Effects of Video Games Experience on Visual Attention

University of Warsaw

Warsaw International Studies in Psychology

Faculty of Psychology

Bartosz Sobczyk

Student’s book no. 271017

Effects of Video Games Experience

on Visual Attention

Master’s degree thesis

Psychology

Thesis written under the supervision of

Dr. Grzegorz Pochwatko

Polish Academy of Sciences

Warsaw, November 2013

EFFECTS OF VIDEO GAMES ON VISUAL ATTENTION 2

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attached electronic version.

Date Signature of the Author of the thesis


Streszczenie

Celem ninejszej pracy jest rozszerzenie badania Green i Bavelier (2006b), w którym

wykazano, że osoby grające w gry typu First Person Shooter (FPS) osiągają lepsze wyniki

od osób nie grających w gry wideo (Non-Video Game Players - NVGP) w zadaniu

badającym zdolność uwagi wzrokowej mierzonej paradygmatem "śledzenia wielu

obiektów". Mechanika strategii czasu rzeczywistego (Real Time Strategy - RTS) jest

zbliżona do tego zadania, dlatego stawiam hipotezę, że gracze RTS osiągną lepsze wyniki

zarówno od grupy FPS, jak i NVGP. Ponadto zwiększyłem liczebność próby aby umożliwić

generalizację wyników. Wyniki nie potwierdzają przewagi graczy FPS nad NVGP. Grupa

RTS osiągnęła lepsze wyniki, niż NVGP podczas śledzenia trzech i czterech obieków. W

porównaniu do grupy FPS, grupa RTS oceniła zadanie jako bardziej podobne do gier, w

które grają oraz osiągnęli lepsze wyniki w śledzeniu trzech obiektów. Wyniki i przyczyny

ich otrzymania są dyskutowane.

Słowa kluczowe: procesy poznawcze, uwaga wzrokowa, śledzenie wielu obiektów, gry

wideo

14.4 Psychologia

Wpływ Doświadczenia w Grach Komputerowych na Uwagę Wzrokową


Table of Contents

1. Introduction ............................................................................................................... 7

1.1. Importance of Technological Advancement and Video Games ....................... 8

1.2. Current Research on Improvement of Cognitive Abilities ............................... 9

1.2.1. Cognitive abilities and far transfer ............................................................. 9

1.2.2. Improvement in cognitive abilities through video game training ............ 10

1.2. Fields of Improvement .................................................................................... 11

1.2.1. Sampling .................................................................................................. 11

1.2.2. Gameplay time ......................................................................................... 12

1.2.3. Genre and display time ............................................................................ 12

1.2.4. Object-based attention ............................................................................. 13

1.3. Video Games Genres and Their Players ......................................................... 15

1.3.1. First person shooters ................................................................................ 15

1.3.2. Real-time strategy .................................................................................... 17

1.3.3. Who are video game players .................................................................... 19

2. Research Problems .................................................................................................. 20

2.1. Hypothesis #1.................................................................................................. 22

2.1.1. Hypothesis #1a ......................................................................................... 22

2.2. Hypothesis #2.................................................................................................. 22

2.2.1. Hypothesis #2a ......................................................................................... 22

2.3. Hypothesis #3.................................................................................................. 22

2.3.1. Hypothesis #3a ......................................................................................... 22

2.4. Manipulation check ......................................................................................... 23

3. Method .................................................................................................................... 23

3.1. Participants ...................................................................................................... 23

3.1.1. Genre and mean gameplay time ............................................................... 24

3.1.2. Age ........................................................................................................... 25

3.1.3. Gender ...................................................................................................... 25

3.2. Materials ......................................................................................................... 25

3.2.1. Multiple objects tracking ......................................................................... 25

3.2.2. Hardware .................................................................................................. 27

3.2.3. Lab environment ...................................................................................... 28

3.3. Design ............................................................................................................. 28


3.4. Procedure ........................................................................................................ 28

4. Results ..................................................................................................................... 30

4.1. Hypothesis #1.................................................................................................. 30

4.1.1. Hypothesis #1a ......................................................................................... 31

4.2. Hypothesis #2.................................................................................................. 32

4.2.1. Hypothesis #2a ......................................................................................... 32

4.3. Hypothesis #3.................................................................................................. 33

4.3.1. Hypothesis #3a ......................................................................................... 34


5. Discussion ............................................................................................................... 36

5.1. Verification of Hypotheses #1 and #1a ........................................................... 36




5.6. Summary ......................................................................................................... 39

5.7. Methodological Observations ......................................................................... 40

5.8. Closing Remarks ............................................................................................. 41

References ................................................................................................................... 43

Appendix A ................................................................................................................. 50


Abstract

The aim of this thesis is to expand the study by Green and Bavelier (2006b), in which they

showed players of first-person shooter (FPS) video games outperforming non-video game

players (NVGPs) in visual attention abilities task as measured by the multiple objects

tracking paradigm. Mechanics of real-time strategy (RTS) games are similar to this task;

therefore I hypothesised that RTS players will outperform both FPS and NVGP groups.

Additionally I increased the sample sizes in order to allow generalization of the results. This

study failed to replicate the previous results of Green and Bavelier; however RTS players

outperformed NVGPs at tracking three and four moving objects simultaneously.

Furthermore, RTS players assessed the MOT task as more similar to the video games they

play when compared to FPS players, and also outperformed them at tracking three objects

simultaneously. These results indicate that RTS players are able to simultaneously track

multiple moving items more efficiently when compared to FPS players and NVGPs. Possible

explanations of these findings are discussed.

Keywords: cognition, visual attention, multiple objects tracking, video games


1. Introduction

During past two decades the development of computer technologies was unlike ever

before. Instead of using paper maps we can now use GPS systems in our cars to not only

lead us to our destination but also select the road with least traffic. Our mobile phones are no

longer a size of a suitcase, and are even capable of directing us to restaurants which we are

likely to enjoy most. New devices outperform their predecessors at incredible rates; the

processing power of the fastest computers 20 years ago cannot even be compared to the

mobile devices we carry in our pockets today. These devices are often used as form of

entertainment which is not as passive as e.g. television or theatres, but requires interaction

and attention. Studies have shown that video gameplay can lead to improvement in various

abilities, such as spatial visualization (Dorval & Pepin, 1996), visual short-term memory

(Boot, Kramer, Simons, Fabiani, & Gratton, 2008), multi-tasking (Green & Bavelier, 2006a)

or various executive functions (Chisholm & Kingstone, 2012; Colzato, van Leeuwen, van

den Wildenberg, & Hommel, 2010; Karle, Watter, & Shedden, 2010). Interestingly, abilities

gained through gameplay can also correlate with professional skills, such as laparoscopic

surgical manoeuvres (Rosser, et al., 2007). Authors of various studies published so far based

their sampling on action video game players, which is only one of many genres on games

market. The rationale behind it remains unclear because there is no scientific analysis of in-

game content and its potential relationship to cognitive abilities. More attention paid to other

genres may lead to clearer understanding of the effects that game mechanics have on our

cognition.

