An agent-based methodology for analyzing and visualizing educational assessment data

Authors:
Elizabeth Sklar;Jordan Salvit;Christopher Camacho;William Liu
Affiliations:
City University of New York, Brooklyn, NY;City University of New York, Brooklyn, NY;Children's Progress, Inc., New York City, NY;Children's Progress, Inc., New York City, NY
Venue:
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Year:
2007

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Abstract

We examine data collected from on-line assessments of the numeracy and literacy skills of young students in order to construct probabilistic agent-based controllers. We demonstrate the value of this methodology as an effective means for both analyzing and visualizing aspects of large data sets that are difficult to capture with traditional equation-based statistics and static graphics.