Optimal Text Space Representation of Student Essays Using Latent Semantic Analysis

Abstract

This paper provides a framework for optimally representing student written essays in a vector space, based upon Latent Semantic Analysis and instructor evaluated grades. Comparing student essays to an authoritative source, a ranking scheme is optimized that allows for a unique vector space representation on the unit circle. Once such a representation has been found, traditional methods of circular data analysis and inference can be applied, as we demonstrate.