In this thesis I will review the most recent literature on differences between video

game players’ and non-video game players’ cognitive abilities and the magnitude of

improvement after video game trainings. I will also identify the methodological flaws

present in some past studies, propose improvements, and implement them in a design


concentrated on identifying cognitive abilities differentiating types of video game experience

and its influence on cognitive performance.

1.1. Importance of Technological Advancement and Video Games

Current trends drive technology to be more natural to humans and human

functioning. New devices, such as Google Glass, are being developed so we will no longer

be forced to use traditional displays and instead immerse ourselves in augmented reality. We

can watch films, documentaries or sport events on high resolution stereoscopic displays

which can now be found in every electronics market. Access to highly immersive virtual

environments will soon be much easier for regular consumers due to a newly developed

stereoscopic head mounted display called Oculus Rift (Oculus VR, 2013). Such

advancements are no longer limited to a wealthy audience or researchers only, but are

getting more available every year.

Rapid development of such inventions has made it possible for a large number of

electronic devices around us to be capable of running video games. Personal computers,

gaming consoles, television sets, laptops, tablets, mobile phones, electronic watches, or in-

flight entertainment support games of various complexities.

Since games started to become a common form of entertainment, their mechanics

found in video games were found to be beneficial in real life contexts. Mobile applications,

corporate management systems, or marketing campaigns are often designed with

implementation of various mechanisms extracted from classical personal computers (PC) or

console video games. This process is known under a relatively new term “gamification”,

which means “use of game design elements in non-game contexts” (Deterding, 2011).

The reason why “gamifying” approach has become widely implemented is the

increase of intrinsic motivation in end-users or participants (Hsu & Lu, 2004). This approach

can also find its application in the field of cognitive psychology and benefit people seeking


cognitive improvement. People play games because it gives them pleasure and satisfaction,

unlike classical cognitive training tools. If game mechanics can be extracted and

implemented in other contexts, it is worthwhile to look closer at video game players’

cognitive benefits and find a way to apply them to trainings and rehabilitation.

1.2. Current Research on Improvement of Cognitive Abilities

1.2.1. Cognitive abilities and far transfer

A far transfer of abilities is traditionally defined as “transfer to a dissimilar context”

– an improvement in one ability as a result of training other ability (Barnett & Ceci, 2002).

It has been hypothesised that working memory capacity and reasoning abilities (such as fluid

intelligence – Gf ) are associated with each other (Kyllonen & Christal, 1990; Engle, 2002)

and can share capacity limits (Halford, Cowan, & Andrews, 2007). Jaeggi proposed that

intensive working memory training should benefit Gf (Jaeggi, Buschkuehl, Jonides, &

Perrig, 2008). Her results showed that improvement in Gf was linearly correlated with time

spent on working memory training (when compared to pre-training measures) which utilized

the “dual n-back” paradigm. The results obtained by Jaeggi and colleagues have been

replicated in a following study (Jaeggi, et al., 2010); however, not all similar trainings were

as successful (Thompson , et al., 2013). Jaeggi’s studies also received criticism regarding a

number of methodological flaws present in their designs, such as differences in procedures

applied to four groups in the original study or varying time limits across groups (Redick, et

al., 2012).

When Redick et al. (2012) replicated the study with randomized samples and placebo

control, they concluded that “despite significant improvements on the training tasks, subjects

showed no positive transfer to fluid intelligence, multitasking, working memory capacity,

crystallized intelligence, or perceptual speed tasks.”


1.2.2. Improvement in cognitive abilities through video game training

Recent research shows that an improvement in cognitive abilities can be obtained by

implementing video game trainings, where participants commit their time to gameplay rather

than taking part in particular cognitive tasks. Since a milestone publication in Nature by

Green and Bavelier (2003) where they observed video game players (VGPs) outperforming

non-video game players (NVGPs) in a number of visual attention tasks, over 60 peer-

reviewed papers have been published with focus on potential cognitive benefits stemming

from video game experience.

We now know that VGPs obtain higher scores than NVGPs on various tests of

cognitive abilities, such as multiple objects tracking (Green & Bavelier, 2006b; Boot,

Kramer, Simons, Fabiani, & Gratton, 2008; Dye & Bavelier, 2010) or task switching (Basak,

Boot, Voss, & Kramer, 2008; Colzato, van Leeuwen, van den Wildenberg, & Hommel,

2010; Cain, Landau, & Shimamura, 2012; Green, Sugarman, Medford, Klobusicky, &

Bavelier, 2012; Strobach, Frensch, & Schubert, 2012). While some studies yielded mixed

results for other cognitive tests, such as flanker compatibility (Green & Bavelier, 2007;

Durlach, Kring, & Bowens, 2009; Irons, Remington, & McLean, 2011; Cain, Landau, &

Shimamura, 2012), useful field of view (Green & Bavelier, 2006a; Feng, Spence, & Pratt,

2007; Murphy & Spencer, 2009) or intentional blindness and repetition blindness tasks

(Murphy & Spencer, 2009), a clearer picture has also been obtained by a number of training

studies where NVGPs were exposed to video game training. Researchers found that it is

possible for NVGPs to improve their performance in cognitive ability tasks after relatively

short video game trainings. These improvements were also found to last for several weeks or

months after trainings (Feng, Spence, & Pratt, 2007; Li, Polat, Makous, & Bavelier, 2009).

Additionally, recent findings suggest that far transfer might have its roots in genetic

predispositions through levels of the brain-derived neurotrophic factor, which is a


neuromodulator that underlies cognitive processes (Colzato, van Muiden, Band, & Hommel,

2011). It is therefore still debatable if all players can improve their cognitive abilities from

video gameplay to the same degree, however because of the general trend of increase in

performance at various cognitive tasks, it is important to investigate this field in more

detailed contexts.

1.2. Fields of Improvement

The research conducted so far suffers from lack of attention to game mechanics and

an arbitrary classification of what makes person a gamer. Genres of games also differ from

each other, but researchers either concentrate on just one or combine all players in one

group. Additionally, playing on various devices might also influence the process of cognitive

training. Therefore I will address some of the flaws present in the current peer-reviewed

papers and suggest solutions, which will provide basis for the research design of this study.

1.2.1. Sampling

The authors of many of the studies – although they provide most necessary statistical

information – attempt to generalize obtained effects for the entire population based on small

and not representative groups. The sample sizes of 8-15 per group might not be sufficient for

reliable statistical analysis (Cohen, 2008) when other sampling issues take place, such as

unbalanced groups or inclusion of males only due to difficulties in finding female players,

while keeping the control group dominated by females (for exapmles see: Green & Bavelier,

2006a; Green & Bavelier, 2006b; Green & Bavelier, 2007; Feng, Spence, & Pratt, 2007;

West, Stevens, Pun, & Pratt, 2008; Boot, Kramer, Simons, Fabiani, & Gratton, 2008; Li,

Polat, Scalzo, & Bavelier, 2010; Hubert-Wallander, Green, Sugarman, & Bavelier, 2011).

