Using Latent Semantic Analysis to Score Short Answer Constructed Responses: Automated Scoring of the Consequences Test.

Journal: Educational and psychological measurement
Published Date:

Abstract

Automated scoring based on Latent Semantic Analysis (LSA) has been successfully used to score essays and constrained short answer responses. Scoring tests that capture open-ended, short answer responses poses some challenges for machine learning approaches. We used LSA techniques to score short answer responses to the Consequences Test, a measure of creativity and divergent thinking that encourages a wide range of potential responses. Analyses demonstrated that the LSA scores were highly correlated with conventional Consequence Test scores, reaching a correlation of .94 with human raters and were moderately correlated with performance criteria. This approach to scoring short answer constructed responses solves many practical problems including the time for humans to rate open-ended responses and the difficulty in achieving reliable scoring.

Authors

  • Noelle LaVoie
    Parallel Consulting, Petaluma, CA, USA.
  • James Parker
    Parallel Consulting, Petaluma, CA, USA.
  • Peter J Legree
    U.S. Army Research Institute for the Behavioral and Social Sciences, Fort Belvoir, VA, USA.
  • Sharon Ardison
    U.S. Army Research Institute for the Behavioral and Social Sciences, Fort Belvoir, VA, USA.
  • Robert N Kilcullen
    U.S. Army Research Institute for the Behavioral and Social Sciences, Fort Belvoir, VA, USA.

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