Cognitive Ability Effects on Effort in Web Search & Navigation by Gwizdka
1. Cognitive Ability Effects on Effort
in Web Search and Navigation
Jacek Gwizdka
Department of Library and Information Science
Rutgers University
New Brunswick, New Jersey, USA
Text & Discourse Annual Meeting, University of Poitiers, 12.07.2011
CONTACT:
www.jsg.tel
2. Background
• People are assumed to strive to minimize effort – the
principle of least effort (Zipf, 1949)
• In more demanding situations people are expected to
make decisions based on satisficing (Simon 1956; Rational Analysis
framework: Anderson, 1990)
• Bounded rationality and satisficing were found to explain
behaviour on low-level and high-level info search tasks (Fu &
Gray, 2006; Gray & Fu, 2001; Mansourian & Ford, 2007)
• For increased difficulty one could expect that a user would
perform less actions and stop sooner
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3. Experiment
• 37 participants
– Working memory assessed using memory span task (Francis & Neath 2003)
• Within subject design with 2 factors: task and user interface
• Tasks
– everyday information search (e.g., travel, shopping) at two levels of
task complexity
– Four task rotations for each of two user interfaces
Information Information
Fact finding Fact finding
gathering gathering
Information Information
Fact finding Fact finding
gathering gathering
Information Information
Fact finding Fact finding
gathering gathering
Information Information
Fact finding Fact finding
gathering gathering 3
4. User Interfaces: Result List vs. Overview Tag-Cloud
1 UI. List
Start
View
New Tag Search Delete Tag
Results
Click Click
Result “Back”
URL button Click “Done” &
enter answer
View
one result
page End
2 UI. List +
Overview Tag Cloud 4
5. Research Questions
• How does performance and effort change in more
demanding situations?
– Task and user interface effects;
– Individual differences - cognitive ability effects.
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6. Measures
• Task completion time
• Cognitive effort:
– search and navigation decisions expressed as user actions:
selection of search terms – number of queries,
selection of documents to view
– reading effort: scanning vs. reading; length of reading sequences;
length of reading fixations (based on reading model)
• Performance: task outcome = relevance * completeness
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7. Introducing Reading Model
• Scanning fixations provide some semantic information
– limited to foveal visual field (1° visual acuity) (Rayner & Fischer, 1996)
• Reading fixation sequences provide more information than
isolated “scanning” fixations
– information is gained from the larger parafoveal region (5° beyond foveal focus;
asymmetrical, in dir of reading) (Rayner et al., 2003)
– some types of semantic information is available only through reading
sequences
• We implemented the E-Z Reader reading model (Reichle et al., 2006)
– Lexical fixations duration >113 ms (Reingold & Rayner, 2006)
– Each lexical fixation is classified to Scanning or Reading (S,R)
– These sequences used to create a two-state model
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10. Task User Behaviour & Reading Model Diffs
• Task outcome: no sig differences between conditions
• Task: more complex tasks required more effort
– More actions (7.8 vs. 4.5) and longer time (255 vs. 195 s)
– Longer max reading fixation length and more reading fixation regressions
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11. UI User Behaviour & Reading Model Diffs
• Overview+List User Interface required less effort
– Users were faster (191s vs. 261s in List UI)
– Less reading effort:
• Scanning more likely (transitions: SS RS: higher; SR lower)
• Scan path length of reading sequences shorter
• Less and shorter mean fixations per page visited
List Overview + List
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13. Individual Differences – Least Effort?
•Higher cognitive ability searchers were faster in Overview UI
and on simple tasks (while they entered same number of queries)
•Higher ability searchers did more in more demanding situations
– but higher search effort did not seem to improve task outcomes
For task complexity factor and working memory (WM):
F(144,1)=4.2; p=.042 F(144,1)=3.1; p=.08
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14. Task and Working Memory – Eye-tracking Data
• Number and duration of reading sequences differs between
task complexity levels
– (borderline: 0.05<p<0.1)
• For high WM searchers:
– for complex tasks more reading
– for simple tasks less reading
• For low WM no such difference!
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15. Summary & Conclusions
• UI effect on effort: Overview+List UI
• Task complexity effect reflected in user actions and in some
eye-tracking measures
• Effects of cognitive abilities (WM) on effort :
– low WM – in more complex tasks less documents read
satisficing
– high WM – more effort on complex tasks than needed
opportunistic discovery of information?
(Erdelez, S., 1997)
– “violation” of the least effort principle not fully explained yet
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16. Thank you! Questions?
Jacek Gwizdka contact: http://jsg.tel
PoODLE Project: Personalization of the Digital Library Experience
supported by US Institute of Museum and Library Studies (IMLS)
grant LG-06-07-0105-07
http://bit.ly/poodle_project
18. Eye-gaze patterns
• Eye-tracking research have
frequently analyzed eye-gaze
position aggregates ('hot spots’)
– spatiotemporal-intensity – heat maps
– also sequential – scan paths
• Higher-order patterns:
– reading models
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19. Reading Eye Patterns
• Reading and scanning have easily distinguished patterns of
fixations and saccades. (Rayner & Fischer, 1996)
• Lexical Processing of Words
– Reading research has established word availability is a function of
fixation duration:
– Orthographic recognition: 40-50 ms
• time to move data from eyes to mind
– Phonological recognition: 55-70ms
– Lexical availability (typical): 113 ms – 150ms (Rayner, 1998)
• Unfamiliar or complex meanings require longer processing
– Eyes do not saccade until the word has been processed
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20. Scan Fixations vs. Reading Fixations
• Scanning fixations provide some semantic information,
limited to foveal (1° visual acuity) visual field (Rayner & Fischer,
1996)
• Fixations in a reading sequence provide more information
than isolated “scanning” fixations:
– information is gained from the larger parafoveal (5° beyond foveal
focus) region (Rayner et al., 2003) (asymmetrical, in dir of reading)
– richer semantic structure available from text compositions
(sentences, paragraphs, etc.)
• Some of the types of semantic information available only
through reading sequences may be crucial to satisfy task
requirements.
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21. Reading Models
• We implemented the E-Z Reader reading model (Reichle et al.,
2006)
– Inputs: (eye fixation location, duration)
– Fixation duration >113 ms – threshold for lexical processing (Reingold
& Rayner, 2006)
– The algorithm distinguishes reading fixation sequences from isolated
fixations, called 'scanning' fixations
– Each lexical fixation is classified to (S,R) (Scan, Reading)
– These sequences used to create a state model
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22. Reading Model – States and Characteristics
• Two states: transition probabilities
• Number of lexical fixations and duration
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24. Current Project:
Can We Implicitly Detect Relevance Decisions?
• Implicit characterization of Information Search Process
using physiological devices
• Can we detect when searchers make information
relevance decisions? Emotiv EPOC
wireless EEG headset
EEG
• Start with pupillometry pupil
animation Eye tracking
– info relevance (Oliveria, Russell, Aula, 2009)
– low-level decision timing (Einhäuser, et al. 2010)
• Also look at EEG, GSR Tobii T-60
Funded by Google Research Award eye-tracker
And by IMLS Career award
GSR
Notes de l'éditeur
decision incorporates assessment of the effort needed to continue searching to obtain a better (or more) information vis-à-vis the expected utility of that information
Some insight offered by examining differences in reading models for high vs. low WM people
Eye tracking work on reading behavior in information search have mostly analyzed eye gaze position aggregates ('hot spots').This does not address the fixation sub-sequences that are true reading behavior.