For this reason I propose a large gender balanced sample of 30 participants per group.


1.2.2. Gameplay time

One major flaw of current research on video game players (VGPs) is arbitrary

assessment of who is a game player and who is not. It is common for researchers to put the

cut-off-line at between 3 and 4 days per week within the past six months without specific

time requirement (Green & Bavelier, 2006a; Green & Bavelier, 2006b; Colzato, van

Leeuwen, van den Wildenberg, & Hommel, 2010), 7 hours per week for at least past 6

months (Murphy & Spencer, 2009), also 7 hours per week, but for at least past two years

(Boot, Kramer, Simons, Fabiani, & Gratton, 2008), or “action video games at least 4 days

per week for a minimum of 1 h per day for the previous 6 months” (Green & Bavelier,

2003). However, researchers so far have treated all of these criteria liberally by assessing

frequency but not duration or going as low as 3 hours per week (Green & Bavelier, 2006a;

Colzato, van Leeuwen, van den Wildenberg, & Hommel, 2010; Chisholm, Hickey,

Theeuwes, & Kingstone, 2010; Karle, Watter, & Shedden, 2010; Irons, Remington, &

McLean, 2011; Chisholm & Kingstone, 2012; Green & Bavelier, 2006b). It is difficult to

assess where the cut-off should lay; however, playing for less than half an hour a day can

hardly be described as constant use of something as involving, such as watching movies,

driving a car or sports training. Video gameplay is a form of entertainment media similar to

watching television. In Poland over 80 percent of people watch television every day and 50

percent watch it over two hours a day (Central Statistical Office, Social Surveys and Living

Conditions Statistics Department , 2012). I therefore propose for this thesis a minimum

gameplay time of 7 hours per week within past 6 months as a minimal criterion for

classification as a video game player.

1.2.3. Genre and display time

Most studies have failed to report types of games played and/or devices used, or have

tested only action video game players. It is however extremely important for our


understanding of cognitive processes to determine both the types of games (which utilize

different skills and cognitive abilities) and the type of devices. Genres also differ from each

other (which is discussed in detail in the next section). There is a tremendous difference

between low-action adventure games and heavily packed first person shooting (FPS) or real

time strategy (RTS) games. The number of objects requiring attention and actions required to

be performed in a limited time are components which can heavily weigh on performance in

tests of cognitive abilities. Elderly training with RTS games have already shown

improvement in executive control functions (task switching, visual short-term memory,

working memory) (Basak, Boot, Voss, & Kramer, 2008).The differences between devices

may also directly influence the experience and gameplay, e.g. field of view when playing on

mobile phone differs from when playing on portable gaming device or PC or large TV set

(which is typical for gaming consoles).

I therefore propose the inclusion of only participants playing on large displays (PC

and console) because the field of view they experience in games is larger and more likely to

stimulate visual attention. I also propose use of FPS and RTS players only in order to

identify most beneficial environments from two of the most popular genres.

1.2.4. Object-based attention

When trying to understand how video game players allocate attentional resources

with multiple objects present, some studies have showed that VGPs perform better than

NVGPs in enumeration task (Green & Bavelier, 2006b). In this task participants are asked to

observe multiple quickly flashed squares and determine their number; however, other results

of replication study did not yield such results (Boot, Kramer, Simons, Fabiani, & Gratton,

2008).

In their research Green and Bevalier (2006b) aimed to verify whether the processing

of multiple objects at the same time can be facilitated by video gameplay. They implemented


the multiple objects tracking paradigm to address this question. In this task they were asked

to track various number of circles moving within the field of view. This task requires

allocating attention to a number of objects within the field of view and tracking their

changing position for a short period of time. Their results showed that VGPs were able to

track approximately two more objects when compared to NVGPs. Additionally, they found

that NVGPs trained with action video games can improve their performance at MOT. In a

cross-sectional study, Boot, Kramer, Simons, Fabiani and Gratton (2008) replicated the main

effect of group where VGPs significantly outperformed NVGPs; however, they failed to find

a significant result for longitudinal groups.

Tasks in which participants are asked to visually track multiple objects at the same

time require allocation of visual attention to multiple items. This task differs from other

attentional tasks, as it requires connecting attention to targets and maintaining this

connection in an environment rich of distractors (Cavanagh & Alvarez, 2005). Therefore it

informs how (to how many targets) the attention can be divided within the field of view in a

rich, changing environment. Selection, tracking and encoding are important functions

required for many everyday activities (such as driving a car on a busy road or playing

football) and specialist occupations (e.g. air traffic control, overseeing swimmers by a

lifeguard). The possibility of training them may be extremely beneficial for patients

suffering from impaired cognitive functioning who seek neurorehabilitation as a result of

their disorder or trauma. Additionally, the ability to track multiple objects decreases with age

– young individuals can easily track 4 moving objects at the same time, while elderly is

capable to track on average only 3 objects simultaneously (Trick, Perl, & Sethi, 2005). It is

therefore important to evaluate the possibility of video game training as a motivating tool for

improvement of visual attention especially also for the elderly. In this study I propose to

extend the study of Green and Bavelier (2006b) by replicating their MOT procedure with


addition of real time strategy players as they may show larger improvements in performance

than first person shooting game players.

1.3. Video Games Genres and Their Players

There are different ways to classify video games based on various criteria. In past

research games classified as action genre were at least questionable, as its definition was

based on Green & Bavelier’s (2006a) description: “(games) that have fast motion, require

vigilant monitoring of the visual periphery, and often require simultaneous tracking of

multiple targets”. This general description can match most of the genres available on the

market, which led to classifying as action VGPs all participants playing anything from

Counter-Strike (first-person shooter) or Grand Theft Auto series (third-person action-

adventure) to Marvel vs. Capcom (fighting) or even Super Mario Kart (racing game).

Most commonly, games are classified into certain genres based on their type of

gameplay as opposed to differences in their audio-visual or narrative components (Apperley,

2006). Unlike other forms of fiction, such as books, films or plays, video games are

classified independently from the setting or world they present. With more games being

created many borders between genres tend to overlap. As a result, a simplified classification

was proposed for this study’s recruitment (for details see Appendix A) and two genres were

selected for the purpose of this study.

1.3.1. First person shooters

Commonly known as FPS, this type of game simulates combat from the first person

(egocentric) perspective of a player-controlled protagonist. The perspective of a soldier is

intended to elicit a feeling of presence, or “feeling of being there” (Lombard & Ditton,

1997), in the environment and participating in the action as it would look like in real life.

