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dc.contributor.authorWu, Jiun-Yuen_US
dc.contributor.authorXie, Chenen_US
dc.date.accessioned2019-04-02T05:58:35Z-
dc.date.available2019-04-02T05:58:35Z-
dc.date.issued2018-11-01en_US
dc.identifier.issn0747-5632en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.chb.2018.07.008en_US
dc.identifier.urihttp://hdl.handle.net/11536/148088-
dc.description.abstractDigital distraction has become a chronic behavior problem for university students that interferes with their attention and learning within personalized learning environment. Applying a randomized control block trial with a counterbalanced experimental design, we investigated the effect of note-taking strategies and time pressure on students' task-irrelevant browsing behaviors and online search performance. Students were randomly assigned to a matrix note, conventional note, or note-free condition and then to one of the four experimental blocks, counterbalancing the order of online search topics and time pressure. Results of the study showed that 44 out of 60 participants (73.33%) conducted at least an irrelevant browsing. Students in the matrix note condition and those under high time pressure exhibited a lower task distraction rate. Moreover, students taking matrix notes demonstrated better online-search performance. Note-taking strategies and task distraction rate were significant predictors of participants' online search performance controlling for their prior knowledge. Study results are consistent with the load theory of attention and cognitive control and have implications to reduce student distraction and improve learning effectiveness.en_US
dc.language.isoen_USen_US
dc.subjectDigital distractionen_US
dc.subjectMedia multitaskingen_US
dc.subjectNote-taking strategyen_US
dc.subjectTime pressureen_US
dc.subjectBrowsing behaviorsen_US
dc.subjectOnline learning performanceen_US
dc.titleUsing time pressure and note-taking to prevent digital distraction behavior and enhance online search performance: Perspectives from the load theory of attention and cognitive controlen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.chb.2018.07.008en_US
dc.identifier.journalCOMPUTERS IN HUMAN BEHAVIORen_US
dc.citation.volume88en_US
dc.citation.spage244en_US
dc.citation.epage254en_US
dc.contributor.department教育研究所zh_TW
dc.contributor.departmentInstitute of Educationen_US
dc.identifier.wosnumberWOS:000443665400027en_US
dc.citation.woscount1en_US
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