Nonmainstream Dialects Research Articles

Assessment of language acquisition.

This review addresses questions of what should be assessed in language acquisition, and how to do it. The design of a language assessment is crucially connected to its purpose, whether for diagnosis, development of an intervention plan, or for research. Precise profiles of language strengths and weaknesses are required for clear definitions of the phenotypes of particular language and neurodevelopmental disorders. The benefits and costs of formal tests versus language sampling assessments are reviewed. Content validity, theoretically and empirically grounded in child language acquisition, is claimed to be centrally important for appropriate assessment. Without this grounding, links between phenomena can be missed, and interpretations of underlying difficulties can be compromised. Sensitivity and specificity of assessment instruments are often assessed using a gold standard of existing tests and diagnostic practices, but problems arise if that standard is biased against particular groups or dialects. The paper addresses the issues raised by the goal of unbiased assessment of children from diverse linguistic and cultural backgrounds, especially speakers of non-mainstream dialects or bilingual children. A variety of new approaches are discussed for language assessment, including dynamic assessment, experimental tools such as intermodal preferential looking, and training studies that assess generalization. Stress is placed on the need for measures of the process of acquisition rather than just levels of achievement. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website.

Variation Within Dialects: A Case of Cajun/Creole Influence Within Child SAAE and SWE

This study examined whether child speakers of Southern African American English (SAAE) and Southern White English (SWE) who were also perceived by some listeners to present a Cajun/Creole English (CE) influence within their dialects produced elevated rates of 6 phonological and 5 morphological patterns of vernacular relative to other SAAE- and SWE-speaking children. A group comparison design was followed. The data were listener judgments, 1-min audiotaped excerpts of conversational speech, and transcribed language samples from 93 children (31 classified as specifically language impaired while the others were classified as either aged-matched or language-matched controls; 13 classified as SWE with CE, 40 classified as SWE only, 18 classified as SAAE with CE, and 22 classified as SAAE only). Results indicated that children with a CE influence produced elevated rates of vernacular phonology relative to the others, with 2 patterns (nonaspirated stops and glide reduction) showing statistically significant group differences. In contrast, the children's use of vernacular morphology was unrelated to their CE status, but was instead related to their primary dialect (SWE vs. SAAE) and language ability classification (impaired vs. normal). The findings highlight the role of phonology in listeners' perceptions of dialect variation within 2 nonmainstream dialects (SWE and SAAE). The findings also demonstrate the ways phonological and morphological forms of vernacular can be independently influenced by different types of child variables.

Methods for Characterizing Participants' Nonmainstream Dialect Use in Child Language Research

Three different approaches to the characterization of research participants' nonmainstream dialect use can be found in the literature. They include listener judgment ratings, type-based counts of nonmainstream pattern use, and token-based counts. In this paper, we examined these three approaches, as well as shortcuts to these methods, using language samples from 93 children previously described in J. Oetting and J. McDonald (2001). Nonmainstream dialects represented in the samples included rural Louisiana versions of Southern White English (SWE) and Southern African American English (SAAE). Depending on the method and shortcut used, correct dialect classifications (SWE or SAAE) were made for 88% to 97% of the participants; however, regression algorithms had to be applied to the type- and token-based results to achieve these outcomes. For characterizing the rate at which the participants produced the nonmainstream patterns, the token-based methods were found to be superior to the others, but estimates from all approaches were moderately to highly correlated with each other. When type- and/or token-based methods were used to characterize participants' dialect type and rate, the number of patterns included in the analyses could be substantially reduced without significantly affecting the validity of the outcomes. These findings have important implications for future child language studies that are done within the context of dialect diversity.

Nonmainstream dialect use and specific language impairment.

Most work looking at specific language impairment (SLI) has been done in the context of mainstream dialects. This paper extends the study of SLI to two nonmainstream dialects: a rural version of Southern African American English (SAAE) and a rural version of Southern White English (SWE). Data were language samples from 93 4- to 6-year-olds who lived in southeastern Louisiana. Forty were classified as speakers of SAAE, and 53 were classified as speakers of SWE. A third were previously diagnosed as SLI; the others served as either age-matched (6N) or language-matched (4N) controls. The two dialects differed in frequency of usage on 14 of the 35 coded morphosyntactic surface patterns; speakers of these dialects could be successfully discriminated (94%) from each other in a discriminant analysis using just four of these patterns. Across dialects, four patterns resulted in main effects that were related to diagnostic condition (SLI vs. 6N), and a slightly different set of four patterns showed effects that were related to developmental processes (4N vs. 6N). More interestingly, the surface characteristics of SLI were found to manifest in the two dialects in different ways. A discriminant function based solely on SAAE speakers tended to misclassify SWE children with SLI as having normal language, and a discriminant function based on SWE speakers tended to misclassify SAAE unaffected children as SLI. Patterns within the SLI profile that cut across the two dialects included difficulties with tense marking and question formation. The results provide important direction for future studies and argue for the inclusion of contrastive as well as noncontrastive features of dialects within SLI research.