Although many FPS games provide players with single-player experience where opponents


and allies are controlled by artificial intelligence algorithms, this genre is mostly experienced

in multiplayer mode (with other players). These two modes do not differ much on a first

look, but differ in consequences of undertaken actions. Activities required from a player

differ between the modes both by qualitative and quantitative means.

In single player the protagonist is most commonly led by a scripted linear scenario

and mistakes usually do not have many consequences aside from necessity to replay the

failed part. Player is often supported by other computer-controlled soldiers and is not

required to be aware of their location.

In multiplayer mode motivation is often dependent on mistakes which are punished

by a waiting period to re-join the game, lower scoring points and decrease in team progress.

This mode is usually preferred by frequent FPS players (because each game provides novel

or different experience) and it often requires higher motor coordination skills, observing a

map in a corner which displays surroundings (Figure 1), making decisions about directions

of attack, controlling resources (ammunition) and controlling body movement, often

communicating with other players at the same time through voice or in-game chat.

Additionally there are various multiplayer modes available in games, ranging from “free for

all” where player has to shoot all other players, team death-match where two teams compete

between each other in number of killed enemies, to more objective based, where one team

defends certain area from other team or has to steal an object protected by another team.

Although these activities are complex in some ways, tracking multiple objects is

required mostly incidentally. The field of view of the protagonist is restricted and limited by

the number of objects which can appear in front of him. Therefore, most of the time the

focus remains in the centre of the screen where the reticule is displayed, with occasional

saccades (switching point of fixation from one position to other) to corners with map display

or gear summary.


Figure 1. Screenshot from Battlefield 3 gameplay (Psygeist, 2012).

1.3.2. Real-time strategy

The real-time strategy genre is commonly known as RTS, but often is also

incorrectly generalized as “strategy games”. In this genre action of the game is continuous

(as opposed to turn-based strategies, where time restrictions are of lower importance). In this

genre player typically sees the game from top-down (allocentric) perspective where multiple

animated elements of the game are presented on the screen simultaneously. Classical RTS

consists of three components: managing resources (such as blue crystals on Figure 2),

developing infrastructure (cubical building), as well as developing army and performing

military operations. All these activities often take place within a single “screen” which leads

to a necessity of observing multiple, often moving, objects within the field of view at the

same time and remaining updated at all time. This genre is characterized by high frequency

of various actions to which the player has to react. During the game the time spent on

activities is important; therefore players usually control the progress of other game elements


with help of peripheral vision, while focusing on one point of attention. Because of that, this

genre resembles the multiple objects tracking paradigm more than first person shooting

games

Figure 2. Screenshot from Starcraft 2 gameplay (HuskyStarcraft, 2013).

Similarly to FPS, RTS games are commonly played in a multiplayer mode. The

differences between single and multiplayer modes usually narrow down to the level of

difficulty, where playing with human opponent is usually considered more challenging due

to less predictable behaviour.

To summarize, the difference between these two genres with regard to multiple

objects paradigm is rooted in their core mechanics. In FPS games player has narrower field

of vision and moves across the map with actions performed only when the stimulus is

present just in front of him. In RTS games player oversees the map from above, controls

multiple units and resources simultaneously, and has to be aware of complex and detailed

environment.


1.3.3. Who are video game players

In recent TNS OBOP report (2011), in Poland 31% of females and 39% of males

declared that they played a game within a past month. The current mean age of video game

players is around 35 years old, where 32% of players are under 18 years old, 32% is aged 18-

35 years and 36% has 36 years or more; with mean of 15 years of gameplay experience

(Entertainment Software Association, 2013). While gamers age, they tend to play less

frequently, which they commonly explain as lack of sufficient time rather than disinterest. It

is therefore important to work on and create tools which would be able to stimulate cognitive

abilities based on mechanisms derived from video games, but at the same time being less

time consuming. Motivating people to train and improve by decreasing the required training

time and allowing access through devices of everyday use (e.g. mobile phones) can result in

much easier access to cognitive improvement. In order to achieve this goal, it is important to

identify key elements of video games which are possible to extract and implement into

training tools.

When asked about types of games played (Draszanowska, Gańko, Samołyk, Sroka,

& Strzałkowska, 2012), males listed their preferences for racing games (46%), logic games

(43%), action (43), strategy (41%), adventure (38%), or sport (36%), however they did not

report any information regarding the frequency or preference of one genre over another.

Females on the other hand listed most commonly logic games (70%), followed by adventure

(46%) and strategy (27%). These differences in preferences are key to understanding how

video games are classified, which ones appeal to either gender, and who can be addressed

with trainings based on components extracted from a particular genre.

During past ten years demographics of players changed and teenagers back then now

continue their hobby as adults. In that time research on cognitive abilities and video games

expanded and resulted with more publications than ever before. Most of the research


concentrated on tests of cognitive abilities: processing speed, mental flexibility, executive

functions, and other attentional processes. Both cross-sectional and training studies have led

to conclusion that some benefits experienced by video game players can be achieved by

NVGPs after sufficient training regime. Since combining the motivational factor of video

game environments with their potential cognitive benefits has already been considered an

alternative to classical cognitive trainings, now it is time to make sure that such tools will be

created on grounds of scientific research. It is therefore important to understand who the

people playing video games are and whether there is something specific about this group

before attempting to replicate or measure benefits of this group .

The possibility of creating a more efficient cognitive training paradigm is important

not only for persons seeking self-improvement for professional or personal reasons, but are

also a key factor for patients with cognitive impairments. Aside from neurorehabilitation

issues, current developed and developing countries struggle with the aging of their societies.

In order to counter the effects of cognitive aging (such as decrease in working memory

capacity or perceptual/processing speed), an efficient and motivating form of cognitive

training can substantially benefit the elderly and later days of current adults' lives.

2. Research Problems

Recent literature on visual attention and video gameplay is based mostly on either a

broad group of video game players or focuses on action video game players as a niche.

Hubert-Wallander, Green and Bavelier (2011) in their review point out that “studies have

shown, for example, that visual attention remains unchanged after training on strategy games

like Rise of Nations.” This statement refers to a training study conducted on older adults

where cognitive changes were observed after 23.5h training regime (Basak, Boot, Voss, &

Kramer, 2008). Even though participants training with strategy games did not improve on

some executive control and visuospatial tasks, they showed improvements in executive


control functions: task switching, working memory, visual short-term memory, reasoning.

The purpose, and yet one of the limitations of this study is its restricted elder sample. Failing

to reproduce some of the effects observed in younger population informs us about different

learning capacity between these groups. However, it does not explain if there are changes

among current players and if so – how they compare with other genres’ frequent players.

Lastly, they did not utilize the multiple objects tracking paradigm which out of various

visuo-spatial attention tasks seems to be most closely related to real time strategy games.

In order to address this gap, this thesis will address following research questions:

Can playing games benefit the ability to track multiple objects

simultaneously?

