Latent knowledge structures of traversal behavior in hypertext environment

  • Authors:
  • Perwaiz B. Ismaili

  • Affiliations:
  • School of Behavioral and Brain Sciences, University of Texas at Dallas

  • Venue:
  • WSEAS Transactions on Computers
  • Year:
  • 2009

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Abstract

In this paper, we introduce "Knowledge Diagraph Contribution" (KDC) analysis as a novel categorical time-series method in observing underlying traversal knowledge structure of experts by exploiting varying hypertext (web) presentation formats and knowledge domains. The navigation behaviors were studied by designing hypertext presentation formats and domain text that adheres to content design principles inspired by discourse and text comprehension scholars. As a continuation of previous study by Ismaili & Golden [1], twenty undergraduate psychology students from University of Texas at Dallas participated in this study. Students traversed through different Hypertext (web) presentation formats while reading content from three different knowledge domains controlled for micro (web-page, web-site) and macro (consistent semantic connections across knowledge domains) characteristics. The influence of expertise and web traversal behavior in deriving underlying knowledge structures is presented using KDC analysis. In addition, previously reported Classical data analysis (ANOVA) are compared with KDC analysis in highlighting quantitative and qualitative differences of these derived latent knowledge structures. As compared with novice, experts tend to exhibit sequential and semantic traversal patterns across all three web formats, whereas, novices are more influenced by and therefore tend to employ random navigation strategies.