Search (3 results, page 1 of 1)

  • × theme_ss:"Benutzerstudien"
  • × theme_ss:"Hypertext"
  1. Marchionini, G.; Xia, L.; Dwiggins, S.: Efforts of search and subject expertise on information seeking in a hypertext environment (1990) 0.00 
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    Abstract
    As part of ongoing investigation of information seeking behaviour of end users in electronic environments, a comparison was made of those users having expertise in a topic area and those with expertise in online searching. Computer scientists and online search specialists conducted assigned searches in a HyperCard database on the topic of hypertext. Both groups of experts were able to conduct successful searches and outperformed a novice control group. Search specialists took slightly less time tahn the domain experts, modified queries by adding terms found in the text, and tended to focus on query formulation. Domain experts focused on the text and used their domain knowledge for further question answering
    Imprint
    Medford, NJ : Learned Information Inc.
    Source
    ASIS'90: Information in the year 2000, from research to applications. Proc. of the 53rd Annual Meeting of the American Society for Information Science, Toronto, Canada, 4.-8.11.1990. Ed. by Diana Henderson
    Theme
    Information
  2. Carlson, J.R.; Kacmar, C.J.: an examination of end-user preferences : Increasing link marker effectiveness for WWW and other hypermedia interfaces (1999) 0.00 
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    Source
    Journal of the American Society for Information Science. 50(1999) no.5, S.386-398
  3. Barab, S.A.; Bowdish, B.E.; Lawless, K.A.: Hypermedia navigation : profiles of hypermedia users (1997) 0.00 
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    Abstract
    In this study we explored the use of logfiles as a window into the process of hypermedia navigation. Although there is a growing body of research addressing theoretical and design issues related to open-ended, non-directive technologies such as hypermedia, relatively few studies have attempted to explain navigational performance. 66 undergraduate students used a multidimensional, computer-based kiosk that could be explored in a nonlinear fashion to find information in response to one of two information retrieval tasks (simple or complex). Cluster analysis was used to generate performance profiles derived from navigational data captured in log files. Analyses of within cluster performance profiles, combined with external validation criteria, led to the classification of 4 different types of navigational performance (models users, disenchanted volunteers, feature explorers, and cyber cartographers). These characterizations were consistent with information retrieval users and the external criteria (self-efficacy, perceived utility, and interest). For example, individual who appeared to fake the time to learn the layout of the kiosk also had the highest self-efficacy, while those who used the help screen and watched the most movies had the lowest self-efficacy. Results also demonstrated an interaction between various individual navigational profiles and type information retrieval task

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