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Gaming, Flow, Genre and Gender: A Mixed Methods Approach

Gaming, Flow, Genre and Gender:

A Mixed Methods Approach

Megan McDonnell Jamie O’Connor

N00092018 N00091866

Sorcha Doyle Vanessa Lewis

N00092100 N00091166


Abstract

This study aims to investigate whether there will be a difference across participant groups in

time spent playing 3 different genres of video game, where time spent playing is an indication

of the experience of flow. An Apple iPod Touch was used to conduct this study. The chosen

games and genres include PingPong (sports) JailBreaker2 (arcade) and Angry Birds Free

(puzzles). A repeated measures ANOVA was calculated and no significance was observed

(F[2,28] = 2.613, p = .091). However, a Spearman Correlation indicated a positive

relationship (r = .667, p = .007) between average gaming time per week and mean time spent

playing each of the 3 genres of video game. A secondary hypothesis, that gender will have an

effect on video game preference was also investigated. A Pearson Chi-Square was performed

and significance was observed (p = .011, df = 2).

Introduction

Csikszentmihalyi (1990) first presented ‘flow’ and defined it as the holistic sensation that

people feel when they act with total involvement. Hoffmann and Novak (1996) have also

provided a definition of flow in relation to technology, which may arguably be more relevant

to the current study; a basic enjoyment through interacting with computers, which can also be

accompanied by a loss of self-awareness.

Limperos, Schmierbach, Kegerise and Dardis (2011) have researched flow in the context of

gaming, and concluded that flow is often experienced by players when there are high levels

of interaction between the console, controller and player. The study is highly focused on flow

across consoles however, and flow across different genres of games seems to have been

neglected. This study aims to investigate whether there will be a difference across the

participant groups in time spent playing 3 different genres of video game, where time spent

playing is an indication of the experience of flow.

Beylefeld & Struwig, (2007) have studied third level medical students who showed a lack of

interest and enthusiasm when it came to learning about microbiology. In order to tackle this

issue, a state of flow was induced by implementing a board game. After two questionnaires

were administered and the data analysed, it was found that the board game did in fact induce

flow. Again, flow is observed while gaming, but only a single genre of game, i.e. a board

game is studied.

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As previously stated, the purpose of this study is to investigate whether there will be a

difference across the participant groups in time spent playing 3 different genres of video

game, where time spent playing is an indication of the experience of flow. It is expected that

participants will perceive that they have played a particular game for a shorter time than the

actual time spent playing. What is meant by this is that the participant will play beyond the 15

minute guideline, due to being in a state of flow. Csikszentmihalyi, (2002) proposed that

people experiencing flow can be seen as being naturally motivated, unaware of themselves

while a task is being performed and losing the sense of time passing.

The second hypothesis under investigation in the current study is that gender will have an

effect on video game preference. Research conducted by Companion and Sambrook (2008)

has found that significantly more males will choose more violent, combat-orientated games,

as opposed to females, who commonly choose less violent and more nurturing options. Due

to these findings, non-gender-specific genres of game were carefully chosen so as not to

leave game preference to stereotype.

It has been noted (Hayes 2005; Cohen, 2009) that statistically, women are more likely to play

more “puzzle” games, and men more “action” games. This is often misinterpreted as their

subsequent preferred genre of game. It may simply be that women play puzzle games due to

convenience (i.e. puzzle games may be less time-consuming, cheaper and more readily

available) rather than preference. To avoid this misconception, game preference will be self-

reported on this occasion.

This study aims to further previous research in the area and provide conclusive answers to

both hypotheses:

H1: There will be a difference across the participant groups in time spent playing 3 different

genres of video game, where time spent playing is an indication of the experience of flow.

H2: Gender will have an effect on video game preference.

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Method

Design

An observational experiment was carried out in order to investigate whether or not a

difference will be observed across participant groups in time spent playing 3 different genres

of video game, where time spent playing is an indication of flow. Whether or not a

relationship exists between gender and game preference was also investigated.

Participants

Fifteen students (of which there were 8 male, and 7 female, see figure 1 below) from an Irish

third-level institution were selected to participate in this study. Age ranged from 18 to 24

years (M = 20.7 years, SD = 1.9 years), with a median age of 21 years and mode of 22 years.

