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Exploring individual variation in Turkish heritage speakers’ complex linguistic productions: Evidence from discourse markers ...
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LASSO Regression Modeling on Prediction of Medical Terms among Seafarers’ Health Documents Using Tidy Text Mining
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In: Bioengineering; Volume 9; Issue 3; Pages: 124 (2022)
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Linguistic Mathematical Relationships Saved or Lost in Translating Texts: Extension of the Statistical Theory of Translation and Its Application to the New Testament
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In: Information; Volume 13; Issue 1; Pages: 20 (2022)
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Predicting Academic Performance: Analysis of Students’ Mental Health Condition from Social Media Interactions
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In: Behavioral Sciences; Volume 12; Issue 4; Pages: 87 (2022)
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Using Geolocated Text to Quantify Location in Real Estate Appraisal
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Cross-Sectional Analysis of Methods of Computing Partial Correlation Coefficients: A Self-Explained Note With R Syntax
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In: Cross-Cultural Communication; Vol 18, No 1 (2022): Cross-Cultural Communication; 18-31 ; 1923-6700 ; 1712-8358 (2022)
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THE EFFECTS OF L2 PRAGMATIC AUTONOMOUS AND CONTROLLED MOTIVATIONS ON ENGAGEMENT WITH PRAGMATIC ASPECT
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In: TEFLIN Journal, Vol 33, Iss 1, Pp 148-172 (2022) (2022)
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Tackling Morphological Analogies Using Deep Learning -- Extended Version
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In: https://hal.inria.fr/hal-03425776 ; 2021 (2021)
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A dimension reduction technique applied to regression on high dimension, low sample size neurophysiological data sets
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In: ISSN: 1471-2202 ; EISSN: 1471-2202 ; BMC Neuroscience ; https://hal.univ-grenoble-alpes.fr/hal-03374818 ; BMC Neuroscience, BioMed Central, 2021, 22 (1), ⟨10.1186/s12868-020-00605-0⟩ (2021)
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Pragmatic Influences on Argument Word Order in Karuk Narrative Texts
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In: Berkeley Papers in Formal Linguistics, vol 3, iss 1 (2021)
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A logistic regression model for predicting child language performance ; Un modèle de régression logistique pour la prédiction du développement langagier chez l'enfant
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In: SIS 2021, 50th Annuale Conference of the Italian Statistical Society" ; https://hal.archives-ouvertes.fr/hal-03318721 ; SIS 2021, 50th Annuale Conference of the Italian Statistical Society", Jun 2021, Pise, Italy (2021)
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Native word order processing is not uniform: An ERP-study of verb-second word order ...
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A multi-method approach to correlate identification in acoustic data: The case of Media Lengua
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In: Laboratory Phonology: Journal of the Association for Laboratory Phonology; Vol 12, No 1 (2021); 13 ; 1868-6354 (2021)
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The Orange workflow for observing collocation trends ColTrend 1.0
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Which data do elementary school teachers use to determine reading difficulties in their students?
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In: Journal of learning disabilities 54 (2021) 5, S. 349-364 (2021)
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STUDENT ACHIEVEMENT INDICATORS AT DEFENSE LANGUAGE INSTITUTE FOREIGN LANGUAGE CENTER
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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. ; Lieutenant Commander, United States Navy ; Approved for public release. distribution is unlimited
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Keyword:
Area Under the Curve; Armed Services Vocational Aptitude Battery; ASVAB; AUC; categorical; classification table; data; Defense Language Aptitude Battery; Defense Language Institute; Defense Language Proficiency Test; DLAB; DLI; DLPT; goodness of fit; grades; language; logistic; model; neural network; numeric; random forest; Receiver Operating Characteristic; regression; ROC; sensitivity; specificity; step-wise; stepwise; success
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URL: http://hdl.handle.net/10945/67111
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Which data do elementary school teachers use to determine reading difficulties in their students? ...
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