Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/12991
DC FieldValueLanguage
dc.contributor.authorNisiforou, Efi-
dc.contributor.authorLaghos, Andrew-
dc.date.accessioned2019-01-15T06:33:34Z-
dc.date.available2019-01-15T06:33:34Z-
dc.date.issued2016-06-01-
dc.identifier.citationInteracting with Computers, 2016, vol. 28, no. 4, pp. 407–420en_US
dc.identifier.issn18737951-
dc.description.abstractThe notion that users' characteristics such as the cognitive ability affect their visual information processing is continuously increasing. This eye tracking user study investigated the association between adults' ($N=54$) cognitive style and eye movement (EM) patterns while interacting with a set of visual tasks. Users' cognitive type was measured with the use of the Hidden Figures Test (HFT), which classifies them into field dependent (FD), field neutral (FN) and field independent (FI) individuals. Overall, the psychometric measures and the eye tracking-derived data were statistically examined revealing significant differences and large effect sizes among the two variables tested. Particularly, the findings demonstrated that the field dependence group exemplifies a more disoriented and disorganized EM activity. Hence, greater numbers of fixations and saccades are generated, contrary to the FN or FI users'. This research study adds further to the evidence and theory base of human-computer interaction for applications in the user-centred design by identifying how users' differences in cognitive style can be manifested in eye gaze patterns.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofInteracting with Computersen_US
dc.rights© Elsevieren_US
dc.subjectHuman–computer interactionen_US
dc.subjectUser cognitive typeen_US
dc.subjectField dependence-independenceen_US
dc.subjectEye trackingen_US
dc.subjectHidden figures tesen_US
dc.subjectEmbedded shapesen_US
dc.subjectEye movement patternsen_US
dc.titleField Dependence-Independence and Eye Movement Patterns: Investigating Users' Differences Through an Eye Tracking Studyen_US
dc.typeArticleen_US
dc.doihttps://doi.org/10.1093/iwc/iwv015en_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1093/iwc/iwv015en_US
dc.identifier.scopus2-s2.0-84976503712-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84976503712-
dc.relation.issue4en_US
dc.relation.volume28en_US
cut.common.academicyear2015-2016en_US
dc.identifier.spage407en_US
dc.identifier.epage420en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextNo Fulltext-
crisitem.journal.journalissn1873-7951-
crisitem.journal.publisherOxford University Press-
crisitem.author.deptDepartment of Multimedia and Graphic Arts-
crisitem.author.deptDepartment of Multimedia and Graphic Arts-
crisitem.author.facultyFaculty of Fine and Applied Arts-
crisitem.author.facultyFaculty of Fine and Applied Arts-
crisitem.author.orcid0000-0001-9217-3491-
crisitem.author.parentorgFaculty of Fine and Applied Arts-
crisitem.author.parentorgFaculty of Fine and Applied Arts-
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