1 IntroductionVideo games have increased greatly in their sophistication and popularity in recentyears. While there has been a great deal of effort focused on the relationship betweenvideo-game violence on real-world behavior and development (cf Dill and Dill 1998;Anderson and Bushman 2001), recent studies have shown specific effects that video-game play can have on visual perception and attention. Green and Bavelier (2003), forexample, demonstrated that previously inexperienced video-game players can improvetheir performance on attentional tasks by playing an action video game an hour a day forten days. A number of studies have shown interesting performance differences betweennon-video-game players and avid video-game players, including on an attentional-blinkand a useful-field-of-view task (Green and Bavelier 2003); enumeration and multipleobject tracking (Green and Bavelier 2006a); a variety of spatial tasks (Pepin and Dorval1988; Subrahmanyam and Greenfield 1994; Green and Bavelier 2006b, 2007; Quaiser-Pohlet al 2006); inhibition-of-return and visual-search tasks (Castel et al 2005); and even low-level measures such as contrast sensitivity (Li et al 2008).

In order to make a serious effort at understanding the perceptual and cognitiveeffects of video games, it must be realized that the variety of video games is quitebroad. Most studies on the perceptual effects of video games in recent years haveutilized a particular genre, that of the fast-action first-person shooter (FPS). However,it is misleading to base conclusions about video games in general on a single genre,just as it would be misleading to base one's conclusions about the effects of televisionby considering only crime shows. In recent years, video-game taxonomy (see Wolf 2001:Apperly 2006) has coalesced into a number of distinct genres. Although many gamesmay overlap in genre, they are often broken down into categories such as sports, simula-tion, puzzle, FPS, role-playing, and so forth, with each of these categories includingseveral subgenres. In the study of the effects of video-game play on perceptual and atten-tional processes, the relevant categorization into genres may be different than for otherpurposes. For example, the game Halo 3 has a science fiction theme, while the gameMedal of Honor 4 has a military theme. If they were films, they might be categorizedinto war and science-fiction genres. However, the relevant aspect here is that they areboth FPS games with a similar style of playöfast reactions, accuracy, and good spatial

Action and puzzle video games prime differentspeed/accuracy tradeoffs

Perception, 2009, volume 38, pages 1678 ^ 1687

Rolf A Nelson, Ian StrachanDepartment of Psychology, Wheaton College, Norton, MA 02766, USA;e-mail: rnelson@wheatonma.eduReceived 11 November 2008, in revised form 6 February 2009

Abstract. To understand the way in which video-game play affects subsequent perception andcognitive strategy, two experiments were performed in which participants played either a fast-action game or a puzzle-solving game. Before and after video-game play, participants performeda task in which both speed and accuracy were emphasized. In experiment 1 participants engagedin a location task in which they clicked a mouse on the spot where a target had appeared, andin experiment 2 they were asked to judge which of four shapes was most similar to a targetshape. In both experiments, participants were much faster but less accurate after playing theaction game, while they were slower but more accurate after playing the puzzle game. Results arediscussed in terms of a taxonomy of video games by their cognitive and perceptual demands.

doi:10.1068/p6324

navigation being important for successful game play. On the basis of this taxonomyof skills utilized, we have chosen two games that require very different skills. Wereasoned that interaction with a puzzle game, in which deliberation and a consideredapproach is required for success, would incur different effects than interaction with afast-action shoot-em-up game, in which these cognitive skills are less relevant.

One fairly consistent finding on the effects of video-game play is a generalizedimprovement on reaction-time (RT) tasks (eg Green and Bavelier 2003; Castel et al2005; Quaiser-Pohl et al 2006; Dye et al submitted). Since an increase in speed on atask is often accompanied by a reduction in accuracy, we wondered if at least part ofthis reaction-time improvement might be due to strategic factors; that is, a shift in thespeed ^ accuracy tradeoff. This sort of shift could result from a demand in the optimalstrategy for a particular game, and thus might yield very different results dependingon the game. For example, a fast-action FPS could require the rapid deployment ofattention and an immediate motor movement, while a more cognitively oriented puzzlegame could require a slow and more deliberate response.

