An Agent-Based Methodology for Analyzing and Visualizing
Educational Assessment Data Elizabeth Sklar Dept of Computer and Information Science Brooklyn College, City University of New York, Brooklyn, NY 11210, USA Jordan Salvit Dept of Computer and Information Science Brooklyn College, City University of New York, Brooklyn, NY 11210, USA Valerie Andrewlevich Dept of Computer and Information Science Brooklyn College, City University of New York, Brooklyn, NY 11210, USA Christopher Camacho Children's Progress, Inc., 41 East 11th Street, Suite 1100, New York City, NY 10003, USA William Liu Children's Progress, Inc., 41 East 11th Street, Suite 1100, New York City, NY 10003, USA 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.

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