Relationship Between Measures of Dialect and Teacher Ratings of Student Language Ability

Students who speak African American English are typically rated lower in language and literacy ability than students who speak General American English. When this happens, it can lead to higher referral rates for evaluations for speech and language disorders and a mischaracterization of academic ability due to linguistic biases. This study explores how teacher ratings of student language and literacy ability are influenced by student dialect use.Teachers completed a questionnaire about students' language and literacy skills. Two measures of student dialect use were computed from student language samples: percent dialect density and a listener judgment task. Linear regressions were conducted to determine the predictive effects of dialect density and listener judgments on teacher ratings. Given that there were significant differences in teacher ratings across grade levels, analyses controlled for student grade.Across two measures of dialect, results suggested that student dialect use did not significantly influence teacher ratings of language and literacy skills when controlling for student grade.The results suggest that factors other than student dialect use may influence teacher ratings. Future research should consider both student-level variables (e.g., socio-economic status) and teacher-level variables (e.g., training and exposure to language variation).

Authors

Institutions

Publication Details

Journal
Seminars in Speech and Language
Published
2025-06-01
DOI
https://doi.org/10.1055/a-2763-2728
Primary Topic
Language Development and Disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Relationship Between Measures of Dialect and Teacher Ratings of Student Language Ability

Alison Eisel Hendricks, Franchesca M. Arecy
Seminars in Speech and Language
Language Development and Disorders
article

Relationship Between Measures of Dialect and Teacher Ratings of Student Language Ability

Alison Eisel Hendricks, Franchesca M. Arecy
article en

Abstract

Students who speak African American English are typically rated lower in language and literacy ability than students who speak General American English. When this happens, it can lead to higher referral rates for evaluations for speech and language disorders and a mischaracterization of academic ability due to linguistic biases. This study explores how teacher ratings of student language and literacy ability are influenced by student dialect use.Teachers completed a questionnaire about students' language and literacy skills. Two measures of student dialect use were computed from student language samples: percent dialect density and a listener judgment task. Linear regressions were conducted to determine the predictive effects of dialect density and listener judgments on teacher ratings. Given that there were significant differences in teacher ratings across grade levels, analyses controlled for student grade.Across two measures of dialect, results suggested that student dialect use did not significantly influence teacher ratings of language and literacy skills when controlling for student grade.The results suggest that factors other than student dialect use may influence teacher ratings. Future research should consider both student-level variables (e.g., socio-economic status) and teacher-level variables (e.g., training and exposure to language variation).

Seminars in Speech and LanguageVol. 46(03)
University at Buffalo, State University of New York (US)
Quality Education
Openalex Percentile: Top 22%
Language Development and Disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.