An increasing number of children in preschools and schools around the country are from culturally and linguistically diverse backgrounds and speak multiple languages. However, clinicians are often challenged in conducting least-biased assessments of bilingual children, which often results in over-referral or under- referral of these children to special education and related services. Utilizing naturalistic and authentic assessment of child language such as language sampling is a recommended approach to augment traditional assessments in clinical settings. The Language ENvironment Analysis (LENA) technology offers clinicians a time-and cost effective means to gathering representative language samples across home and school environments to help determine the presence of speech-language impairment in young bilingual children. We describe an exploratory study using the LENA with five Spanish-English bilingual children to identify the accuracy of traditionally transcribed child word counts as compared to the automated child vocalization analyses obtained through the LENA. Results indicate the need for more research to fully explore the clinical utility of this technology for assessment of bilingual children.