Figure 1. Gender Distribution

Apparatus

An Apple iPod Touch was used to conduct this study. All three games were downloaded onto

the console free of charge from the Apple "AppStore".The chosen games and genres are as

follows:

1. Ping Pong (sports)

2. Jail Breaker2 (arcade)

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3. Angry Birds Free (puzzle)

A stopwatch was used in order to time participants while playing.

Procedure

Each participant was selected and asked to play a series of three different games on the

chosen console. Participants received briefing form prior to taking part, where aims of the

study and instructions were outlined (see appendix a). A consent form was then administered,

where participants also volunteered information about their average time spent gaming per

week (see appendix b).

Prior to actual game play, each participant watched a demonstration of the game. Each

participant was then timed while playing the three different games and told to stop when they

thought 15 minutes had passed. Data was recorded on a stopwatch (in seconds) and

immediately typed into a spread sheet (see appendix c). No timers or clocks were visible

during testing. Following testing, participants were debriefed accordingly (see appendix d).

Data was analysed using SPSS (see appendix e, f, g for output). A repeated measured

ANOVA was calculated to investigate whether or not a difference will be observed across

participant groups in time spent playing 3 different genres of video game, where time spent

playing is an indication of flow. A Spearman correlation was also calculated in order to

investigate whether or not there was a relationship between participants time spent gaming

per week and their average time spent playing the three different game genres. Finally, a

Pearson chi-square was calculated in order to investigate whether or not gender had an effect

on game preference.

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Results

A repeated measures ANOVA (see table 1 below) was calculated and no significance was

observed (F[2,28] = 2.613, p = .091).

Table 1. Summary ANOVA table

A Spearman Correlation was then carried out using mean scores for each participant across

the 3 genres and the average time spent gaming per week (see figure 2 below), and a

moderately strong positive correlation was evident (r = .667, p = .007).

Figure 2. The relationship between mean time spent playing across the 3 genres and average

time spent gaming per week.

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Source of Variance SS df MS Fobs Fcv

Individual 410063.07 14 29290.22

Occasions 207116.98 2 103558.49 2.61 3.340

Residual 1109505.06 28 39625.18

Total 1726685.11 44


Finally, a Pearson Chi-Square (see figure 3 below) was calculated and significance was again

observed (p = .011, df=2).

Figure 3. Gender and game preference

Discussion

A Repeated Measures ANOVA and a Pearson Chi-Square were used to analyse the data from

this experiment. A non-significant result was observed when the repeated measures ANOVA

was calculated, therefore the H1 was rejected; there is no difference across the participant

groups in time spent playing 3 different genres of video game, where time spent playing is an

indication of the experience of flow.

This is possibly due to the small sample size, differences in environment when testing took

place and also differences among the four researchers and their attitudes/bias. Also, the

sample selected was due to convenience, i.e., all participants were Irish third-level

undergraduate students, from the same institute and with a relatively small age range (18 –

24years).

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Due to a lack of significance in the repeated measures ANOVA, a Spearman Correlation was

calculated in order to investigate whether or not there was a relationship between participants

gaming time per week and their average time spent playing the three different game genres,

and a significant result was observed.

A significant result was also observed when a Pearson Chi-Square was calculated and the H2

was accepted; gender has an effect on video game preference. It is possible a significant

result was observed due to an almost equal number of males to females given the parameters

of the study. Also, the participant’s game preference was self-reported rather than statistically

calculated from a possible confounding variable, such as time, or stereotypical “favourites”

for males and females.

As previously stated, a relatively small sample size was tested in this experiment, resulting in

a lack of generalizability. The minimal variation in demographics such as occupation,

nationality and age in the study also has a negative effect on generalizability.

There are also issues surrounding the use of time spent playing each game as an indication of

flow. It is difficult to know whether or not this is an accurate measurement scale, or if flow is

being measured at all; it is possible that simply enjoyment is being measured. Possibly a state

scale such as The Dispositional Flow State Scale 2 (Jackson & Eklund, 2002) may be more

accurate in measuring flow.