In the present experiments we investigated whether video-game play can influencestrategic deployment of speed and accuracy in a task which utilizes both. We measuredperformance on a task that could be influenced by different strategic approachesöpartic-ipants could either be very fast at the task, or very accurate. Speed ^ accuracy tradeoffshave been shown to be influenced most prominently by including incentives for emphasiz-ing one or the other (eg Fitts 1966; Wood and Jennings 1976; Dickman and Meyer 1988),but also by situational variables such as nearness to completion of a task (Fo« rster et al2003). It was our prediction that playing a video game would cause a generalized shiftin strategy reflecting the skills used in that game. Playing a game which requires veryfast deployment of visual attention and motor movement could prime a strategy ofspeed over accuracy, while playing a game which emphasizes a slower, more thoughtfulpace could prime the opposite pattern.

2 Experiment 1: Speed and accuracy in a location task2.1 Method2.1.1 Participants. Twenty students (eleven male, nine female) from Wheaton Collegein Norton, MA, were recruited for the study. Ages ranged between 19 and 23 years(mean � 21:8 years). They received compensation in the form of a $10 gift certificateto the campus bookstore for their participation.

2.1.2 Procedure. After signing a consent form, participants were asked to fill out a briefsurvey on the amount of experience they had playing video games. Along with a fewother background questions, participants were asked to circle a number on a scale of 1 to10 how often they played FPS action games such as Quake, Doom, or Halo. Underneaththe rating scale were the words `̀ never'', `̀ seldom'', `̀ sometimes'', `̀ frequently'', and ``often''.

Participants were then given a location task. The task was given on a Dell Optiplexcomputer with a 21-inch ViewSonic CRT monitor at a resolution of 1024 by 768 pixels.Participants sat approximately 24 inches from the screen, giving the visible screen atotal size of approximately 19.5 deg of visual angle wide by 14.5 deg of visual anglehigh. Stimuli were presented via the program SuperLab.

All participants received the following instructions:

`̀ In this test, you will have a number of trials. On each trial, a plus sign will appearin the middle of the screen. When this happens, you will move the mouse to the plussign and click it. Next, a square with an `̀ X'' in it will flash somewhere on the screen.Your task is to click the mouse QUICKLY and ACCURATELY at the center of the spotwhere the box was. After you have clicked on it, the next trial will begin. To familiarize youwith the procedure, there will be five practice trials. Do you have any questions?''

Action and puzzle video games 1679

Figure 1 shows the sequence for each trial. Initially, a fixation cross appeared at thecenter of the screen. When participants clicked on the cross with the mouse, a 1500 msSOA was followed by the appearance of a rectangular box with an `6' inside it. Thistarget appeared randomly at one of twenty locations on the screen, varying fromapproximately 2.8 deg to 10.2 deg from the center. The target was present for 200 ms,a time selected so that participants would not be able to click on it while still present.As soon as participants clicked the mouse on a location, the fixation cross appearedat the center of the screen to begin the next trial. There were five blocks of 20 trialspresented. Each block contained all 20 locations.

Following the pretest, participants were introduced to one of two video games(ie ten participants per game). After being familiarized with the game, they played itfor an hour. Performance on these games was recorded in order to ensure that theparticipants were sufficiently engaged.

The action game Unreal Tournament is an FPS game. The pace of the game isvery fast, with the goal being to kill as many opponents as possible while avoidingbeing killed. Each participant went through the game tutorial (and was observedby the experimenter), which lasted approximately 5 min and familiarized them withthe controls, before engaging in four 15-min sessions. All participants were startedon the easiest level, `novice', If they performed sufficiently well during each session(as measured by killing more enemies than they were killed), they advanced to a moredifficult level. Thus, participants could advance from `novice' to `average' to `experienced'to `skilled' during the course of the hour if they performed optimally.

