specic transfer in context hypothesis.

Do students with high versus low skill in Tetris differ in how they perform

mental rotation tasks?

A secondary goal of Experiment 1 was to examine whether high-skill students were

carrying out mental rotation tasks in a different manner from low-skill students. In

particular, we were interested in whether high-skill students showed evidence of storing

the familiar shapes at multiple orientations so that they would not have to mentally rotate

them as far. To examine this issue, each subject's reaction time functions for performanceon the Tetris shape and non-Tetris shape mental rotation tasks was compared to eight

linear regression models.4 Each model was evaluated based on the degree to which it

accounted for the variance in the participant's data. Figure 5 shows examples of each of the

regression models.

Table 2. Means and standard deviations for high- and low-skill groups on ninemeasures of spatial ability Experiment 1

Group

High skill Low skill

Cognitive measure M SD M SDMental rotation of Tetris shapes (ms) 1508 409 1757 325

Mental rotation of Non-Tetris shapes (ms) 1644 451 1864 332

Mental rotation of Tetris-like letters (ms) 1342 352 1439 295

Mental rotation of Non-Tetris letters (ms) 1315 348 1400 321

Computerized form boardwith Tetris Shapes (ms) 2861 1021 3079 796

Computerized form boardwith non-Tetris shapes (ms) 3243 1110 3528 927

Card rotations (out of 80) 60.36 14.72 56.78 13.67

Form board (out of 120) 61.49 21.15 53.64 17.96

Paper folding (out of 10) 6.41 2.52 5.88 1.74

3An analysis of variance was conducted for each cognitive measure, with group and sex as between-subjectsfactors. However, only group effects are reported here.4Only the `L' shape was used in this analysis because the `Z' shape cannot be used for orientations greater than135.



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Figure 5. Eight models of mental rotation strategies



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Model 1 was intended to test whether a participant's data were like a Shepard/Metzler

curve, with rotation proceeding clockwise to 180, and counterclockwise for later

orientations. Model 2 is a variant of Model 1 in which the participant mentally rotates

clockwise to 225, and that counterclockwise rotation is slower than clockwise rotation,

perhaps accounting for the decision to rotate further clockwise. Model 3 is a variant of

Model 2 in which the participant mentally rotates clockwise to 225

, and counter-clockwise for further rotations, but that counterclockwise rotation is no slower thanclockwise rotation. Model 4 was intended to represent subjects who were not mentally

rotating, instead taking a similar amount of time to complete all non-0 trials. Model 5 was

intended to represent the participant who had stored Tetris shapes at Tetris orientations and

mentally rotated Tetris shapes at non-Tetris angles to one of these stored orientations.

Model 6 was a variant of Model 5 corresponding to any participant who stored Tetris

shapes at Tetris orientations, but who mentally rotated to the upright for Tetris shapes at

non-Tetris orientations. Model 7 represents the participant who mentally rotated only

clockwise all the way around. Similarly, Model 8 portrays the participant who imaginedrotation counterclockwise all the way around.

For each participant, we computed the mean RT on the Tetris shape mental rotation taskfor each of the eight orientations (i.e., 0, 45, 90, 135, 180, 225, 270, and 315), and

repeated this procedure for the non-Tetris shape mental rotation task. We computed a

regression analysis between each participant's pattern of RTs and the pattern predicted by

each model, and designated the model producing the highest percentage of explained

variance as the best tting model. The top of Table 3 shows the number of high- and low-

skill students whose pattern of response times for the Tetris shapes mental rotation task

was best t by each model. As can be seen, the classic Shepard/Metzler curve (i.e., Model

1) best t the performance of most high- and low-skill students and its variants (i.e.,

Models 2 and 3) best t the performance of almost all of the other high- and low-skill

students. The bottom portion of Table 3 shows the number of high-and low-skill students

whose pattern of response times for the non-Tetris shapes mental rotation task was best t

by each model. As with Tetris shapes, the classic Shepard/Metzler curve (Model 1) best t

Table 3. Number of high- and low-skill players whose performance on mentalrotation of Tetris and non-Tetris shapes was best t by each of the eight models Experiment 1

Tetris shapesModel

#1 #2 #3 #4 #5 #6 #7 #8

High-skill 30 9 11 1 0 0 2 0Low-skill 28 4 13 0 0 0 0 0

Total 58 13 24 1 0 0 2 0Non-Tetris shapes

Model

#1 #2 #3 #4 #5 #6 #7 #8

High-skill 33 7 9 4 0 0 0 0Low-skill 35 2 5 2a 1a 0 1 0

Total 68 9 14 6 1 0 1 0

aFor one subject, Models 4 and 5 accounted for an equal amount of the variance (29%).