Does playing real time strategy games benefit multiple objects tracking

more than playing first person shooters?

Are real time strategy games similar to multiple objects paradigm more

than first person shooters?

If action video game players are indeed better at tracking three, four and five circles

at the same time when compared with non-video game players, as presented by Green and

Bavelier (2006b), in this study the FPS group should outperform the NVGP group when

three, four or five circles have to be tracked. If the assumption, that the MOT task is more

similar to classical RTS mechanisms than to mechanics of FPS games is true, then not only

RTS players should outperform FPS players, but also outperform the NVGP group. Finally,

a manipulation check will be done by asking the participants after the procedure whether

MOT mechanics are more similar to RTS games compared with FPS games.

With the purpose of addressing these questions a study with RTS and FPS players

has been conducted. As a control group participants with no video gameplay experience


were tested. The following hypotheses were formulated in order to address the research

questions:

2.1. Hypothesis #1

First Person Shooter players will perform significantly better at Multiple Objects

Tracking compared with Non-Video Game Players as measured by overall accuracy.

2.1.1. Hypothesis #1a

When difficulty increases at three, four and five simultaneously moving objects,

First Person Shooter players will perform significantly better at Multiple Objects Tracking

compared with Non-Video Game Players.

2.2. Hypothesis #2

Real-Time Strategy players will perform significantly better at Multiple Objects

Tracking compared with First Person Shooter players as measured by overall accuracy.


When difficulty increases at three, four and five simultaneously moving objects,

Real-Time Strategy players will perform significantly better at Multiple Objects Tracking

compared with First Person Shooter players.

2.3. Hypothesis #3

Real-Time Strategy players will perform significantly better at Multiple Objects

Tracking compared with Non-Video Game Players.


When difficulty increases at three, four and five simultaneously moving objects

Real-Time Strategy players will perform significantly better at Multiple Objects Tracking

compared with Non-Video Game Players.


2.4. Manipulation check

Real-Time Strategy players will report that Multiple Objects Tracking task is more

similar to the games they primarily play compared with First Person Shooter players.

3. Method

In everyday life, when walking in the city or looking at a landscape, we observe a

montage of many objects at the same time. We carry out saccades (quick movement of eyes

from one point of focus to another) and fixate (briefly pause) on points of interest (Goldstein,

2008). However, we also pay attention to objects which are not in our direct line of sight. We

are able to identify them quickly without focusing on each one separately (Kosslyn, 1996).

Visual attention is a cognitive process of concentrating on selected elements within

the visual field while ignoring others (Martin, Carlson, & Buskist, 2007). The multiple

objects tracking (MOT) paradigm was pioneered by Zenon Pylyshyn (Pylyshyn & Storm,

1988). It is a technique used to study how multiple moving objects are tracked by the visual

system independent of eye movement.

Alterations in visual attention and perceptual processes as well as visuo-motor

coordination can be an effect of video gameplay (among both adults and children), as shown

by numerous researchers (Gopher, Well, & Bareket, 1994; Greenfield, DeWinstanley,

Kilpatrick, & Kaye, 1994; Dorval & Pepin, 1996; Clark, Fleck, & Mitroff, 2011; Green,

Sugarman, Medford, Klobusicky, & Bavelier, 2012; Strobach, Frensch, & Schubert, 2012).

3.1. Participants

All participants in this study were recruited via an online screening questionnaire

from gumtree.pl announcement website, and from students of University of Social Sciences

and Humanities. All participants received monetary compensation for taking part in this

study (10zl). Additionally, afterwards they could have taken part in other procedures carried


out that day in the laboratory, which allowed them to receive additional compensation (20zl).

All signed informed consent forms in which they also declared to be over 18 years old, not

being under influence of alcohol or any psychoactive substances, and that are able to read

and understand Polish language fluently. None of the participants were colour-blind for red

and green and all of them had good or corrected vision.

A total of 90 participants were recruited from 1864 volunteers. The main aim of the

study was to compare performance between FPS, RTS and NVGPs. In order to recruit

persons playing predominantly one type of video game, participants were recruited based on

several strict criteria.

3.1.1. Genre and mean gameplay time

Participants were assigned to either one of three groups: VGPs playing primarily

First Person Shooters (n=30), VGPs playing primarily Real Time Strategies (n=30) and

NVGPs (n=30). In order to be assigned to either of VGP groups participants had to declare

their weekly mean time committed to this particular genre as minimum of seven hours a

week in past 6 months.

For example, in order to make sure that participants are primarily FPS players they

could not play RTS more than 5h per week and vice versa. Other genres were controlled for

and did not influence the selection during recruitment process. In order to create an

appropriate sample, NVGP group members could not play more than 2h a week FPS and

RTS in total (for details see table 1) and more than 5h a week of all genres in total.

Table 1

Gameplay time across the groups

Group

Hours spent playing

FPS games per week

Hours spent playing

RTS games per week


M SD M SD

FPS group 18.83 6.55 0.70 1.51

RTS group 1.87 1.83 19.10 8.62

NVGP group .50 .82 .20 .55

3.1.2. Age

All persons taking part in the study had to be at least 18 years old. In order to

decrease a possibility of aging processes significantly skewing the results, participants’ age

limit has been set to 35 because it should include the middle 1/3 of gaming population, but

also to limit the possible effects of cognitive aging on the performance in test (Basak, Boot,

Voss, & Kramer, 2008; Cebeza, et al., 2004). Mean ages of participants within each category

were as follows: MFPS = 22.13, SD = 3.93; MRTS = 22.23, SD = 4.50 and MNVGP = 25.40, SD =

4.40.

3.1.3. Gender

In order to control for possible differences, gender has been controlled for during the

recruitment process. Each group had 2 female members. It should be noted that only 2

female players meeting recruitment criteria for each gamers’ category could be found (which

keeps them balanced across the samples). Since they were recruited from a large sample of

over 1800 volunteers, it is possible that such gender composition might be close to

representative of the population and therefore it is more likely to compose an ecologically

valid sample.

3.2. Materials

3.2.1. Multiple objects tracking

For the purpose of this study special software was created. The specifications were

based on the task used in a study by Green and Bavelier (2006b). In this procedure


participants were seated with their eyes approximately 65 centimetres away from the screen

and the distances and sizes of objects on the screen were calculated to match the angular

values as in the original study. Participants fixated at the centre ring (.25°) on the screen and

pressed spacebar in order to proceed to the next trial. During each trial a circular grey

background (r=10°) was displayed with 16 circles (.5°) moving towards random directions at

rate of 5°/s. With minimum separation between the circles of .5°, when contacted they would

repel each other.

As demonstrated on figure 3, at the beginning of each trial a random number of

circles (1-7) turned colour to red, while the rest remained black. Participants’ task was to

attend to the red circles, which after 2 seconds changed colour back to black, and track their

position. At this point all of the 16 circles were coloured black. After 5 seconds of all circles

moving towards random directions, one circle changed colour to yellow. Participants’ task

was to respond whether the yellow circle was originally highlighted in red. The answer was

given by either pressing the “Z” button (yes) or “M” button (no) on keyboard.

