Student Achievement Indicators at Defense Language Institute Foreign Language Center

Abstract

The Defense Language Institute (DLI) trains most of the cryptologic language analysts (CLA) that perform translation and analysis of data to support the United States military and intelligence communities. Students take the Defense Language Proficiency Test (DLPT) when graduating, passing if they achieve a score of L2/R2 (2+ on the Listening portion, 2+ on the Reading). DLI has been ordered to improve its students scores upon graduation. It seeks an improved model to screen applicants for the potential to achieve the new, more difficult grading benchmark of 2+ Listening, 2+ Reading. Former NPS student Jonathan Bermudez-Mendez looked into predicting student test scores based on grades, prior language experience, Defense Language Aptitude Battery (DLAB) scores, whether a student was recycled from a different language program, language category, and whether the student attended an immersion program, using stepwise logistic regression. We show that random forests and neural networks, especially the former, can improve on existing predictive models. We also investigate some univariate relationships based on prior language experience and show that many aspects of prior language exposure are statistically significantly related to the event of a student passing at the new benchmark.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1150437

Entities

People

  • Ian A. Brenner

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Data Analysis
  • Data Mining
  • Data Science
  • Deep Learning
  • Enlisted Personnel
  • Information Science
  • Machine Learning
  • Neural Networks
  • Operations Research
  • Personnel Management
  • Predictive Modeling
  • Statistical Analysis
  • Statistics
  • Students
  • Supervised Machine Learning
  • Two Dimensional
  • United States

Fields of Study

  • Education

Readers

  • Computational Linguistics
  • Psychometric Testing or Psychological Assessment.
  • STEM Education

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation
  • AI & ML - Neural Networks