The puzzle game Portal is superficially similar to an FPS game(1) in that it involvesnavigating around a complex spatial environment from a first-person perspective;however, the focus of the game-play is on solving puzzles. Rather than using a weaponto kill opponents, players must aim a gun at walls and objects to create a temporary `portal'

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Figure 1. The time course of the trials for experiment 1.

(1) The Source game engine for Portal has in fact been used for FPS games, most notably Half-Life 2.

1680 R A Nelson, I Strachan

between spatial locations. So, for example, players may shoot the gun at a distantwall to create a hole. They may then shoot the gun at the floor in front of them andcreate a second hole. If they step through the floor in front of them, they will appearout of the distant wall where they had created the first hole. The physics of the gamepreserves momentum, so that if a player jumps into a hole far below them, he/shewill be propelled with an equivalent speed (but not direction) from the far wall. Newplayers to the game must spend time to understand these novel physics, so cognitivestrategy should be less concerned with rapid response than with one that solves theproblem at hand. After observing participants during the first level to ensure theyunderstood the controls, the experimenter then began an hour of play. Progress wasmeasured by the number of levels through which they successfully navigated.

When participants finished the hour of video-game play, they repeated the spatial-location task (the post-test), identical to the one they had taken earlier.

2.2 Results2.2.1 Reaction time. There was a significant difference in RT patterns for the twogroups. Figure 2 shows RT scores before and after playing each game. A 262 ANOVAwith epoch (pre-test=post-test) as a within-subjects variable, and video game as abetween-subjects variable indicated an interaction (F1 18 � 18:64, p 5 0:001), such thatparticipants showed a much greater speed increase on the task after playing the actiongame than the puzzle game.

Individual comparisons indicate that pre-test RTs did not differ between the twogame types (t18 5 1), but post-test RTs were considerably faster for the action-gameplayers than for the puzzle-game players (t18 � 5:44, p 5 0:0001). In fact, althoughperformance was faster after playing the action game than before for the same partic-ipants (t9 � 3:44, p 5 0:01), performance was actually slower after playing the puzzlegame (t9 � 2:63, p � 0:01).

2.2.2 Accuracy. There was also a significant difference in the pattern of accuracybetween game conditions. Figure 3 shows accuracy in terms of mean distance from thetarget (ie greater distance corresponds to more error). While both the action- and puzzle-game players performed similarly in the pre-test (t18 5 1), puzzle-game players weresignificantly more accurate than action players in the post-test (t18 � 3:10, p 5 0:01).This resulted in a significant interaction between game type and the pre-test/post-testconditions (F1 18 � 10:69, p 5 0:01). Paired comparisons indicate that participants whoplayed the action game became less accurate (t9 � ÿ2:90, p 5 0:01), and participantswho played the puzzle game became more accurate (t9 � 1:82, p � 0:05).

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Figure 2. Reaction-time (RT) results for experiment 1. Participants were faster after playing anaction game than after playing a puzzle game.

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Figure 4 shows errors in more detail, offering a visualization of the ways in whichparticipants strayed from the target. Each scatter dot represents a single response onan X and Y axis relative to the target position. A positive point reflects a responsefarther from the fixation than the target, while a negative point reflects a response closerto the fixation than the target. In this figure, one can see the more scattered and lessprecise responses that came after playing the action video game. As indicated by linearregression trend lines in the figures, overall error patterns show that participantstended to err along the linear trajectory running from the fixation to the target.

2.2.3 Video-game expertise and performance. On a scale of 1 to 10, participants aver-aged a score of 3.55 on the survey of experience playing action games, with individualscores ranging all the way from 1 to 10. There was no difference between the averagesof the action group (mean � 3:6) and the puzzle group (mean � 3:5) (t 5 1), rulingout video-game experience as a factor in the results described above.