Each number of simultaneously highlighted circles (between one and seven) was

presented randomly 10 times with correct “yes” response” and 10 times with correct “no”

response, thus the total number of trials was 140. Despite the fact, that no differences in

accuracies were expected in conditions with 1 or 2 highlighted circles, these conditions

remained in the procedure. If participants would answer randomly they would be likely to

achieve accuracy of around 50%. If they would answer either “yes” or “no” to all of the

trials, their accuracy would also be close to 50%. Such discrimination may not be possible in

more difficult conditions, as the likelihood of answering correctly should decrease together

with increasing number of circles.

In order to familiarize participants with the procedure, before the experiment started,

participants took part in three practice trials, where 1, 2 and 3 objects were highlighted.


Figure 3. Multiple Objects Tracking. 1. Trial starts. 2. While focused on the centre ring,

some of the circles change colour to red. 3. Circles return to their original colour and move

randomly within the gray circle. 4. One circle is highlighted and participant responds with

“Z” (yes) or “M” (no) on the keyboard. 5. Participant receives feedback. 6. Participant

continues to the next trial.

3.2.2. Hardware

The MOT task was displayed on 22 inches (diagonally) ViewSonic VX2268wm

LCD monitor with refresh rate of 100Hz. The display was 60cm away from the participants’

eyes. Participants responded to the test using a mechanical keyboard. JVC HA-NC250

headphones with active noise cancellation were used in order to minimize disruption.


3.2.3. Lab environment

All participants were tested in the same laboratory at the same work station. The

height of the chair was adjustable. There was no distraction caused by noise from the

outside. The room was illuminated throughout the entire procedure.

3.3. Design

A 3 (FPS / RTS / NVGP) x 7 (no. of circles to track) factorial design was used.

Participants were assigned to their groups by the time of gameplay in either FPS or RTS or a

lack of thereof. Groups were matched in age (18-35) and gender (balanced across the

groups) in order to decrease a possibility of these factors affecting the results. Mean

gameplay time was controlled for to make sure that an extreme (over 40h/week of declared

gameplay time, which is equivalent to full-time job) player will not affect the results.

Correct and incorrect responses were recorded for all trials where 1-7 circles were

highlighted. A mean score of 20 trials for each of 1-7 circle cases was calculated, resulting in

7 dependent variables. While

A final check has been done to verify whether the task was more similar to the games

FPS and RTS players usually play.

3.4. Procedure

Participants were recruited through online screening questionnaire designed to

identify participants appropriate for either of the three groups. Questions about age, gender,

education, video game habits and contact details were gathered.

Participants who completed the questionnaire and met the recruitment criteria were

individually scheduled for the study. All of the sessions took place in the Virtual Reality

Laboratory (VRLab) of the Institute of Psychology, Polish Academy of Sciences.

Participants filled in a consent form and were informed that they are allowed to discontinue


the experiment at any given time without repercussions. Additionally, they were informed

that the group they belong to should achieve higher scores. This attempt to equalize the

motivational levels has been derived from Strobach, Frensch and Schubert’s (2012)

recruitment procedure, where the advertisement of their study was promoted by two types of

flyers addressed to VGPs and NVGPs separately. This manipulation has been implemented

as a response to Boot, Blakeley and Simons’s (2011) critique. They argued that players

recruited because of their gaming experience to a study, where the tests are game-like, may

expect to perform better. Such expectation, as a result, may influence the performance on the

test. The influence of mind-set has already been shown to influence the results of visual

acuity tests (Langer, Djikic, Pirson, Madenci, & Donohue, 2010). Participants were also

informed that their results will not be analyzed individually and they will not receive an

overall accuracy score. Afterwards, participants sat down in front of the computer, adjusted

their seat and were asked to remain in that position for duration of the study. Participants

were informed that in case of any questions or doubts they should not proceed further with

the experiment but ask the experimenter for assistance. Once they put headset on, they read

instruction and when ready preceded to three practice trials. After three training trials they

were informed that the total number of trials to follow is 140 and in order to initiate the next

trial, they have to press spacebar.

Each MOT procedure lasted around 30-35 minutes. Upon completion, participants in

FPS and RTS groups were asked to assess how similar the test was to the type of game they

play most. They provided answers on a paper-based seven-level Likert scale answer sheet

where 1 meant “not at all” and 7 meant “very much”.

Afterwards participants were thanked and informed of real hypotheses of the study.

They received their compensation and confirmed it with their signature. The entire procedure

was carried out with respect to APA ethical guidelines.


4. Results

In this study all answers were coded as 0 (incorrect) and 1 (correct). For each circle

condition 10 correct answers were “yes”, and 10 correct answers were “no”. Scores for each

circle condition were added together and divided by the number of times they occurred (10

“yes” and 10 “no” resulting in total of 20). Therefore separate mean accuracies of each

participant for each number of circles were placed on a scale from 0 (0% correct) to 1 (100%

correct). The mean accuracy across all trials was calculated by addition of all individual

accuracies for all responses and divided by the number of occurrences (7 circle conditions x

20 “yes” and “no” = 140).

During the study, data of two FPS players was lost due to technical difficulties.

Additionally, two outliers (belonging to the RTS group) were found by analysis of z-scores

at 2.5 standard deviations threshold. Their mean accuracies were lower than means of any of

the groups (M = .58, M = .64). Throughout the experiment it has been noted that they did not

pay attention to the instructions and kept looking away during trials. One failed to track

neither of 1, 2 nor 3 circles during practice trials, the second one kept answering “yes” to

most of the trials. None of the female participants were outliers and their scores did not

significantly differ from males in any of the groups (ps > .5); therefore female and male data

were analyzed together. Following accuracy analyses were conducted on 28 FPS players, 28

RTS players and 30 NVGPs. An overall main effect of groups: FPS: M = .791 , SD = .055;

RTS: M = .823, SD = .044; NVGP: M = .782, SD = .054; F(2,83) = 4.91, p = .01 was

observed.

4.1. Hypothesis #1

A one-way analysis of variance was run to determine the effect of video game

experience of action video game players on performance in multiple objects tracking test of

visual attention. Seven measures of accuracy for number of circles 1-7 were assessed.


Participants were assigned into two groups based on their video game experience: if they

played primarily FPS games, they were assigned to FPS group. If they met the requirements

of NVGP group as described in methods section of this thesis, they were assigned to NVGP

group.

In order to test hypothesis #1, results for samples of 28 FPS players and 30 NVGPs

were analyzed. There was homogeneity of variances, as assessed by Levene's Test of

Homogeneity of Variance (p > .05). No main effect of group was observed F(1,56) = .349, p

= .557.