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the performance of most high- and low-skill students and its variants (Models 2 and 3) best

t the performance of most of the other high- and low-skill students.

These results suggest that both high- and low-skill students completed the rotation tasks

by using mental rotation. Although the experts were faster for both Tetris and non-Tetris

shapes, they were not using a look-up strategy. Contrary to Tarr and Pinker's (1989) work,

there was no evidence that high-skill students stored the familiar shapes at multiple an-gles. Instead, the evidence is more in line with the working memory hypothesis in whichhigh-skill students are able to speed mental rotation because they do not have to spend

valuable mental resources maintaining a stable image of the stimulus.

Do students with high versus low skill in Tetris differ in encoding speed

or in rotation speed?

The examination of individual rotation functions suggested that the mental rotation

process is not qualitatively different for high- and low-skill students. However, it is

possible that high- and low-skill students differ quantitatively in terms of speed of

encoding or rotating the shapes in a mental rotation task. For 70 of the 98 subjects, a

Shepard/Metzler curve (Model 1) accounted for more than 50% of the variance. For these

subjects, slopes and intercepts were calculated, and the data were subjected to 2(group:

high skill versus low skill) 2(shape type: Tetris versus non-Tetris) mixed ANOVAs. The

intercept represents the time to encode, compare, and respond, whereas the slope

represents the time to mentally rotate shapes. Table 4 shows the means and standard

deviations for intercept and slope as a function of shape type and expertise.

The mean intercept (milliseconds) for high-skill students was 790.69 (SD 205.90) on

Tetris shapes and 947.69 (SD 289.62) on non-Tetris shapes, the mean intercept

(milliseconds) for low-skill students was 915.96 (SD214.72) on Tetris shapes and

1150.48 (SD 227.53) for non-Tetris shapes. The intercept analysis indicated a main

effect for group in which high-skill students were faster than low-skill students at

encoding, comparing, and responding, F(1, 68)10.29, MSE 91536.87, p< 0.01. There

was also a main effect for shape, F(1, 68) 65.31, MSE20538.01, p< 0.001. Encoding,comparing, and responding took less time for Tetris shapes than for non-Tetris shapes. The

lack of a signicant interaction indicates that experts were faster to encode both Tetris and

the similar non-Tetris shapes. This result is consistent with the idea that experts may have

used stored representations of the familiar Tetris shapes to aid in the representation of the

very similar non-Tetris shapes.

The mean slope (milliseconds) for high-skill students was 5.91 (SD3.22) on Tetris

shapes and 7.69 (SD 3.45) on non-Tetris shapes; the mean slope (milliseconds) for

Table 4. Mean intercept and slope for high- and low-skill players onmental rotation of Tetris and non-Tetris shapes Experiment 1

High skill Low skill

M SD M SD

Intercept (ms)Tetris shapes 790.69 205.90 915.96 214.72Non-Tetris shapes 947.69 289.62 1150.48 227.53

Slope (ms/degree)Tetris shapes 5.91 3.22 8.66 3.22Non-Tetris shapes 7.69 3.45 8.89 3.42



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low-skill students was 8.66 (SD3.22) on Tetris shapes and 8.89 (SD 3.42) for non-

Tetris shapes. The slope analysis yielded a signicant main effect for group (F(1,

68)6.98, MSE 19.54, p< 0.05) in which high-skill students mentally rotated more

quickly than low-skill students. There was also a main effect for shape, F(1, 68)13.33,

MSE2.63, p< 0.001. Tetris shapes were mentally rotated more quickly than non-Tetris

shapes. More interestingly, these effects were modulated by a signicant group shapetype interaction, F(1, 68) 7.96, MSE2.63, p< 0.01, in which low-skill studentsmentally rotated equally quickly for both Tetris and non-Tetris shapes, t(34) 0.61,

p0.55. whereas high-skill students mentally rotated more quickly for Tetris shapes than

for non-Tetris shapes, t(34) 4.46, p< 0.0001. This result suggests that when the task is

less memory intensive, such as encoding a stimulus, high-skill Tetris players show transfer

to stimuli that are very similar to those with which they are highly familiar. However,

during a more memory-intensive procedure such as the maintenance of an image during

mental rotation, the high-skill Tetris players show a much greater speed benet for the

highly familiar stimuli.