As Hoffman and Novak (1996) and Csikszentmihalyi (2002) have stated, those who

experience flow usually develop a sense of unawareness. It is possible that due to the

instructions given by researchers to participant’s to play each game for their perception of 15

minutes, that participants may have been too focused on the time passing to become

“unaware”, and therefore would be unable to experience flow. Emulations of the study in the

future may benefit from merely stopping participants after 15 minutes of gameplay, and

instructing participants to indicate how much time they have perceived to have passed. This

may minimize the fixation on time, and subsequently encourage a sense of flow.

The researcher’s presence during the observation may also have been a confounding variable.

Many participants reported feeling uncomfortable or uneasy during gameplay. Pressure

seems to have added to this unease, as participants also commented that they felt they had to

perform well in the game in order to take part in the study. A more naturalistic observation

may be advisable for future research.

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Further research may benefit if demographics were varied and sample size increased, and also

if participants were selected due to having an interest in a particular game, on the grounds

that someone is more likely to reach a state of flow playing a game that they already enjoy,

rather than a novel game. Also, upon testing, it may be beneficial to have only one researcher

and a controlled environment for all participants in order to create a sense of continuity.

It also may be beneficial to expand the research across different consoles within the one study

in order to suit a particular game. In line with research by Limperos, Schmierbach, Kegerise

& Dardis (2011), a player is more likely to experience flow during a game if the controller is

interactive; it is possible that a participant playing “Just Dance” on a motion sensor activated

console such as the Nintendo Wii is more likely to become engaged (and therefore experience

flow) in the game than if they were playing the same game using a more traditional “plugin”

controller.

To conclude, this study suggests that different genres of video game will not result in

different levels of flow. However it is interesting to note the relationship between gender and

genre preference in games and also the positive correlation between average time spent

gaming per week, and time spent playing the three different genres of game in this study.

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References

Beylefeld, A. A., & Struwig, M. C. (2007). A gaming approach to learning medical

microbiology: students' experiences of flow. Medical Teacher, 29(9/10), 933-940.

Cohen, A. M. (2009). Closing the Gender Gap in Online Gaming.Futurist, 43(6), 10-11.

Companion, M., & Sambrook, R. (2008). The influence of sex on character attribute

preferences. Cyberpsychology & Behavior, 11(6), 673-674.

Csikszentmihalyi M. (2002). Flow: The Classic Work on How to Achieve Happiness.

London: Rider.

Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York:

Harper and Row.

Hayes, E. (2005). Women, Video Gaming & Learning: Beyond Stereotypes. Techtrends:

Linking Research & Practice To Improve Learning, 49(5), 23-28.

Hoffman, D.L., Novak, T.P., (1996). Marketing in hypermedia computer- mediated

environments: Conceptual foundations. Journal of Marketing 60(1), 50-68.

Jackson,S. A., & Eklund, R. C. (2002). Assessing flow in physical activity: The flow state

scale-2 and dispositional flow scale-2. Journal Sport & Exercise Psychology, 24(2),

133-150.

Limperos, A. M., Schmierbach, M. G., Kegerise, A. D., &Dardis, F. E. (2011). Gaming

Across Different Consoles: Exploring the Influence of Control Scheme on Game-

Player Enjoyment. Cyberpsychology, Behavior& Social Networking,14(6), 345-350.

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Appendices

Appendix a – Briefing form

Briefing Form - Cyberpsychology Experiment

In this experiment you will be required to play 3 Games on an iPod touch. The three games

are as follows:

1. Ping Pong (Genre: Sport)

2. Angry Birds Free (Genre: Puzzle/Action)

3. JailBreaker 2 (Arcade)

All games have are free to download from the Apple "AppStore".

You will be asked to play the three aforementioned games and inform the experimenter when

you think that you have been playing each game for 15 minutes, without the use of any time

measuring apparatus (i.e., no clocks/stopwatches will be visible). Afterward, your favourite

game will be noted.

Please note that any data collected will be used only for the purposes of the study and that

you may withdraw at any time.

If you are willing to take part, please fill in the consent form attached and return to one of the

experimenters.

