becoming a gamer: cognitive effects of real-time strategy gaming brian glass the university of texas...
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![Page 1: Becoming a Gamer: Cognitive Effects of Real-Time Strategy Gaming Brian Glass The University of Texas at Austin, 2011](https://reader034.vdocuments.mx/reader034/viewer/2022051417/56649e6f5503460f94b6c897/html5/thumbnails/1.jpg)
Becoming a Gamer: Cognitive Effects of Real-Time Strategy
Gaming
Brian Glass
The University of Texas at Austin, 2011
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Overview
• Real-time strategy (RTS) gaming
• Why study gaming?
• Blitzy results from 40-hour training with novices
• Novel modeling technique
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Real-Time Strategy Games
Games
Video Games
Action Adventure Simulation Strategy
Most ExistingResearch
e.g., First-personshooter
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Real-Time Strategy Games
Games
Video Games
Action Adventure Simulation Strategy
Real-TimeStrategy
• God-like view / command• Rapid, fluid action• Small window into larger world (literal spotlight)• Resource management• War themes, many “fronts”
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Why video games?
1. Popular
2. Lead to generalized learning
3. We can control them
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Why video games?
Popular
• 72% of Americans reported playing video games in 2008
• Females are fastest growing demographic
• In 2010, 40% of gamers were female
• Of all gamers, 33% were adult women > 20% who were males under 17
• Striatal dopamine during video game was on par with methamphetamine injection (Koepp, et al., 1998)
• DSM-V committee found insufficient evidence for video game addiction (as of 2007)
Entertainment Software Association, 2010 Essential Facts Guide
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Why video games?
Lead to generalized learning
• Transfer to new tasks and new contexts
• Prior work demonstrates that long-term training in attention-based tasks can lead to performance enhancement
• Most training procedures tap specific skill specific system
Green & Bavelier (2008)
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Existing Research: Action Games
Players vs. Non-Players
• Self-report as avid action gamers (5+ hours per week)• Tested on various speeded-choice RT tasks
Dye, Green, & Bavelier (2009)
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Existing Research: Action Games
Training Non-Players
• Pretest – 50 hours of play over 9 weeks – Posttest
Dye, Green, & Bavelier (2009)
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Existing Research: Action Games
Training Non-Players
• Multiple-object tracking task
• Useful field of view task
• Attentional blink (10 Hz)
• Crowding tasks (identification among tightly packed distractors)
• Mental rotation
• Piloting training (flight simulator)
Feng, Spence & Pratt (2007)
Dye, Green, & Bavelier (2009)
Myers, et al. (2000)
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StarCraft: “Gold Standard” RTS
Video
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Attention and StarCraft
Does RTS gameplay have more of an attentional component?
Strains on attention:
Multi-agent system
Resource management
Multiple “fronts”
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Attention and StarCraft
• Alerting• Sensitivity to incoming stimuli
• Orienting• Selection of information from sensory input
• Executive• Monitoring and resolving conflicts
StarCraft
Sensitivity to enemy units which may appear
on the screen
Selecting which game elements to attend to
Determining priority of which enemy units to
attack
(Posner & Rothbart, 2007)
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Training Novices
3. We can control them
1. Control Game (The Sims)
2. Low-Attention Starcraft
3. High-Attention Starcraft
Used in: Dye, Green, & Bavelier, 2009
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Training Novices
Low-Attention(One Base)
High-Attention(Two Bases)
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Training Novices
Intake / Screening Pretest 20 Hours of
GamingMidtest 20 Hours of
GamingPosttest
1. Control (The Sims)2. Low-Attention StarCraft3. High-Attention StarCraft
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Training Novices
Battery of cognitive / perceptual tasks – Expect Change?
Stroop – Directed attention
Task Switching
Multitask Switching
Attentional Network Test (ANT)
Visual Search
Filtering
Digit Span – Working Memory
Operating Span (Ospan)
Balloon Analogue Risk Taking Task
Multimedia Multitasking Index
Yes
Maybe
No
Pretest only, possible covariate
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Training Novices
Fan, McCandliss, Fossella, Flombaum, Posner (2005)
Attentional Network Test (ANT)
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Attentional Network Test (ANT)
ANT, Time3-Time1
0.00
0.05
0.10
0.15
0.20
0.25
0.30
SC-Low SC-High SC Sims
Acc
urac
y
ANT, Time3-Time1
-200.0
-150.0
-100.0
-50.0
0.0
50.0
100.0
SC-Low SC-High SC SimsR
T
All groups faster, but StarCraft-High group more accurate
Training Novices
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Multitask Switching
Switching between locations, remembering states
0 0
Odd?4
7
Odd?2
3
Odd? 6
1
8
Training Novices
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Multitask Switching
Switching between locations, remembering states
Multitask Switching, Time3-Time1
-0.4-0.3-0.2-0.10.00.10.20.30.4
SC-Low SC-High SC Sims
AC
C -
Sw
itch
Tri
als
Multitask Switching, Time3-Time1
-1200.0-1000.0
-800.0-600.0-400.0-200.0
0.0200.0400.0
SC-Low
SC-High
SC Sims
RT
- S
witc
h T
ria
ls *
Training Novices
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Task Switching
Ophir, Nass, Wagner (2009)
43
51
Even / Odd?
pu
jo
Vowel / Cons.
