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Yujia Liu; Emily K. Penner; Sabrina Solanki; Xuehan Zhou – Journal of Education Human Resources, 2025
Identifying high-quality educators at the point of hire can reduce future recruitment costs and minimize the impact of attrition on school organizations and student learning. One low-cost way to screen applicants and learn about their beliefs, values, and pedagogy is through their short-essay writing samples. However, there is limited research…
Descriptors: Teacher Selection, Screening Tests, Essays, Job Applicants
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Yangna Hu; Cindy Sing Bik Ngai; Sihui Chen – Journal of Speech, Language, and Hearing Research, 2025
Purpose: This study examines existing automatic screening methods for developmental language disorder (DLD), a neurodevelopmental language deficit without known biomedical etiologies, focusing on languages, data sets, extracted features, performance metrics, and classification methods. Additionally, it summarizes the strengths and weaknesses of…
Descriptors: Developmental Disabilities, Language Impairments, Automation, Screening Tests
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Altena, Allard J.; Spijker, René; Leeflang, Mariska M. G.; Olabarriaga, Sílvia Delgado – Research Synthesis Methods, 2021
When performing a systematic review, researchers screen the articles retrieved after a broad search strategy one by one, which is time-consuming. Computerised support of this screening process has been applied with varying success. This is partly due to the dependency on large amounts of data to develop models that predict inclusion. In this…
Descriptors: Screening Tests, Automation, Diagnostic Tests, Models
Wilson, Joshua; Rodrigues, Jessica – Grantee Submission, 2020
The present study leveraged advances in automated essay scoring (AES) technology to explore a proof of concept for a writing screener using the "Project Essay Grade" (PEG) program. First, the study investigated the extent to which an AES-scored multi-prompt writing screener accurately classified students as at risk of failing a Common…
Descriptors: Writing Tests, Screening Tests, Classification, Accuracy
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Dirlikov, Benjamin; Younes, Laurent; Nebel, Mary Beth; Martinelli, Mary Katherine; Tiedemann, Alyssa Nicole; Koch, Carolyn A.; Fiorilli, Diana; Bastian, Amy J.; Denckla, Martha Bridge; Miller, Michael I.; Mostofsky, Stewart H. – Journal of Occupational Therapy, Schools & Early Intervention, 2017
This study presents construct validity for a novel automated morphometric and kinematic handwriting assessment, including (1) convergent validity, establishing reliability of automated measures with traditional manual-derived Minnesota Handwriting Assessment (MHA), and (2) discriminant validity, establishing that the automated methods distinguish…
Descriptors: Handwriting, Evaluation Methods, Children, Preadolescents