Semantic Difficulty for Bilingual Children: Effects of Age, Language Exposure, and Language Ability.

PURPOSE: Semantic tasks evaluate dimensions of children's lexical-semantic knowledge. However, the relative ease of semantic task completion depends on individual differences in developmental and language experience factors. The purpose of this study was to evaluate how language experience and language ability impact semantic task difficulty in English for school-age Spanish-English bilingual children with and without developmental language disorder (DLD). METHOD: Participants included 232 Spanish-English bilingual children in second through fifth grade with (n = 35) and without (n = 197) DLD. Data included children's performance on the English Semantics subtest of the Bilingual English-Spanish Assessment-Middle Extension Field Test Version (BESA-ME), age of English acquisition, and percent English language exposure. Task difficulty, a measurement of the relative ease of task completion, was calculated for six semantic task types included on the BESA-ME. Multilevel regression modeling was conducted to estimate longitudinal growth trajectories for each semantic task type. RESULTS: Results showed that language ability and grade level drive semantic task difficulty for all task types, and children with DLD experienced greater difficulty on all task types compared to their typically developing peers. Longitudinally, semantic task difficulty decreased for all children, regardless of language ability, indicating that semantic task types became easier over time. While children made gains on all semantic tasks, the growth rate of task difficulty was not equal across task types, where some task types showed slower growth compared with others. English language exposure emerged as a significant predictor of semantic task difficulty while age of acquisition was not a significant factor. CONCLUSIONS: This study clarifies developmental profiles of lexical-semantic performance in bilingual children with and without DLD and supports clinical decision-making regarding children's English language learning.

Identifying Language Disorder in Bilingual Children Using Automatic Speech Recognition.

PURPOSE: The differential diagnosis of developmental language disorder (DLD) in bilingual children represents a unique challenge due to their distributed language exposure and knowledge. The current evidence indicates that dual-language testing yields the most accurate classification of DLD among bilinguals, but there are limited personnel and resources to support this practice. The purpose of this study was therefore to determine the feasibility of dual-language automatic speech recognition (ASR) for identifying DLD in bilingual children. METHOD: Eighty-four Spanish-English bilingual second graders with (n = 25) and without (n = 59) confirmed diagnoses of DLD completed the Bilingual English-Spanish Assessment-Middle Extension Morphosyntax in both languages. Their responses on a subset of items were scored manually by human examiners and programmatically by a researcher-developed ASR application employing a commercial speech-to-text algorithm. RESULTS: Results demonstrated moderate overall item-by-item scoring agreement (k = .54) and similar classification accuracy values (human = 92%, ASR = 88%) between the two methods using the best-language score. Classification accuracy of the ASR method increased to 94% of cases correctly classified when test items with poorer discrimination in the ASR condition were eliminated. CONCLUSION: This study provides preliminary support for the technical feasibility of ASR as a bilingual expressive language assessment tool. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.20249994.

Factors influencing US speech and language therapists' use of technology for clinical practice.

BACKGROUND: There is an increasing number of technological resources available to speech and language therapists (SLTs) for use in clinical practice, but the factors that influence SLTs' selection and use of such resources are not well understood. In related fields, technology acceptance models have been employed to explain users' adoption of technology and to inform the advancement of empirically supported technological resources. AIMS: To determine the factors that influence SLTs' use of technology for clinical practice by testing a model of their technology acceptance and use. METHODS & PROCEDURES: We surveyed 209 practising SLTs in the United States representative of the speech and language membership of the American Speech-Language-Hearing Association (ASHA). Participants completed a 38-item electronic survey representing four categories: (1) technology use, (2) technology attitudes and factors influencing technology use, (3) employment information and (4) demographics. Items measuring technology attitudes served as indicators of the research model, which mapped the primary relationships of a technology acceptance model. Survey data were collected before the Covid-19 pandemic. OUTCOMES & RESULTS: The research model accounted for 66% of the variance in SLTs' behavioural intention to use technology, which significantly and positively predicted the amount of time they reportedly spent using technology in the workplace. Subjective norms and attitudes towards technology use directly predicted the intention to use technology. Perceived usefulness and ease of use indirectly predicted intention to use technology. Survey respondents reported using technology during 48% (SD = 24%) of their overall weekly work hours on average, with a large majority reporting using technology at least once per week for planning (89% of respondents), assessment (66% of respondents) or intervention (90% of respondents). CONCLUSIONS & IMPLICATIONS: These findings statistically explain the relationships between SLTs' attitudes and their intention to use technology for clinical practice, contributing to our understanding of why SLTs adopt certain technologies. We also detail the nature and frequency of technology use in the clinical practice of SLTs. Future directions for this work include further exploring use categories, employing direct measurements of technology use and exploring the impact of recent changes in SLT service delivery due to the Covid-19 pandemic on SLTs' technology attitudes. What this paper adds What is already known on the subject Existing research about the adoption and use of technological resources by SLTs indicates that they select tools based on convenience, cost and recommendations by others. What this paper adds to existing knowledge This study is the first to develop and test a research model of SLTs' technology attitudes. The findings from model testing demonstrate the significant predictors of SLTs' behavioural intention to use technology for clinical purposes. Intent of use is related to how much SLTs use technology in the workplace. What are the potential or actual clinical implications of this work? The present findings can inform interventions targeting the design and adoption of electronic SLT resources that are empirically supported.