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Figure 3. Accuracy results for experiment 1. Action gamers were less accurate than puzzle gamers.

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Figure 4. Plot of location errors in experiment 1. Action gamers were less accurate in the post-test than in the pre-test, and as compared to puzzle gamers.

1682 R A Nelson, I Strachan

All participants were able to understand the controls and successfully play the games.For the action game, all participants finished at least 1 level (average � 3.1 levels finished).For the puzzle game, participants finished between 8 and 15 levels (average � 11.4 levels).

2.3 DiscussionResults convincingly demonstrate a priming effect for two different types of videogames. Playing an action video game resulted in faster reaction times and lower accu-racy on a location task, while playing a puzzle game resulted in slower reaction timesand higher accuracy.

It is interesting that participants tended to overshoot the target, especially in thepost-test for the action-game condition. It might be expected that the fastest RTs (whichoccurred in this condition) would result from undershooting the target. That is, since thetime to move the mouse outward from the center increases the farther the response is,it might be that participants are increasing speed by clicking closer along the trajectoryto the target. However, this is not the case. It would appear that they are amplifying thesame type of error that participants in all conditions are making, just at a faster speed.

How generalizable are these strategic shifts in tasks after video-game play? Experi-ment 1 demonstrated speed ^ accuracy priming in a task that was closely related tothe types of movement used in the video game. While playing the action game, partic-ipants moved the mouse around the screen as rapidly and as accurately as possible totarget enemies before shooting at them. Likewise, in the location task, they movedthe mouse to a cued location as rapidly as possible before clicking on it. In order tounderstand the nature of the strategy shift that was observed in experiment 1, we wantedto measure performance on a task which did not employ the same motor-movementsor location-accuracy skills as the video game itself did.

The task in experiment 2 was quite different, while still requiring both speed andaccuracy. Rather than mimicking the movements made in the video game, this taskrequired participants to make judgments about the similarities of shapes. We reasonedthat if the strategy shift we saw in experiment 1 was at a more cognitive (rather thanearly visual or motor processing) level, we could reasonably expect a similar speed ^accuracy shift in a task that does not require the same type of spatial attention andmotor movements.

3 Experiment 2: A matching-figures taskThe task was loosely based on the Kagan's Matching Familiar Figures Test (Kagan1965), and is also similar to the one used by Dickman and Meyer (1988) in measuringspeed ^ accuracy tradeoffs. In this task, a sample shape is shown along with comparisonshapes, and response time and error rate are measured in choosing the correct match.

3.1 Method3.1.1 Participants. Twenty college students (twelve male, eight female) from the samepopulation as in experiment 1 participated, and no participants were in both experiments.Ages ranged between 19 and 22 years (mean � 20:7 years). They received the samecompensation as those in experiment 1.

3.1.2 Procedure. General procedures were the same as in experiment 1 except for thetask. The instructions given for the matching-figures task were:

`̀ In this test, you will be shown shapes that look like this.'' [A set similar to figure 5 wasshown on the screen.] `̀ Your task is to find which of the four shapes matches the top one.To do this you will press the corresponding button on the button box.'' [The button boxis shown.] `̀ These may seem difficult, but it is important that you respond as QUICKLYand as ACCURATELY as possible. If your response is longer than 5 seconds, you will geta prompt and the trial will be repeated. Before the actual trials begin, you will be given a

Action and puzzle video games 1683

few practice trials.'' [Practice trials are given.] `̀ Now the actual trials will begin. If youhave any questions, or are unsure about what to do, please ask the experimenter now.Remember to respond as QUICKLY and as ACCURATELY as you can.''

Figure 5 demonstrates the type of figures that were used in the task. There were atotal of 20 different such sets, and for each set there were 4 different trials consistingof the similar shape in each of the 4 positions. Thus, in all, there were 80 differenttrials, and they were presented randomly. The stimulus set was designed by changingjust one vertex of a shape. The differences in the shapes were intentionally very slightto increase the difficulty of the task and to decrease the corresponding accuracy.