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Appendix b – Consent form

Consent Form - Cyberpsychology experiment

Age:

Gender:

Occupation:

Taking all consoles (including phone, iPod, computer etc.) into account, how much

time would you spend gaming per week?

< 30 mins 1hr 2-4hrs

4-8hrs 8-12hrs > 12hrs

Signed:

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C


Appendix c – Data Collection

Participant Age GenderTime spent playing PingPong (Medium Difficulty) in secs

Time spent playing Jailbreaker 2 in secs

Time spent playing Angry Birds (Free) in secs

Preferred Game

Time Spent Gaming (per week)

Average Time spent Playing the 3 Genres of Game

1 18 Male 685 578 1110 Jailbreaker 2 8-12hrs 791.002 19 Female 574 777 746 Angry birds 4-8hrs 699.003 23 Male 792 1014 988 Jailbreaker 2 > 12hrs 931.334 20 Male 738 1063 523 Jailbreaker 2 > 12hrs 774.675 21 Male 1002 592 569 PingPong 4-8hrs 721.006 18 Female 422 557 949 Angry Birds 1hr 642.677 21 Female 559 848 695 Angry Birds 4-8hrs 700.678 22 Female 611 508 544 PingPong 1hr 554.339 21 Male 663 554 1343 Angry Birds 8-12hrs 853.3310 24 Female 618 939 734 PingPong 2-4hrs 763.6711 22 Male 567 640 867 Jailbreaker 2 8-12hrs 691.3312 19 Female 623 982 862 Angry Birds 4-8hrs 822.3313 22 Female 502 688 824 Angry Birds 2-4hrs 671.3314 18 Male 804 954 814 Jailbreaker 2 > 12hrs 857.3315 22 Male 765 1009 759 Jailbreaker 2 2-4hrs 844.33

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Appendix d – Debriefing form

Debriefing Form - Cyberpsychology Experiment

The purpose of the experiment was to investigate whether or not people perceive time to be

passing more quickly when gaming due to being in a state of flow.

We will also investigate whether or not gender has an effect on video game genre preference.

If this experiment has caused you any worry, discomfort or anxiety, please do not hesitate to

contact the student services on 01 239 4650 or alternatively, e-mail the student counselor at

[email protected].

If you would like to withdraw from the study at any time, please contact one of the

researchers listed below and your data will be destroyed or returned to you upon request.

Thank you for your participation.

Researchers: Megan McDonnell - [email protected]

Vanessa Lewis - [email protected]

Jamie O'Connor - [email protected]

Sorcha Doyle - [email protected]

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Appendix e – SPSS Output: Repeated Measures ANOVA

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Appendix f – SPSS Output: Pearson Correlation

Correlations

AvgTimeAcrossGenres TimeSpentPlayingPerWeek

Spearman's rho AvgTimeAcrossGenres Correlation Coefficient 1.000 .667**

Sig. (2-tailed) . .007

N 15 15

TimeSpentPlayingPerWeek Correlation Coefficient .667** 1.000

Sig. (2-tailed) .007 .

N 15 15

**. Correlation is significant at the 0.01 level (2-tailed).

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Appendix g - Pearson Chi-Square

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Gender * PreferredGame 15 100.0% 0 .0% 15 100.0%

Chi-Square Tests

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 8.973a 2 .011

Likelihood Ratio 11.502 2 .003

N of Valid Cases 15

Statistics

Gender PreferredGame

N Valid 15 15

Missing 0 0

PreferredGame

Frequency Percent Valid Percent

Cumulative

Percent

Valid PingPong 3 20.0 20.0 20.0

Jailbreaker2 6 40.0 40.0 60.0

AngryBirds 6 40.0 40.0 100.0

Total 15 100.0 100.0

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Gender * PreferredGame Crosstabulation

PingPong Jailbreaker2 AngryBirds

Gender Male 1 6 1 8

Female 2 0 5 7

Total 3 6 6 15

Gender

Frequency Percent Valid Percent

Cumulative

Percent

Valid Male 8 53.3 53.3 53.3

Female 7 46.7 46.7 100.0

Total 15 100.0 100.0


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