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Naturalistic observation is a primary methodological tool in studies of language development, yielding many insights about common developmental patterns as well as variation across children. Among other important findings, such studies have demonstrated that variation in language outcomes is linked to “meaningful differences” in the input that children hear (Hart & Risley, 1995). Yet in order to reap the benefits of this type of data, researchers must first tackle several challenges such as how to: 1) sample such that the data are dense enough to capture the phenomena of interest, 2) collect recordings that are representative of children’s daily lives, and 3) transcribe in a way that is both reliable and cost-efficient. The LENATM (Language ENvironment Analysis) system is a recent technological innovation that greatly facilitates the collection and analysis of naturalistic language samples. In this talk, we present how we have incorporated this technology into our ongoing studies of links between speech processing efficiency and early input in English- and Spanish-speaking toddlers from diverse backgrounds. Our goals are to share what we view as the advantages as well as the limitations of the LENA system for studies of children’s language development and language learning environments. This research was supported by grants from NIH to Anne Fernald (DC008838). |
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