Search (4 results, page 1 of 1)

  • × author_ss:"Gwizdka, J."
  • × year_i:[2010 TO 2020}
  1. Gwizdka, J.: Distribution of cognitive load in Web search (2010) 0.00 
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    Abstract
    The search task and the system both affect the demand on cognitive resources during information search. In some situations the demands may become too high for a person. This article has a three-fold goal. First, it presents and critiques methods to measure cognitive load. Second, it explores the distribution of load across search task stages. Finally, it seeks to improve our understanding of factors affecting cognitive load levels in information search. To this end, a controlled Web search experiment with 48 participants was conducted. Interaction logs were used to segment search tasks semiautomatically into task stages. Cognitive load was assessed using a new variant of the dual-task method. Average cognitive load was found to vary by search task stages. It was significantly higher during query formulation and user description of a relevant document as compared to examining search results and viewing individual documents. Semantic information shown next to the search results lists in one of the studied interfaces was found to decrease mental demands during query formulation and examination of the search results list. These findings demonstrate that changes in dynamic cognitive load can be detected within search tasks. Dynamic assessment of cognitive load is of core interest to information science because it enriches our understanding of cognitive demands imposed on people engaged in the search process by a task and the interactive information retrieval system employed.
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  2. Gwizdka, J.; Moshfeghi, Y.; Wilson, M.L.: Introduction to the special issue on neuro-information science (2019) 0.00 
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  3. Gwizdka, J.; Hosseini, R.; Cole, M.; Wang, S.: Temporal dynamics of eye-tracking and EEG during reading and relevance decisions (2017) 0.00 
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    Abstract
    Assessment of text relevance is an important aspect of human-information interaction. For many search sessions it is essential to achieving the task goal. This work investigates text relevance decision dynamics in a question-answering task by direct measurement of eye movement using eye-tracking and brain activity using electroencephalography EEG. The EEG measurements are correlated with the user's goal-directed attention allocation revealed by their eye movements. In a within-subject lab experiment (N?=?24), participants read short news stories of varied relevance. Eye movement and EEG features were calculated in three epochs of reading each news story (early, middle, final) and for periods where relevant words were read. Perceived relevance classification models were learned for each epoch. The results show reading epochs where relevant words were processed could be distinguished from other epochs. The classification models show increasing divergence in processing relevant vs. irrelevant documents after the initial epoch. This suggests differences in cognitive processes used to assess texts of varied relevance levels and provides evidence for the potential to detect these differences in information search sessions using eye tracking and EEG.
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  4. Bilal, D.; Gwizdka, J.: Children's query types and reformulations in Google search (2018) 0.00 
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