Individual analyses for each number of circles indicated a no significant or marginal

differences between groups (Figure 4).

Figure 4. Mean accuracy of FPS and NVGP groups for each number of circles on a scale

from 0 (0% correct responses) to 1 (100% correct responses). Error bars represent standard

errors.

0,55

0,6

0,65

0,7

0,75

0,8

0,85

0,9

0,95

1

1 2 3 4 5 6 7

Co

rre

ct r

esp

on

ses

Number of circles

FPS

NVGP


4.2. Hypothesis #2





played primarily FPS games, they were assigned to FPS group, if they played primarily RTS

games, they were assigned to RTS group

In order to test hypothesis #2, results for samples of 28 FPS players and 28 RTS

players were analyzed. There was homogeneity of variances, as assessed by Levene's Test of

Homogeneity of Variance (p > .05). Main effect of groups was observed F(1, 54) = 5.721, p

= .02.


Individual analyses for each number of circles indicated a significant advantage (p =

.038) for RTS players (M = .900, SD = .0667) over FPS players (M = .852, SD = .099) only

for three circles to track (Figure 7).

Additionally, there was marginally significant advantage (p = .066) for RTS (M =

.679, SD = .093) over FPS group (M = .625, SD = .119) for seven circles to track.


Figure 5. Mean accuracy of FPS and RTS groups for each number of circles on a scale from

0 (0% correct responses) to 1 (100% correct responses). Error bars represent standard errors.

* p = .038

4.3. Hypothesis #3





played primarily RTS games, they were assigned to RTS group. If they met the requirements

of NVGP group as described in methods section of this thesis, they were assigned to NVGP

group.

In order to test hypothesis #3, results for samples of 28 RTS players and 30 NVGP

players were analyzed. There was homogeneity of variances, as assessed by Levene's Test of

0,55

0,6

0,65

0,7

0,75

0,8

0,85

0,9

0,95

1

1 2 3 4 5 6 7

Co

rre

ct r

esp

on

ses

Number of circles

FPS

RTS

*


Homogeneity of Variance (p > .05). Main effect of groups was observed F(1, 56) = 9.610, p

= .003.


Individual analyses for each number of circles indicated a significant advantage (p =

.011) for RTS players (M = .900, SD = .067) over NVGP group (M = .840, SD = .101) for

three circles to track, a significant advantage (p = .004) for RTS players (M = .829, SD =

.075) over NVGP group (M = .752, SD = .113) for four circles to track. It has not been

hypothesized, however a significant advantage (p = .033) for RTS players (M = .679, SD =

.093) over NVGP group (M = .620, SD = .111) for seven circles to track was found (Figure

7).

Additionally there was marginally significant advantage (p = .069) for RTS players

(M = .991, SD = .024) over NVGP group (M = .977, SD = .034) for one circle to track and

marginally significant advantage (p = .066) for RTS players (M = .752, SD = .125) over

NVGP group (M = .693, SD = .112) for five circles to track.


Figure 6. Mean accuracy of RTS and NVGP groups for each number of circles on a scale

from 0 (0% correct responses) to 1 (100% correct responses). Error bars represent standard

errors. * p = .011, ** p = .004, *** p = .033


An independent-samples t-test was run to determine if there were differences in

similarity of MOT and games played either by RTS or FPS players. Mean scores were not

normally distributed, as assessed by Shapiro-Wilk's test (p < .05); however, the independent-

samples t-test still can be considered robust because it does not substantially affect Type I

error rate. The assumption of homogeneity of variances was violated, as assessed by

Levene's Test for Equality of Variances (p = .019). The Multiple Objects Tracking task was

more similar to games played by RTS players (M = 6.10, SE = .194) than FPS players (M =

5.00, SE = .299 ) as presented on Figure 6. This difference was statistically significant, t

(49.681) = -3.084, p = .003.

0,55

0,6

0,65

0,7

0,75

0,8

0,85

0,9

0,95

1

1 2 3 4 5 6 7

Co

rre

ct r

esp

on

ses

Number of circles

RTS

NVGP

*

**

***


Figure 7. Declared mean similarity of Multiple Objects Tracking task for each players group

(FPS and RTS) on a scale from 1 (not similar) to 7 (very similar). Error bars represent

standard errors.

5. Discussion

The purpose of this thesis was to address the research findings on video games and

visual cognition. I tried to verify whether video games can benefit the ability to track

multiple objects simultaneously over time, whether there is a difference between two of most

popular genres (FPS and RTS) and whether there is a similarity of RTS games and MOT

task.

5.1. Verification of Hypotheses #1 and #1a

Contrary to the results presented by Green and Bavelier (2006b), no presence of

main effect of group and lack of significant differences in performance across all difficulty

conditions indicate that FPS players do not outperform NVGPs in their ability to track

0

1

2

3

4

5

6

7

Me

an s

imila

rity

of

MO

T to

gam

es

pla

yed

FPS

RTS


several objects simultaneously over time. These results contradict the findings of Green and

Bavelier, however for the purpose of this study participants had to play more hours per week

and primarily FPS games in order to be classified as action video game players. Green and

Bavelier did not provide any information about means and standard deviations of mean

gameplay time in their sample, therefore it is possible that their results might have been

influenced by sampling. In order to decrease the possibility of that happening, I increased the

sample sizes three times compared to the original study. Failing to replicate the original

study suggests that action VGPs do not outperform NVGPs in MOT task and the first

hypothesis cannot be supported.


The results showed difference in advantage of RTS over FPS players for three

simultaneously tracked circles only. When tracing more or less than three circles, RTS

players were not significantly better than FPS players. Therefore the hypothesis is partially

supported, because the results show an advantage of RTS players in tracing three moving

items.


When RTS players were compared to the NVGP group, on average they performed

better at tracing three or more circles simultaneously. As expected, the cases with three and

four circles showed significant differences between the groups. Surprisingly there was also

an advantage of RTS players in tracing seven items. Such result was not expected not only

because tracing that many objects should be very difficult for everyone, but also because

there was only a marginal advantage of RTS group at five circles and no advantage at six

circles.


However, these results support the hypothesis that in general RTS players are able to

track more items simultaneously when compared to NVGPs, but the advantage fades when

five objects need to be tracked.


A main finding of this hypothesis is that MOT task is perceived by RTS players as

more similar to the games they play, when compared with FPS players, which supports the

hypothesis #2. Therefore it is more likely that due to familiarity of MOT mechanics, RTS

players will outperform FPS players.

Table 2

Summary of differences in mean accuracies between compared groups for each difficulty

level (measured in no. of circles tracked).

Difficulty FPS vs. NVGP FPS vs. RTS* RTS vs. NVGP*

1 circle − − −

2 circles − − −

3 circles − RTS better a RTS better

b

4 circles − − RTS better c



7 circles − − RTS better d

Note. Only statistically significant results are presented.* - significant main effects of group.

a denotes p = .038.

b denotes

p = .011.

c denotes p = .004.

d denotes p = .033.


