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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: 06-28-2022 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC
Script Copyright © 06-28-2022 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)
currentsetsize: the number of letters to recall for the current problem
text.letters.currentItem: the currently presented letter
sentenceproblemcount: counts the number sentences in a given block
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
sentenceaccuracy: percentage of correctly classified sentences within the current block
sentencetotalerrors: counts number of any errors (speed or accuracy) made during sentence classification within the current block
sentenceaccerrors: counts the number of incorrectly classified sentences within the current block
sentencespeederrors: counts the number of times participant ran out of time when reading the sentence within the current block
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).
recalledletters: the number of letters recalled of the current problem
totalcorrectletters: the total number of letters recalled in the correct position.
totalrecalledsets: the number of correctly recalled sets
//trial data (summary at the end of each complete ' test trial' stored under trial 'letter_feedback')
trialCount: trial counter
recalledLetters_perTrial: the number of recalled letters for the current trial only
recalledLettersACC_perTrial: proportion correct recalled letters for the current trial only
correctSentences_perTrial: the number of correctly categorized sentences for the current trial only
sentenceACC_perTrial: proportion correctly categorized sentences for the current trial only
(2) Summary data file: 'automatedrspan_summary*.iqdat' (a separate file for each participant)
inquisit.version: Inquisit version run
computer.platform: the platform the script was run on (win/mac/ios/android)
startDate: date script was run
startTime: time script was started
subjectid: assigned subject id number
groupid: assigned group id number
sessionid: assigned session id number
elapsedTime: time it took to run script (in ms); measured from onset to offset of script
completed: 0 = script was not completed (prematurely aborted);
1 = script was completed (all conditions run)
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).
totalcorrectletters: the total number of letters recalled in the correct position.
sentencetotalerrors: counts number of any errors (speed or accuracy) made during sentence classification during the test block
sentencespeederrors: counts the number of times participant ran out of time when reading the sentence during the test block
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
