Computer-based studies usually produce log files as raw data. These data cannot be analyzed adequately with conventional statistical software. The Chemnitz LogAnalyzer provides tools for quick and comfortable visualization and analyses of hypertext navigation behavior by individual users and for aggregated data. In addition, it supports analogous analyses of questionnaire data and reanalysis with respect to several predefined orders of nodes of the same hypertext. As an illustration of how to use the Chemnitz LogAnalyzer, we give an account of one study on learning with hypertext. Participants either searched for specific details or read a hypertext document to familiarize themselves with its content. The tool helped identify navigation strategies affected by these two processing goals and provided comparisons, for example, of processing times and visited sites. Altogether, the Chemnitz LogAnalyzer fills the gap between log files as raw data of Web-based studies and conventional statistical software.
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http://dx.doi.org/10.3758/bf03192691 | DOI Listing |
Behav Res Methods
August 2009
Deutsche Telekom Laboratories, Berlin University of Technology, Berlin, Germany.
In the present study, we investigated three factors that were assumed to have a significant influence on the success of learning from multiple hypertexts, and on the construction of a documents model in particular. These factors were task (argumentative vs. narrative), available text material (with vs.
View Article and Find Full Text PDFBehav Res Methods
May 2005
Department of Psychology, Program in Cognitive Psychology, Chemnitz University of Technology, D-09107 Chemnitz, Germany.
Computer-based studies usually produce log files as raw data. These data cannot be analyzed adequately with conventional statistical software. The Chemnitz LogAnalyzer provides tools for quick and comfortable visualization and analyses of hypertext navigation behavior by individual users and for aggregated data.
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