5.6. Summary

The results show that differences between RTS, FPS and NVGPs in the ability to track

multiple objects simultaneously differ from what we knew so far. The advantages do not

support previous claims of the original study that action video game players outperform non-

players (Green & Bavelier, 2006b). As presented in table 2, the overall results indicate that

there is a limit in advantage from playing RTS games. Even though the RTS group

performed better than NVGPs at tracking seven objects, the advantages seem to disappear

earlier, at tracking five items.

It is important for the future research to not only pay more attention to game genres

when designing the studies, but also begin investigating possible advantages of playing

various types of games. This study concentrated on measuring the accuracy at MOT task,

however investigating reaction times and manipulating the speed of objects’ movement may

provide more details on differences in visual attention among players of different genres.

Similar approach, where researchers pointed out that not all video games are equal and may

yield various independent cognitive benefits, has already been taken by Boot, Kramer,

Simons, Fabiani, and Gratton (2008), but they did not report any in-depth analysis with

separation by game genre. This study concentrated on effects of RTS video games, where

players are required to keep numerous items in short-term memory, visually follow multiple

moving objects simultaneously, process presented information and make concious decisions

at the same time. These tasks all together are more complex than for example puzzle games

(Green & Bavelier, 2006a; Green & Bavelier, 2006b; Green & Bavelier, 2007; Feng, Spence,

& Pratt, 2007), or life simulation games (Li, Polat, Scalzo, & Bavelier, 2010; Green,

Sugarman, Medford, Klobusicky, & Bavelier, 2012) which are often used as control groups’

training tasks. These results show that while investigating cognitive benefits of video games,


researchers must first understand mechanisms of more video game genres and do not treat all

of them as equal.

5.7. Methodological Observations

Based on prior research by Green and Bavelier (2006b) we know that eye-movement

from the centre greater than 1° happens fairly rarely (c.a. 6%) and was consistent across

groups, however due to lack of appropriate equipment, no eye-tracking check has been done.

One of the limitations of this study was lack of appropriate equipment which would

support participants’ heads in steady position. Such device would assure that the angle of

view would remain standardized across the participants.

When studying video games, the main limitation of cross-sectional design is lack of

control over video game experience during childhood and throughout adolescence. Video

game players usually start playing games earlier in their life, which means that they have

thousands of hours of gameplay experience with video games. For this reason studies on

video games may give different results when concentrated on training either children or

adults inexperienced with video games. Another disadvantage of the cross-sectional design is

the fact that it is impossible to explain whether the group, which outperformed others, did so

because they benefited from their experience, or rather they are more likely to play video

games simply because it is easier for them and they can outmatch others thanks to higher

initial skill levels.

Additionally, an important observation is a number of RTS players who (after the

experiment session was over) described the MOT task as “fun”. Such claims were not as

common in FPS or NVGP groups. It supports the results of RTS players judging it as more

similar to the form of entertainment of their choice; however it could have also influenced

their performance due to increased familiarity of the tasks’ rules. In order to minimize the

differences in motivation between the groups, a manipulation has been has been


implemented, where participants of both groups were told prior to the study, that they should

perform better. They were informed that this is not a diagnostic study and their results will

only be analyzed on a group level; however it is still possible that participants who do not

enjoy competition could feel more pressure on themselves, which could affect their

performance. This could especially be the case of NVGPs, who might not play games simply

because of its common competitiveness.

5.8. Closing Remarks

Researching video games and their effects on cognitive performance is interesting

because classical cognitive trainings are recently found not to be as effective as thought

before. If their elements of fun and intrinsic motivation could help the society to slow down

the process of cognitive aging, the benefits would be a step forward in use of modern

technologies.

The results of this thesis show that research on cognitive improvement and video

games should not be narrowed to players of action video games only. In this study only the

multiple objects tracking paradigm was implemented, while investigating visuospatial

abilities of gameplay requires more encompassed sets of studies. Nevertheless, results of this

study indicate the need for more accurate replication of previous researches. Moreover,

research done so far concentrates mostly on samples of FPS gamers or video game players in

general. The rationale behind it is unclear because not a single study attempted to analyze

elements of particular genres and their similarities to various cognitive tasks.

Research on cognitive improvements through video gameplay is very important in

the context of changes which modern societies undergo. We play games on numerous

devices; children from early years are more familiar with electronic interfaces than with

handwriting, thus taking advantage of these changes may provide revolutionary benefits. It is

too early to fully study the generations brought up on video games, but perhaps in upcoming


years we will be able to explain the correlation between the cognitive skills and video games,

and apply them in more scientifically controlled trainings. Such trainings might also play a

vital role in neurorehabilitation of patients seeking cognitive improvement.

It is important to verify if video games indeed improve cognitive skills and these

correlations are not present because, for example, people with good cognitive abilities are

better at games and therefore play them. Additionally, future research should investigate not

only improvements in laboratory tasks, such as MOT, but also observe improvements in

everyday life tasks, such as ability to notice multiple road signs while driving, find persons

of interest from within a crowd or play various types of sports. This task is very specific and

differs from other attentional tests used by researchers. It answers a very particular question

of the limit, as to how many connections with targets can be maintained simultaneously,

while they are not only in motion, but also among distractors which are also changing its

position (Cavanagh & Alvarez, 2005). However, more in-depth studies are required to

investigate individual abilities required for successful multiple objects tracking. Only then

we will understand if video gameplay benefits both visual memory and tracking, or if it one

of these components. Finally, we still cannot pin exact functions to precise game mechanics.

Studies, where the result of gameplay experience is observed will not address this issue.

Therefore, implementing eye-tracking procedures, tasks variations, and manipulating with

the mechanics themselves is required for successful identification of game elements which

can potentially benefit cognition.

Since this field of research is relatively new and growing, it is my hope that the study

I presented will help in finding the optimal benefits of video games, which might later be

applied in contexts more ambitious than simple entertainment.


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Appendix A

Table 1.

List of game genres and examples used during the recruitment process.

Genre Examples

First Person Shooter Call of Duty, Counter-Strike, Battlefield

Platform Mario, Donkey Kong, Rayman

Fighting Street Fighter, Tekken, Virtua Fighter

Adventure Zelda, Tomb Raider, Uncharted

Turn-Based Strategy Civilization, Heroes of Might and Magic,

Total War Series

Real Time Strategy StarCraft, Command & Conquer, Age of

Empires

Role-Playing Games Elder Scrolls, Final Fantasy, Fallout

Racing Need for Speed, Gran Turismo, Forza

Puzzle Angry Birds, Portal, Lemmings

Multiplayer Online Battle Arenaa

League of Legends, Dota 2, Warhammer

Online, World of Tanks

Note. a Multiple Online Battle Arena games were treated separately from Real Time Strategies due to

differences in mechanics and types of operations required during gameplay.

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