Abstract
Developmental systems theory posits that development cannot be segmented by influences acting in isolation, but should be studied through a scientific lens that highlights the complex interactions between these forces over time (Overton, 2013a). This poses a unique challenge for developmental psychologists studying complex processes like language development. In this paper, we advocate for the combining of highly sophisticated data collection technologies in an effort to move toward a more systemic approach to studying language development. We investigate the efficiency and appropriateness of combining eye-tracking technology and the LENA (Language Environment Analysis) system, an automated language analysis tool, in an effort to explore the relation between language processing in early development, and external dynamic influences like parent and educator language input in the home and school environments. Eye-tracking allows us to study language processing via eye movement analysis; these eye movements have been linked to both conscious and unconscious cognitive processing, and thus provide one means of evaluating cognitive processes underlying language development that does not require the use of subjective parent reports or checklists. The LENA system, on the other hand, provides automated language output that describes a child’s language-rich environment. In combination, these technologies provide critical information not only about a child’s language processing abilities but also about the complexity of the child’s language environment. Thus, when used in conjunction these technologies allow researchers to explore the nature of interacting systems involved in language development.
Highlights
Developmental systems theory posits those forces explaining child development cannot be measured as independent influences (Lerner, 2006; Gottlieb, 2007; Overton, 2013a); rather, all forces interact to produce development over time
The study of language development is no exception; language is a hugely complex system whose development is affected by many factors, including both cognitive factors, such as processing efficiency, statistical learning, and phonological awareness (e.g., Stanovich et al, 1984; Fernald et al, 1998; Saffran, 2003) and environmental factors, like the socioeconomic status (SES) of the child’s family, the quantity and quality of language heard by the child, and the number of people with whom a child regularly spends time (e.g., Huttenlocher et al, 1991; Hart and Risley, 1995; Shneidman et al, 2009)
We propose that the Language Environment Analysis (LENA) system be used as a measure of typical children’s language development, alongside traditional measures of receptive and expressive vocabulary, in order to gain a more complete picture of the child’s skill level, the child’s language environment, and the role of adult language input in predicting the child’s skill level
Summary
Developmental systems theory posits those forces explaining child development cannot be measured as independent influences (Lerner, 2006; Gottlieb, 2007; Overton, 2013a); rather, all forces (e.g., cognitive, affective, motivational, environmental) interact to produce development over time. Faced with the task of incorporating several different factors to create a comprehensive model for early language development, there is a strong need to move toward more efficient data collection methodology coupled with stronger statistical models (Urban et al, 2011). In this methodological paper, we argue for the use of combinations of sophisticated technologies to allow researchers to examine the language environment, as well as those cognitive processes influenced by and influencing language environments. Will we begin to understand language development from a relational developmental systems perspective (Overton, 2013b)
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