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dc.contributor.authorSlowinski, P
dc.contributor.authorGrindley, B
dc.contributor.authorMuncie, H
dc.contributor.authorHarris, D
dc.contributor.authorVine, S
dc.contributor.authorWilson, M
dc.date.accessioned2023-01-04T12:24:52Z
dc.date.issued2023-01-04
dc.date.updated2022-06-19T16:51:58Z
dc.description.abstractThis is the dataset used for the Slowinski et al. (2022) article "Assessment of cognitive biases in augmented reality: Beyond eye tracking" published in the Journal of Eye Movement Research.en_GB
dc.description.sponsorshipDefence Science and Technology Laboratory (DSTL)en_GB
dc.description.sponsorshipWellcome Trusten_GB
dc.format.csv
dc.identifier.doi10.24378/exe.4064
dc.identifier.grantnumberDSTLX1000133918en_GB
dc.identifier.grantnumber204909/Z/16/Zen_GB
dc.identifier.urihttp://hdl.handle.net/10871/132142
dc.identifierORCID: 0000-0002-6612-9902 (Slowinski, Piotr)
dc.language.isoenen_GB
dc.publisherUniversity of Exeteren_GB
dc.relation.urlhttps://osf.io/kcd83/en_GB
dc.relation.urlhttp://hdl.handle.net/10871/132140en_GB
dc.rightsCC BY 4.0en_GB
dc.subjecteye movementen_GB
dc.subjecthand movementen_GB
dc.subjecthead movementen_GB
dc.subjectearth mover’s distanceen_GB
dc.subjectcorrelation matrixen_GB
dc.subjecteye trackingen_GB
dc.subjectcognitive biasen_GB
dc.subjectaugmented realityen_GB
dc.titleAssessment of cognitive biases in Augmented Reality: Beyond eye tracking (dataset)en_GB
dc.typeDataseten_GB
dc.date.available2023-01-04T12:24:52Z
dc.descriptionData collected for a project: "Augmented reality as a tool for cognitive debiasing: A pilot study to identify behavioural markers that indicate cognitive biases." funded by Phase 1, Defence and Security Accelerator (Behavioural Analytics) Contract Number DSTLX1000133918. Include are data from 40 participants. Data files are in the text format. Files contain recordings of hand, head and eye movements recorded during an odd-one-out task. An additional file contains short comprehensive assessment of rational thinking (CART) scores. xx_OOO_hand.csv - each file with hand movements has the following columns: % timestamp - seconds and fractions of seconds % year, % month, % day, % hour, % minute, % second, % 1st detected hand marker: 1001 - right, 1002 - left % x - x position in the leapmotion frame % y - y position in the leapmotion frame % z - z position in the leapmotion frame % 2nd detected hand marker: 1001 - right, 1002 - left % x - x position in the leapmotion frame % y - y position in the leapmotion frame % z - z position in the leapmotion frame xx_OOO_head.csv - each file with head rotations has the following columns: % timestamp - seconds and fractions of seconds % year, % month, % day, % hour, % minute, % second, % x - rotation % y - rotation % z - rotation xx_OOO_gaze.csv - each file with gaze positions has the following columns extracted from the pupil-labs export file: % timestamp - posixtime with 'TimeZone' 'Europe/London' % confidence - computed confidence between 0 (not confident) 1 (confident) % x - x position in the world image frame in normalized coordinates % y - y position in the world image frame in normalized coordinates xx_OOO_response.csv - each file the odd-one-out task responses has the following columns: % year, % month, % day, % hour, % minute, % second, % task number, % 2nd response, % 1st response xx_OOO_walltime.csv - each file contains: % timestamp - time saved as matlab serial date short_CART_score.csv - file with the short CART score for each participant (in order). The file has following columns: % duration in seconds % indicator that a participant completed CART % short CART score Matlab code used to analyse the data can be accessed at: https://osf.io/kcd83/en_GB
dc.descriptionThe article associated with this dataset is available in ORE at: http://hdl.handle.net/10871/132140en_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_GB
rioxxterms.versionNAen_GB
rioxxterms.licenseref.startdate2023-01-04
rioxxterms.typeOtheren_GB
refterms.dateFOA2023-01-04T12:24:57Z


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