Identifying Developmental Language Disorder in School age Bilinguals: Semantics, Grammar, and Narratives.

Children with Developmental language disorder (DLD) have particular difficulty learning language despite otherwise general normal development. When school age bilingual children struggle with language, a common question is if the difficulties they present reflect lack of ability or lack of language experience. To address the question of identification of DLD in the context of bilingualism, we explore the diagnostic accuracy of measures administered in two languages. The Bilingual English Spanish Assessment Middle Extension (BESA-ME) assesses semantics and morphosyntax and the Test of Narrative Language (TNL) assesses comprehension and production of narratives. These measures were administered to 112 second graders (19 with DLD) and 64 fourth graders (7 with DLD). We explored the classification accuracy of each of these measures alone and in combination using receiver operator characteristic (ROC) curve analysis. The ROC curve illustrates diagnostic classification of a measure at various cutpoints. We compared the extent to which measures in English, Spanish, or best language account for area under the (ROC) curve. Discriminant function analysis using the best indicator (Spanish, English, best language) from each type of measure (semantics, morphosyntax, narrative) in combination demonstrate classification accuracy above 80%. Morphosyntax in the best language was the strongest predictor of DLD for second grade children. In fourth grade, the three measures contributed more equally in predicting DLD.

Los niños con trastornos de desarrollo del lenguaje tienen dificultad especial para aprender el lenguaje a pesar de tener un desarrollo general dentro de los límites normales. Cuando los niños de edad escolar no aprenden el idioma de la misma manera que sus compañeros nos preguntamos si esto se debe a un trastorno o falta de experiencia con el idioma. Para entender cómo identificar el trastorno del lenguaje en el contexto bilingüe, exploramos la precisión diagnóstica de pruebas que se administran en los dos idiomas del niño bilingüe. The Bilingual English Spanish Assessment Middle Extension (BESA-ME) (Prueba del Lenguaje Bilingüe en Español e Inglés ­ extensión media) se enfoca en la semántica y la morfosintaxis y del Test of Narrative Language (TNL) (Prueba de Lenguaje Narrativo) que evalúa la comprensión y expresión de la narrativa. Se dieron estas pruebas a 112 estudiantes de segundo grado (19 con trastorno del lenguaje) y 64 estudiantes de cuarto grado (7 con trastorno del lenguaje) . Usamos la característica del operador del receptor (COR) para calcular la precisión de las dos pruebas individuales y en combinación. La curva del COR ilustra la precisión diagnóstica de una prueba en base de varios puntos de corte en la curva. Comparamos la precisión de las medidas en español, inglés o en la mejor de los dos lenguas, en base del área bajo la curva COR.El análisis de la función de discriminación, usando el indicador más informativo (español, inglés, o el mejor idioma) de cada área evaluada (semántica, morfosintaxis, narrativa), resultó en un índice de precisión arriba del 80% correcto. El rendimiento en el área de morfosintaxis en el mejor idioma es el indicador más preciso para los niños de segundo grado. Para los niños de cuarto grado, los tres indicadores contribuyeron igualmente a la precisión diagnóstica para el trastorno en el desarrollo de lenguaje.