A New Integrated Model for Multitasking during Web Searching
Author(s) -
Peggy Alexopoulou,
Anne Morris,
Mark Hepworth
Publication year - 2014
Publication title -
procedia - social and behavioral sciences
Language(s) - English
Resource type - Journals
ISSN - 1877-0428
DOI - 10.1016/j.sbspro.2014.07.088
Subject(s) - human multitasking , computer science , think aloud protocol , cognition , task (project management) , task switching , working memory , information behavior , protocol analysis , artifact (error) , cognitive models of information retrieval , human–computer interaction , exploratory research , cognitive psychology , psychology , world wide web , cognitive science , artificial intelligence , engineering , usability , human–computer information retrieval , systems engineering , neuroscience , search engine , sociology , anthropology
There have been many studies in the field of information behavior. Recently Du and Spink (2011) presented a model, which simulates multitasking, cognitive coordination and cognitive shifts on web. However, this model does not incorporate personal variables and the impact of task or web design. This research addresses this gap. Information and psychological scientists have shown that information behavior (IR) is affected by: the affective domain, cognitive attributes, psychological factors, personality dimensions and sociological factors. This study investigates how IR is affected by working memory (wm), cognitive coordination, cognitive shifts and various artifacts and task variables influenced by the PAT model (Personal, Artifact and Task characteristics) of flow. The research is exploratory and takes a pragmatic, mixed method approach. Thirty University students will participate. The research tools include: pre and post questionnaires, working memory tests, Flow State Scale test, think aloud data, observations, audio-visual data, web search logs and use of the Critical Decision Method. The qualitative data will be coded and analyzed thematically and will be related to the quantitative data. This study is expected to identify the impact of all these variables on multitasking IR in the web and provide a new integrated framework, which is not only going to help information scientists to better understand this behavior but also web companies to develop more effective web products
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