E/O V/CE/O E/O V/C E/O E/O V/C V/C V/C V/C E/O V/C
SwitchSwitch Switch Switch Switch
Training Novices
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Task Switching
Ophir, Nass, Wagner (2009)
E/O V/CE/O E/O V/C
Switch
Task Switching, Time3-Time1
-0.06
-0.04
-0.02
0.00
0.02
0.04
0.06
0.08
0.10
SC-Low SC-High
SC Sims
Acc
ura
cy
Switches Non-Switches
Task Switching, Time3-Time1
-500-450-400-350-300-250-200-150-100
-500
SC-Low SC-High
SC Sims
RT
Switches Non-Switches
Training Novices
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Filtering
Ophir, Nass, Wagner (2009)
Information Filtering, Time3-Time1
-0.150
-0.100
-0.050
0.000
0.050
0.100
0.150
SC-Low
SC-High
SC Sims
Acc
ura
cy
Information Filtering, Time3-Time1
-120
-100
-80
-60
-40
-20
0
20
40
SC-Low SC-High
SC Sims
Re
act
ion
Tim
e
Training Novices
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Balloon Analog Risk Taking (BART)
• Sensation seeking• Impulsivity• Constraint deficiencies• Self-reported:
• Addictive Risk Bx• Health Risk Bx• Safety Risk Bx
Lejuez, et al. 2002
Training Novices
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Balloon Analog Risk Taking (BART)
Lejuez, et al. 2002
BART, Time2-Time1
-0.04-0.020.000.020.040.060.080.100.12
SC-Low SC-High
SC Sims
Acc
ep
t Le
ng
th
Ris
kier
Training Novices
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Battery of cognitive / perceptual tasks
Sims SC-Lo SC-Hi
Stroop – Directed attention + +
Task Switching* -A / -RT +A / -RT +A / -RT
Multitask Switching* -RT
Attentional Network Test (ANT)* -RT -RT +A / -RT
Visual Search – Target/Distractors H<E
-RT
H<E
-RT
H~E
-RT
Filtering -RT -A / -RT +A / -RT
Digit Span – Working Memory* + +
Operating Span (Ospan)* - +
Balloon Analogue Risk Taking* +Risk ++Risk Risk
2
3
*NHST p<0.05
Results Summary
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StarCraft Measures
• Games won
Duration
Final difficulty levels
• Feature Modeling
70+ features are being captured during game play
Continuing Analyses
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Feature Modeling with RADAR
Feature Recording for Each UnitID unit ID
unittype type of unit
isselected is selected by the player
isabuilding is a building
isidle idle = 1, not idle = 0, being built = 2, newly built = 3
isloaded loaded into a transporter
disttocc distance to nearest command center
hasgas scv carrying gas
hasminerals scv carrying minerals
isrepairinganother is repairing another unit
tickssincelastunderattack milliseconds since last under attack
prophealth proportion health remaining
killcount other units killed
velocity movement velocity
healedbymedic being healed by a medic
blindedbymedic being blinded by a medic
targetDist distance to target
islifted is lifted (building)
cntfriendly friendly units in view
cntenemy enemy units in view
distfriendly distance to nearest friendly unit
distenemy distance to nearest enemy unit
cntfriendlybldg # friendly buildings in view
cntenemybldg # enemy buildings in view
distfriendlybldg distance to closest friendly building
distenemybldg distance to closest enemy building
cntfriendlyunderattack # friendly units under attack in view
cntenemyunderattack # enemy units under attack in view
distfriendlyunderattack distance to closest friendly unit under attack
distenemyunderattack distance to closest enemy unit under attack
cntfriendlybldgunderattack # friendly buildings under attack in view
cntenemybldgunderattack # enemy buildings under attack
distfriendlybldgunderattack distance to clsoest friendly building under attack
distenemybldgunderattack distance to closest enemy building under attack
cntgas # of geysers in view
cntmineral # of mineral patches in view
distgas distance to closest gas
distmineral distance to closest minerals
propvisible proportion of possible tiles in view which are unobstructed and viewable
propbuildable proportion of possible tiles in view on which buildings can be built
ispatrolling is patrolling
istraining is being trained
remaintraintime remaining time to be trained
isresearching is a building which is researching
remainresearchtime remaining time to research
screenMoved_int has the screen moved since last recording
mmDragged_int has the minimap been dragged since last recording
sX screen x position on map
sY screen y position on map
x x position
y y position
critterinview critter in view
angle angle of rotation
xdivy x position divided by y position
ydivx y position divided by x position
mousedist distance from the mouse cursor
distscreentop distance from unit to top of screen
distscreenleft distance from unit to left of screen
distscreencorner distance from unit to screen corner
cntfriendlyunderattackodd # friendly units under attack is odd
