Re-Estimation of Student Ability in Foreign Languages Using the Rasch Model

Abstract

This study investigates the effectiveness of the Rasch psychometric model in improving predictive validity of French language placement testing. Three multidimensional models, multiple regression, discriminant analysis, and an a priori rational weighting scheme were compared to three unidimensional ability estimation procedures, raw score, Rasch model score (non-fitting test items deleted), and the Rasch model score corrected for five test disturbances (guessing, test start-up anxiety, sloppiness, item content and person interaction, and plodding). These six estimation procedures (predictor variables) were applied to a single French placement test used in assigning students to three language courses of differing levels of instruction. The criterion (predicted) variables were the student scores obtained on all tests during one semester of language instruction.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1988
Accession Number
ADA197151

Entities

People

  • Philip J. Westfall

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Data Analysis
  • Data Science
  • Discriminant Analysis
  • French Language
  • Grammars
  • Information Science
  • Language
  • New York
  • Psychology
  • Regression Analysis
  • Schools
  • Statistical Analysis
  • Statistics
  • Students
  • United States

Fields of Study

  • Education

Readers

  • Psychometric Testing or Psychological Assessment.
  • Theoretical Analysis.