Responses were collected via a Cedrus RB-834 USB button box using the four centrallarge buttons.

3.2 Results3.2.1 Reaction time. 68 trials, or about 2% of the total, were discarded because partici-pants took over 5 s to respond.

Results, shown in figure 6, were quite similar to those of experiment 1. Again, a262 ANOVA with epoch (pre-test/post-test) as a within-subjects variable, and videogame as a between-subjects variable indicated an interaction (F1 18 � 19:46, p 5 0:001),such that participants showed a much greater speed increase on the task after playingthe action game than the puzzle game. Participants were much faster after playing theaction game than before (t9 � 3:31, p 5 0:01), and slower after playing the puzzle gamethan before (t9 � 3:08, p 5 0:01).

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Figure 5. A sample stimulus for experiment 2.Participants' task was to decide which of the fourshapes matched the one on top.

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Figure 6. Reaction-time (RT) results for experiment 2. Action gamers showed a speed increase,while puzzle gamers showed a speed decrease.

1684 R A Nelson, I Strachan

3.2.2 Accuracy. There was again an interaction such that participants were more accu-rate after the puzzle game than the action game (F1 18 � 23:85, p 5 0:001). Individualcomparisons (see figure 7) show that accuracy was worse after playing the action gamethan before (t9 � 2:77, p � 0:01), and that their accuracy was better after playing thepuzzle game than before (t9 � 5:07, p 5 0:0001).

3.2.3 Video-game expertise and performance. Participants averaged a score of 4.75 onthe survey of experience playing action games, with individual scores ranging from 1to 10. There was no difference between the averages of the action and the puzzle group(t18 5 1).

In the action condition, all participants finished at least one level (average � 2:7levels finished). For the puzzle game, participants finished between 6 and 18 levels(average � 11:7 levels).

3.3 DiscussionIn addition to replicating and verifying the results of experiment 1, experiment 2 pro-vided clear evidence that this priming effect can not be attributed solely to a changein motor skills or to task-specific perceptual learning. The matching-figures task wasvery different in terms of the skills needed and motor-movements involved than thelocation task used in experiment 1.

One objection that might be made is that in experiment 2 (unlike in experiment 1),the pre-test scores from the two types of games were different. RTs for the puzzlegamers on the pre-test were in fact faster than for the action gamers (t18 � 3:30,p 5 0:01). This could not be a result of any experimental manipulation, since the pre-test was given to all participants in an equal manner at the beginning of the experiment.We attribute this difference to a greater range of flexibility in strategy for this task.Note that RTs are overall much higher than for experiment 1 (roughly two to threetimes higher), and there is a greater variability for individual average response times.For experiment 1, the standard deviation of responses between subjects for the pre-test was 219 ms, while in experiment 2, this standard deviation was 741 ms. Clearlythere was more individual variation in the initial strategy employed. However, it isimportant to keep in mind that this was a within-subjects design that was primarilyinterested in the way that participants' individual strategies shiftedöand results con-clusively demonstrated that those who played the action game showed faster RTs andless accuracy on the post-test, while those who played the puzzle game showedthe reverse. It could be argued that the different pre-test scores indicated differentstrategies, which in turn caused a different response to the games. Under this scenario,pre-test RTs (and not game) should be the best predictor of post-test RTs. To address

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Figure 7. Accuracy results for experiment 2. Action gamers became less accurate, while puzzlegamers became more accurate.

Action and puzzle video games 1685

this possibility, a further analysis was done correlating pre-test and post-test RTs.Although there was a significant correlation for both the puzzle game (r 2 � 0:44,p 5 0:01) and the action game (r 2 � 0:29, p 5 0:01) for pre-test and post-test RTs, therewas no correlation between overall pre-test and post-test RTs (r 2 � 0:04, p 4 0:05),strongly indicating that pre-existing strategies (eg differences in pre-test scores) cannotsufficiently explain the results.

