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last updated:  11-28-2018 by K. Borchert ( for Millisecond Software, LLC
Scipt Copyright ©  11-28-2018 Millisecond Software



The script implements the 'Bean Fest Paradigm' developed by Fazio et al (2004) to study attitude formation
and subsequent generalization.


Fazio, R. H., Eiser, J. R., & Shook, N. J. (2004). Attitude formation through exploration: 
Valence asymmetries. Journal of Personality and Social Psychology, 87, 293-311.

Participants are presented beans of various oval shapes with various speckles and they have to learn which 
of these beans to choose to gain points and which of these beans to reject to avoid the loss of points.
Participants either accept or reject a bean using 2 keys on the keyboard.
A test phase presents familiar and novel beans.

This script uses points and full feedback. 
Participants start with 100 points and gain or lose 10 points with each bean. 
There is no time penalty. Each of these parameters can be easily modified. 

The default data stored in the data files are:

(1) Raw data file: 'Beanfest_raw*.iqdat' (a separate file for each participant)

build:							Inquisit build
computer.platform:				the platform the script was run on
date, time, subject, group:		date and time script was run with the current subject/group number 
blockcode, blocknum:			the name and number of the current block
trialcode, trialnum: 			the name and number of the currently recorded trial
									(!!!Note: not all trials that are run might record data)
response:						the participant's response, scancode of response button
latency: 						the response latency (in ms)
/ totalpoints:					stores the total points
/ currentbean:					stores the current bean image
/ currentbeanvalue:				assigns the current beanvalue according to group

(2) Summary data file: 'Beanfest_summary*.iqdat' (a separate file for each participant)

script.startdate:				date script was run
script.starttime:				time script was started
script.subjectid:				subject id number
script.groupid:					group id number
script.elapsedtime:				time it took to run script (in ms)
computer.platform:				the platform the script was run on
/completed:						0 = script was not completed (prematurely aborted); 1 = script was completed (all conditions run)
/ totalpoints:					stores the total points earned

EXPERIMENTAL SET-UP (in this script)

Beans vary along 2 dimensions:
1. circular -> oval (in 10 steps)
2. number of speckles: 1-10
=> 100 possible combinations
=> 6 regions with 5-7 beans (36 beans total) are selected for the Learning Phase (Fazio et al, 2004, p.295).
=> 3 regions add points; 3 regions subtract points (if chosen)
!!!NOTE: by using groupids '1' and '2', the regions are counterbalanced

(I) Learning Phase: 
A. Practice: 6 trials; one bean randomly selected from each of the 6 regions
B. 1. Learningblock: 
The first 12 trials present 2 beans from each region.
The remaining 24 trials present the remaining beans in a random order
C. 2. Learningblock: all 36 beans presented in random order (block is repeated as many times as specified by parameters.maxlearningtrials)

(II) Test Phase (in this script):
100 trials: tests all learning beans and new beans (=remaining beans)

100 beans that vary along the dimensions circular shape and number of speckles (see under EDITABLE STIMULI)


check under EDITABLE CODE below for (relatively) easily editable parameters, stimuli, instructions etc. 
Keep in mind that you can use this script as a template and therefore always "mess" with the entire code to further customize your experiment.

The parameters you can change are:
- startingpoints: the number of points the participant starts with at the beginning of the game
- maxpoints: the maximum number of points that a participant can have
- timeout: the number of milliseconds the participant is given to respond to a bean
- positivebeanvalue: the number of points gained by eating a good bean
- negativebeanvalue: the number of points lossed by eating a bad bean
- timevalue: the number of points lost on each trial as a function of time
- feedbackduration: length of time in ms that feedback remains on the screen
- fullfeedback: whether to display hypothetical effect of rejected beans 

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