cntenemyunderattackodd # enemy units under attack is odd
cntfriendlybldgunderattackodd # friendly buildings under attack is odd
cntenemybldgunderattackodd # enemy buildings under attack is odd
xodd x position is odd
yodd y position is odd
angleodd angle of rotation is odd
xgreatery x position is greater than y position
cntfriendlyunderattackmult3 count of friendly units under attack is multiple of 3
cntenemyunderattackmult3 count of enemy units under attack is multiple of 3
cntfriendlybldgunderattackmult3 # friendly buildings under attack is multiple of 3
cntenemybldgunderattackmult3 # enemy buildings under attack is multiple of 3
xmult3 x position is a multiple of 3
ymult3 y position is a multiple of 3
anglemult3 angle of rotation is a multiple of 3
random1 random number
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Feature Modeling with RADAR
Feature Recording for Each Unitunittype type of unitisselected is selected by the playerisabuilding is a buildingisidle idle = 1, not idle = 0, being built = 2, newly built = 3isloaded loaded into a transporterdisttocc distance to nearest command centerhasgas scv carrying gashasminerals scv carrying mineralsisrepairinganother is repairing another unittickssincelastunderattack milliseconds since last under attackprophealth proportion health remainingvelocity movement velocityhealedbymedic being healed by a medicdistenemy distance to nearest enemy unitcntfriendlybldg # friendly buildings in viewcntenemybldg # enemy buildings in viewdistfriendlybldg distance to closest friendly buildingcntenemybldgunderattack # enemy buildings under attackdistfriendlybldgunderattack distance to clsoest friendly building under attackcntgas # of geysers in viewcntmineral # of mineral patches in viewpropvisible proportion of possible tiles in view which are unobstructed and viewableyodd y position is oddxgreatery x position is greater than y positioncntfriendlyunderattackmult3 count of friendly units under attack is multiple of 3cntenemyunderattackmult3 count of enemy units under attack is multiple of 3ymult3 y position is a multiple of 3anglemult3 angle of rotation is a multiple of 3
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Feature Modeling with RADAR
Response Adaptive Display Anticipates Request (RADAR)
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Feature Modeling with RADAR
• StarCraft – Correctly predicts how likely a unit is to be selected – 75% of the time.
Compare Novice vs. Expert
Cross-validate over games to measure consistency of game play
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Summary
• RTS gaming represents unique opportunity for long-term cognitive training
• Train 36 novices over three conditions• High-Attention RTS• Low-Attention RTS• Control (The Sims)
• StarCraft vs. Control (Sims)• When accuracy is high, RT improvement• When accuracy is moderate, accuracy + RT improvement• However, Control faster at location switching task
•StarCraft-High vs. StarCraft-Low• StarCraft-Low group is riskier on time 3• StarCraft-High group > SC-Low at information filtering
• Game factors such as success, and some offerings from RADAR to be taken into account
• 2-months follow up
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Thank You!
Todd MaddoxBrad Love
Marc TomlinsonDevon GreerRusty Gomez
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Attention and StarCraft
• Alerting• Sensitivity to incoming stimuli• Fronto-Parietal• Norepinephrine system, locus coeruleus
• Orienting• Selection of information from sensory input• Cholinergic system, basal forebrain• Reduce neural activity and RT for invalid cues
• Executive• Monitoring and resolving conflicts• Usual suspects: ACC and LatPFC• Targets of mesocortical dopamine system
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Training Novices
Operating Span (OSpan)
Ospan, Time3-Time1
-20
-15
-10
-5
0
5
10
SC-Low SC-High SC Sims
O-S
pa
n S
core
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Task Switching, Time2-Time1
-0.06
-0.04
-0.02
0.00
0.02
0.04
0.06
0.08
0.10
SC-Low SC-High
SC Sims
Acc
ura
cy
Switches Non-Switches
Task Switching, Time2-Time1
-300-250-200-150-100
-500
50100150200
SC-Low SC-High
SC Sims
RT
Switches Non-Switches
Task Switching, Time2-Time1
-300
-250
-200
-150
-100
-50
0
50
100
150
200
SC-Low SC-High
SC Sims
RT
- S
witc
h C
ost
Task Switching, Time2-Time1
-0.060
-0.040
-0.020
0.000
0.020
0.040
0.060
0.080
0.100
SC-Low
SC-High
SC Sims
AC
C -
Sw
itch
Co
st
Task Switching
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Multitask Switching, Time2-Time1
-600.0
-400.0
-200.0
0.0
200.0
400.0
600.0
SC-Low
SC-High
SC Sims
RT
- C
ost
Multitask Switching, Time2-Time1
-0.4-0.3-0.2-0.10.00.10.20.30.4
SC-Low SC-High SC Sims
AC
C -
Co
st
Multitask Switching