4 General discussionIt is clear from the present results that video games can prime certain strategic shiftsin subsequent tasks which require both speed and accuracy. In fact, it is striking howdramatically these strategies can be shifted by a single hour of video-game play.

These results underscore the importance of studying the cognitive and perceptualconsequences of video games in terms of the types of skills demanded from the partic-ular video game under study. It is clear that generalized statements about how videogames affect cognition are misleading; different genres affect perception and strategyin very different ways. An action video game and a puzzle video game have very differentdemands, and no doubt there are other demands of video games which fall into othercategories.

This leads to an important issue: creating a useful taxonomy of video gamesaccording to the visuo-spatial skills they employ. In the present study, the games werechosen because the demand on speed and accuracy is very differentöin Unreal, onemust monitor for moving targets and respond quickly to them, while in Portal, one mustsurvey the situation before acting; a fast response is not a demand characteristic.(2)

Other video games could have differing demands on speed and/or accuracy, andgiven that many video games have a story arc that incorporates multiple types of game-play, might have different demands at different parts of the game. Besides (1) speed and(2) accuracy, we propose that other visuo-spatial skills defining a useful taxonomy mightbe (3) target discrimination, (4) multiple object tracking, (5) visual search, (6) dividedattention, (7) change detection, and (8) spatial navigation in 2-D or 3-D environments.This is not intended to be an exhaustive list, but rather to enumerate some visuo-spatialskills utilized in video games that are well-studied in human visual perception.(3)

An issue which may be interesting to speculate on, and one left to further research,involves the degree to which the type of strategy effect demonstrated here manifests itselfin everyday life. It might be wondered how video-game play affects the way in whichstudents interact in the classroomöperhaps students who have just played an actionvideo game before class are less patient but faster in their interactions, while thosewho have played a puzzle game show a slower but more accurate mode of interaction.It also might be wondered how video games affect those in the workplace, especiallythose who spend a great deal of time on computers. Is there an effect such that playingpuzzle games contributes a slower mode of working, while playing action games con-tributes to a speedier mode? One must, however, be cautious in overextending presentresults. Since the time course in the present experiments was shortöthe priming effectwas demonstrated immediately after the video game was playedöit is not known if theseare persistent effects. It is a topic for further investigation whether these effects mightpersist over the course of hours, days, or weeks. It may be that these effects accumulatewith increased video-game play, such that long-term action gamers favor speed over

(2) In terms of visuo-spatial processing, Unreal requires a strategic adjustment between speed andaccuracy, while Portal, for the most part, does not. That is, the time window for a response inUnreal (shooting at a randomly moving target) is limited, while a response in Portal (shooting at astatic target, or at a moving target with a predictable trajectory) is less constrained.(3) Naturally, most games will employ many of these skills to one degree or another; boundariesbetween games in these categories would be graded.

1686 R A Nelson, I Strachan

accuracy,(4) and the reverse for long-term puzzle gamers. In order to make a convincingcausal link between long-term video-game play and resulting cognitive strategies, a studywith training on these types of games over days or weeks would be necessary.

Nevertheless, present results are conclusive in demonstrating that video games cancause a shift in cognitive strategy outside the game. Given the cultural ubiquity of videogames, it is surprising that there is so little research on the cognitive consequencesof video-game play. We hope that this will change as it becomes clear how demands ofvideo games may transfer to strategic approaches.Acknowledgments. This work was supported in part by a summer fellowship from the MarsFoundation, and by the Wheaton Research Partnership.

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(4) Since the skills required in action games included both speed and accuracy, and because video-gameplay has been shown to improve the kinds of skills involved in playing the game, it seems reasonableto suggest that more-practiced video-game players would not simply have different speed/accuracytradeoffs than less-practiced players, but that their own tradeoffs may shift with experience.

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