Predictive Analysis of Defense Language Proficiency Test Outcomes: A Comparative Study Using Neural Networks and Logistic Regression
Document Type
Conference Proceeding
Publication Date
4-17-2025
Abstract
Excerpt: Proficiency in foreign languages is crucial for effective global operations, and proficiency can be gained from training courses. In this work, we study the influence of various training courses by analyzing a 9,436-row dataset, including factors such as language, test timing, and their effect on an individual's language test performance.
Source Publication
Data Science. CSCE 2024. Communications in Computer and Information Science, vol 2253
Recommended Citation
Smith, J., Mbonimpa, E., Wagner, T., Langhals, B. (2025). Predictive Analysis of Defense Language Proficiency Test Outcomes: A Comparative Study Using Neural Networks and Logistic Regression. In: Stahlbock, R., Arabnia, H.R. (eds) Data Science. CSCE 2024. Communications in Computer and Information Science, vol 2253. Springer, Cham. https://doi.org/10.1007/978-3-031-85856-7_1
Comments
This conference paper is published by Springer as cited, and is available by purchase or subscription through the DOI link below.
Author note: All authors affiliated with the Data Analytics Certificate Program at AFIT's Graduate School of Engineering and Management.