New Metrics & Measurement

for information search dynamics in decision making

Presenter: Xiaolei ZhouAdvisor: Dr. Joseph G. Johnson

Department of Psychology Miami University

JDM Lab: tinyurl.com/CogLabMiami

Decision Making Processes•How could we discover the mental

processes while we making choices?•Outcome?•Reaction Time (RT)?•Etc.

•We need to be more accurate!!!•Track online information searching

processes

Tracking Online Decision Processes

•Eye tracking

Typical Analysis of Decision Processes

•Exclusive Focus on summary statistics•Total number of acquisitions•Time per acquisition

One Step Further•New application of techniques deployed in

other fields to better utilize such rich data•Comparing Similarities search strings

across trials, conditions, theoretical predictions, etc

String Edit Distance (SED)

Experimental Paradigm•Preferential Choice Task• Select option that is most attractive

• 3 options x 4 attributesStars Budget Rating Original

Movie A + - - +

Movie B - + + +

Movie C + - - -

Participants make a decision among several options (Rows), described by several attributes (Columns). For example, they must predict which movie has the highest receipts based on several binary features (above). The values of each cell in the information table are occluded until an eye fixation occurs on the cell A B C D B C D E F G H C B A …A B C D B C D E F G H C B A …

Stars Budget Rating Original

Movie A -

Movie B

Movie C

Optimize Eye-tracking Technique

•Minimum “cost” to align two strings using Minimum “cost” to align two strings using basic operations:basic operations:

•SubstitutingSubstituting one element for another one element for another

•Inserting “gap” Inserting “gap” in one sequencein one sequence

Dynamic programming methodsDynamic programming methods11 used to determine optimal used to determine optimal solutionsolution22 based on costs associated with each operation based on costs associated with each operation

1Needleman-Wunsch algorithm (local optimal alignment of sub-sequences)

2Back-Tracing Dynamic Programming

B A BB A B D C D B C DD C D B C D A B AA B A B C AB C A BBB D A C D BB D A C D B D C AD C A B C BB C B A BA BB B A -A - D C D B D C D B C DC D A B A B AA B - A B B - A B

String Edit Distance (SED)

Comparing Similarities: •How do experimental conditions affect the search process?•Time Pressure Experiment (6s,

18s, 30s)B A B D C DB A B D C D B C DB C D A B AA B A B C AB C A B …B …B D A C D BB D A C D B D C AD C A B C BB C B A B …A B …

A (30s)A (30s)B B

(18s)(18s) D C B A B C AD C B A B C A B C BB C B A B …A B …C (6s)C (6s)

Summary Statistics (Typical Measurements)

Summary Statistics (Cont’)

String Edit Distance Analysis★ ★

Summing up• Development of sophisticated metrics for

rich process data sets• Enhances our ability to address complex

questions in a comprehensive way• Testing behavioral changes across

conditions• More precise testing of competing

models

Thank you!Special thanks to my

instructor : Dr. Joseph G. Johnson

And my lovely labmates:Ruohui Zhang & Mary Frame