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								*Automated 'Reading Span Task (Arspan) *
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Inquisit programming for the ARSPAN: David Nitz (dave@gmillisecond.com) for Millisecond Software, LLC.
last updated:  06-30-2020 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC

Script Copyright © 06-30-2020 Millisecond Software

Copyright for the ARSPAN: Task Copyright (c) 2005 by Dr. Randall Engle
http://psychology.gatech.edu/renglelab/

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BACKGROUND INFO 	
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This script implements the Automated Reading Span Task (ARSPAN), a measure of working memory. 

Working Memory Span Tasks Reference:
CONWAY, A.R.A., KANE, M.J.,BUNTING, M.F., D. ZACH HAMBRICK, D.Z., WILHELM, O., & ENGLE, R.W. (2005).
Working memory span tasks: A methodological review and user’s guide. Psychonomic Bulletin & Review
2005, 12 (5), 769-786.

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TASK DESCRIPTION
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Participants are presented a visual sequences of letters ranging from 3-7 letters (default) that need to be 
recalled at the end. Each letter in the sequence in preceded by a sentence problem ('Andy was stopped by 
the policeman  because he crossed the yellow heaven') followed by the task to decide whether this sentence 
made sense. Letter recall is tested by asking participants to select letters from a provided letter matrix.											  
									
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DURATION 
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the default set-up of the script takes appr. 20 minutes to complete

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DATA FILE INFORMATION 
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The default data stored in the data files are:

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

build:								The specific Inquisit version used (the 'build') that was run
computer.platform:					the platform the script was run on (win/mac/ios/android)
date, time, 						date and time script was run 
subject, group, 					with the current subject/groupnumber
session:							with the current session id

blockcode, blocknum:				the name and number of the current block (built-in Inquisit variable)
trialcode, trialnum: 				the name and number of the currently recorded trial (built-in Inquisit variable)
										Note: trialnum is a built-in Inquisit variable; it counts all trials run; even those
										that do not store data to the data file such as feedback trials. Thus, trialnum 
										may not reflect the number of main trials run per block.
										
											
stimulusitem:						the presented stimuli in order of trial presentation
response:							the participant's response (scancode of response buttons)
correct:							accuracy of response: 1 = correct response; 0 = otherwise
latency: 							the response latency (in ms)

values.currentsetsize: 					the number of letters to recall for the current problem
text.letters.currentitem: 				the currently presented letter
values.sentenceproblemcount: 			counts the number sentences in a given block
values.sentencetimeout: 				duration (in ms) after which the sentence disappears (for test block: calculated for each participant based on average performance during practice)
text.PracSentenceProblem.currentitem: 		the currently presented practice sentence
text.SentenceProblem.currentitem: 			the currently presented test sentence

values.sentenceaccuracy: 				percentage of correctly classified sentences within the current block
values.sentencetotalerrors: 			counts number of any errors (speed or accuracy) made during sentence classification within the current block
values.sentenceaccerrors: 				counts the number of incorrectly classified sentences within the current block
values.sentencespeederrors: 			counts the number of times participant ran out of time when reading the sentence within the current block

values.rspan:						The RSPAN (reading span) score, uses the traditional 'absolute rspan' scoring method. 
									It is the sum of all perfectly recalled sets. 
									So, for example, if an individual recalled correctly 2 letters in a set size of 2,
									3 letters in a set size of 3, and 3 letters in a set size of 4,
									their rspan score would be 5 (2 + 3 + 0).
										
values.recalledletters: 			the number of letters recalled of the current problem										
values.totalcorrectletters: 		the total number of letters recalled in the correct position.
values.totalrecalledsets: 			the number of correctly recalled sets


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

computer.platform:					the platform the script was run on (win/mac/ios/android)
script.startdate:					date script was run
script.starttime:					time script was started
script.subjectid:					assigned subject id number
script.groupid:						assigned group id number
script.sessionid:					assigned session id number
script.elapsedtime:					time it took to run script (in ms); measured from onset to offset of script
script.completed:					0 = script was not completed (prematurely aborted); 
									1 = script was completed (all conditions run)

values.rspan:						The rspan score (reading span), uses the traditional 'absolute rspan' scoring method. 
									It is the sum of all perfectly recalled sets. 
									So, for example, if an individual recalled correctly 2 letters in a set size of 2,
									3 letters in a set size of 3, and 3 letters in a set size of 4,
									their rspan score would be 5 (2 + 3 + 0).
										
values.totalcorrectletters: 		the total number of letters recalled in the correct position.
values.sentencetotalerrors: 		counts number of any errors (speed or accuracy) made during sentence classification during the test block
values.sentencespeederrors: 		counts the number of times participant ran out of time when reading the sentence during the test block
values.sentenceaccerrors: 			counts the number of incorrectly classified sentences during the test block

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EXPERIMENTAL SET-UP 
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NOTE: by entering 'debug' as the subjectid, the script runs in debug mode and presents the correct responses

1 Practice Session (default):
	a) Practice of recalling sequences of letters of set sizes 2-3 in ascending order (4 trials)
	b) Practice of semantic evaluations (15 trials)
	c) Combined practice of recalling sequence of letters (set size 2 only) and semantic evaluation of sentences: 
	each letter is preceded by either a sentence that makes sense or one that does not (3 trials).
	Letter recall is done by picking out letters from a provided letter matrix.

Test Session (default):
	15 Trials (15 = 3 repetitions of 5 set sizes; order of set sizes is randomly determined): 
	Recalling sequences of letters (set size 3-7): each letter is preceded preceded by either a sentence 
	that makes sense or one that does not.
	Letter recall is done by picking out letters from a provided letter matrix.

Scoring:
The program reports five values at the conclusion of the experiment: 
	
The first, RSPAN score, uses the traditional “absolute rspan” scoring method. 
It is the sum of all perfectly recalled sets. 
So, for example, if an individual recalled correctly 2 letters in a set size of 2,
3 letters in a set size of 3, and 3 letters in a set size of 4,
their RSPAN score would be 5 (2 + 3 + 0).

Total number correct is the total number of letters recalled in the correct position
(2 + 3 + 4 = 9 in the above example). 
	
Sentence errors are reported as total number of errors, 
accuracy errors where the subject judged the sentence incorrectly, 
and speed errors in which the subject ran out of time 
in attempting to solve a given sentence problem.

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STIMULI
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Letters: T, L, Q, N, F, H, Y, S, P, K, R, J
sentences: check section Editable Stimuli
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INSTRUCTIONS 
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Instructions can be edited under section Editable Instructions

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EDITABLE CODE 
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check 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:

/ learninginterval:					duration (in ms) of the letter presentation trials

/ startsentencetimeout:				start duration (in ms) of the sentence presentation trials
										Note: the duration is adjusted for the test trials based on practice performance

										
/ debugmode:						0 = testmode => no debug information is presented
									1 = debugmode => debug information is presented on screen