Report on a Query Generation Technique for Measuring Comprehension of Statistical Graphics

Abstract

In our information-driven society, there is increasing use of statistical graphics to convey information in a variety of settings, including industry, mass media, government operations, and health care. Current methods for assessing a readers ability to comprehend statistical graphics are custom-written, not widely accepted, usable only once, and/or reliant on subjective interpretations and inferences. We have developed a method for generating queries suitable for evaluating graph comprehension capability. Our method is based on the Sentence Verification Technique (SVT), an empirically validated framework for measuring an individuals comprehension of prose material. Compared to ad hoc methods for testing graph comprehension, our technique is less subjective, requires less manual effort and subject matter expertise, and addresses the essential features of a given graph: values and relationships depicted, frames of reference, and style attributes. The SVT and our derived method combat superficial comprehension by testing what the reader has encoded, as opposed to testing the readers ability at visual recall or ability to look up data without reaching real comprehension. We motivate and describe our query generation method and report on a pilot study using queries generated with it.

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Document Details

Document Type
Technical Report
Publication Date
Aug 29, 2019
Accession Number
AD1089902

Entities

People

  • Alexander S. Lulushi
  • Christopher Van Dolson
  • Dennis J. Perzanowski
  • Derek Brock
  • Jonathan W. Decker
  • Joseph Matthews
  • Mark A. Livingston

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Cognitive Science
  • Computer Graphics
  • Computers
  • Data Visualization
  • Education
  • Graphics
  • Health Care
  • Human-Machine Interaction
  • Information Systems
  • Language
  • Machine Learning
  • Pilot Studies
  • Psychology
  • Standards
  • Visualizations

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Information Retrieval