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dc.contributor.authorCarmel, Erran
dc.contributor.authorCrawford, Stephen
dc.contributor.authorChen, Hsinchun
dc.date.accessioned2004-08-22T00:00:01Z
dc.date.available2010-06-18T23:26:20Z
dc.date.issued1992-09en_US
dc.date.submitted2004-08-22en_US
dc.identifier.citationBrowsing in Hypertext: A Cognitive Study 1992-09, 22(5):865-884 IEEE Transactional on Systems, Man, and Cybermeticsen_US
dc.identifier.urihttp://hdl.handle.net/10150/105491
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractWith the growth of hypertext and multimedia applications that support and encourage browsing it is time to take a penetrating look at browsing behavior. Several dimensions of browsing are examined, to find out: first, what is browsing and what cognitive processes are associated with it; second, is there a browsing strategy, and if so, are there any differences between how subject-area experts and novices browse; and finally, how can this knowledge be applied to improve the design of hypertext systems. Two groups of students, subject-area experts and novices, were studied while browsing a Macintosh H y p e r c a r d application on the subject of The Vietnam War. A protocol analysis technique was used to gather and analyze data. Components of the GOMS model were used to describe the goals, operators, methods, and selection rules observed. Three browsing strategies were identified: 1) search-oriented browse, scanning and reviewing information relevant to a fixed task, 2) reviewbrowse, scanning and reviewing interesting information in the presence of transient browse goals that represent changing tasks, and 3) scan-browse, scanning for interesting information (without review). Most subjects primarily used review-browse interspersed with search-oriented browse. Within this strategy, comparisons between subject-area experts and novices revealed differences in tactics: experts browsed in more depth, seldom used referential links, selected different kinds of topics, and viewed information differently than did novices. Based on these findings, suggestions are made to hypertext developers.
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectInformation Seeking Behaviorsen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherBrowsingen_US
dc.titleBrowsing in Hypertext: A Cognitive Studyen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalIEEE Transactional on Systems, Man, and Cybermeticsen_US
refterms.dateFOA2018-07-01T13:28:39Z
html.description.abstractWith the growth of hypertext and multimedia applications that support and encourage browsing it is time to take a penetrating look at browsing behavior. Several dimensions of browsing are examined, to find out: first, what is browsing and what cognitive processes are associated with it; second, is there a browsing strategy, and if so, are there any differences between how subject-area experts and novices browse; and finally, how can this knowledge be applied to improve the design of hypertext systems. Two groups of students, subject-area experts and novices, were studied while browsing a Macintosh H y p e r c a r d application on the subject of The Vietnam War. A protocol analysis technique was used to gather and analyze data. Components of the GOMS model were used to describe the goals, operators, methods, and selection rules observed. Three browsing strategies were identified: 1) search-oriented browse, scanning and reviewing information relevant to a fixed task, 2) reviewbrowse, scanning and reviewing interesting information in the presence of transient browse goals that represent changing tasks, and 3) scan-browse, scanning for interesting information (without review). Most subjects primarily used review-browse interspersed with search-oriented browse. Within this strategy, comparisons between subject-area experts and novices revealed differences in tactics: experts browsed in more depth, seldom used referential links, selected different kinds of topics, and viewed information differently than did novices. Based on these findings, suggestions are made to hypertext developers.


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