An Analysis of Factors Predicting Retention and Language Atrophy Over Time for Successful DLI Graduates

Abstract

The Defense Language Institute Foreign Language Center (DLIFLC) is the Department of Defense multi-service school that provides resident instruction in more than a dozen languages to thousands of students annually. Students have to pass the Defense Language Proficiency Test (DLPT) with a score of 2 or better on listening and reading parts of the test to graduate. Service members have to re-test annually after they graduate to maintain their qualifications and additional pay. Some service members maintain their proficiency after graduating better than others, however, and many show a deterioration of proficiency over time and require additional training. DLIFLC needs to better understand how graduates' language skills evolve after they leave the school, to justify future adjustments and enhancements to the program. Using the data collected by DLIFLC and the Defense Manpower Data Center we developed a logistic regression model to determine what factors are associated with the atrophy of the acquired language skills within the first year after graduation. We also looked at the long-term survival probabilities for DLPT scores using Kaplan-Meyer estimators by stratifying data into subsets. Both methodologies have shown that overall GPA is the most important predictor of the score longevity. Service branch, language category, and initial DLPT scores were shown to be significant discriminators of the test scores' survival over time.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2022
Accession Number
AD1184905

Entities

People

  • Oleg Green

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • California
  • Data Centers
  • Data Sets
  • Databases
  • Department Of Defense
  • Estimators
  • Foreign Languages
  • Information Science
  • Language
  • Literature Surveys
  • Machine Learning
  • Neural Networks
  • Operations Research
  • Schools
  • Statistical Analysis
  • Statistics
  • Students
  • Training
  • United States

Fields of Study

  • Education

Readers

  • STEM Education
  • Systems Analysis and Design