EXPERIMENT 2

Experiment 1 showed that students with high skill in Tetris playing outperformed students

with low skill in Tetris playing only on mental rotation tasks that used stimuli that were

either the same or were representationally very similar to shapes learned in the game. For

these shapes, the experiment also showed that high- and low-skill students completed

mental rotation tasks in a similar manner, but high-skill students were faster to actually

encode and carry out the mental rotation procedure. Within the high-skill group, the results

also showed faster rotation for the Tetris shapes than for the non-Tetris shapes. These

results are consistent with the hypothesis that Tetris expertise is highly domain-specic.

However, it is not possible to attribute a causal relationship between Tetris expertise and

changes in spatial ability skills on the basis of correlational data presented in Experiment 1.In Experiment 2, we examine whether there is a causal relationship between Tetris

expertise and performance on spatial ability measures. In Experiment 2, female graduate

students who had never played Tetris took a battery of spatial ability tests as a pretest and a

posttest, while either playing 12 hours of Tetris (experienced group) or not playing Tetris

(inexperienced group) during the intervening period. The general-skills hypothesis

predicts the experienced group will show greater pretest-to-posttest gains than the in-

experienced group on all measures of spatial ability; the specic-skills hypothesis predicts

that the experienced group will show greater pretest-to-posttest gains than the inexper-

ienced group only on tests of mental rotation; and the specic-skills-in-context hypothesis

predicts that the experienced group will show greater gains than the inexperienced group

only on tests involving mental rotation of Tetris shapes. A second goal of Experiment 2 isto examine the relationship between pretest scores on a battery of spatial ability tests, and

the pattern of cognitive changes associated with learning to play the game.

Method

Participants and design

The participants were 16 female graduate students at the University of California,

Santa Barbara who had no Tetris experience. Eight participants served in the experienced



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group and received $75 for approximately 14 hours of participation; 8 other participants

served in the inexperienced group and received $25 for approximately 4 hours of

participation. Participants in the two groups were matched on the basis of pretest scores

on tests of spatial ability. Comparisons of pretest-to-posttest changes are within subject

comparisons.

Materials and apparatus

The materials included the same computerized and paper-and-pencil tasks as in

Experiment 1. The apparatus and computer programs were identical to those used in

Experiment 1.5

Procedure

An e-mail message soliciting female graduate students who had never played Tetris

yielded 29 prospective participants. At a pre-experiment session, prospective participants

were paid $5 to take three paper-and-pencil tests of spatial ability as in Experiment 1. Thethree tests paper folding, form board, and card rotations yielded a composite score of

spatial ability. Eight matched pairs were identied on the basis of the composite score,with two pairs scoring low, two pairs scoring high, and four scoring average. One member

of each pair was assigned to the experienced group and the other to the inexperienced

group. The other 13 prospective participants were excused from further participation.

Students in the experienced group attended 14 additional sessions, each lasting

approximately 1 hour. During session 1, students completed the same computerized tests

of spatial ability as in Experiment 1 and learned to play Tetris for approximately 20minutes. During each of sessions 2 through 13 students devoted approximately one hour to

playing Tetris. In addition, participants were given the computerized mental rotation tests

for Tetris and non-Tetris shapes during the rst 5 to 10 minutes of sessions 5 and 9. During

session 14, students completed the same paper-and-pencil and computerized tests as they

had taken as a pretest. Students in the inexperienced group took the same tests as the

experienced group in sessions 1, 2, 5, 9 and 14 but did not participate in any Tetris playing.The sessions were scheduled over a four week period. The tests were scored and analysed

as in Experiment 1.

Results and discussion

As in Experiment 1, errors and times over 6 seconds were not used in the reaction time

analyses.

Are spatial skills altered by Tetris play?

According to the general skills hypothesis, those experienced playing Tetris should show a

larger pretest-to-posttest gain than the inexperienced group on all measures of spatialability. The specic skills hypothesis is that those who learn Tetris should improve on all

mental rotation tasks. According to the specic skills in context hypothesis, those who are

required to play Tetris should show larger pretest-to-posttest gains than non-playing

students only on mental rotation tests involving Tetris shapes. Based on the results of

Experiment 1, we would also predict this effect for shapes that are highly similar to Tetris

5As in Experiment 1, participants also completed vocabulary and sentence/picture verication tasks that were notincluded in these analyses.



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Table5.

Pretestandposttestscoresforexperience

dandinexperiencedgroupsonninemeasuresofspatialabilityExperim

ent2

Experienc

ed

Inexpe

rienced

Pre-versuspo

sttest

Pretest

Posttest

Pretest

Posttest

ANOVA

Measure

M

SD

M

SD

M

SD

M

SD

Values

Mentalrotationof

1828

444

1

000

189

1812

340

1145

292

F(1,42)10

0.55

Tetrisshapes(

ms)

MSE

1811

666

p

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