Jessica Sullivan - US grants

Project Summary  Understanding how children learn ­­ and especially understanding how children learn language ­­  is a  critical  public  health  issue.  Positive  academic  outcomes  (which  are  predicted  by  early  language  skill)  are  associated with positive health outcomes like lower rates of substance abuse, higher rates of offspring survival,  higher occupational success, and longer lifespans (Hawkins, Catalano, & Miller, 1992? Low, Low, Baumler, &  Huynh,  2005?  McGregor  et  al.,  2007?  Serbin,  Stack,  &  Kingdon,  2013).  While  we  know  that  early  social,  cognitive,  and  language  ability  predict  educational  outcomes  (McGregor  et  al.,  2007?  Marchman  &  Fernald,  2008),  many  basic  questions  about  early  child  development  remain  unanswered,  making  it  challenging  to  design effective early educational policy and interventions. One important question is how a child?s input (e.g.,  the things that they see and hear in daily life) predicts what they end up learning. This question is relevant to  researchers interested in all aspects of development. Answering such a question, however, requires actually  measuring a child?s input ­­ something that until recently was technologically impossible. PI Sullivan and Drs.  Frank  and  Perfors  (see  letters  of  support)  created  a  large  longitudinal  dataset  of  videos  from  the  child?s  perspective to measure input. Our goal is to make this dataset available and accessible to other researchers.  Using a head­mounted camera, we recorded everything that participants saw and heard ­­ from their  perspective  ­­  for  approximately  2.5  hours  a  week  over  the  course  of  two  years  (from  infancy  through  toddlerhood), and continued through toddlerhood. Recordings were naturalistic, and included a wide array of  contexts and activities that have never previously been recorded. This resulted in a dataset of over 325 hours  of audiovisual recordings, along with a dense collection of cognitive, social, and linguistic measures that were  also  collected  longitudinally.  This  dataset  is  the  first  of  its  kind,  and  is  unique  in  its  size,  scope,  and  perspective.  This R03 proposal has three main aims. First, we aim to post the entirety of our dataset to Databrary,  an NIH­funded host for video data relevant to child development research. This will allow other researchers to  access our rich dataset. This will require converting the videos into a standardized format and collaborating  with Databrary to host the videos. Our second aim is to attach the appropriate metadata to the videos so that  they can be searchable by researchers. To this end, we will hire a full­time research assistant who will create a  database of both video­level data (e.g., the time of day and year, the child?s age, the people featured in the  video) and timestamped data (e.g., names of locations, activities, and objects salient in the child?s visual field).  Third, we will transcribe and provide a detailed coding of a sizeable subset of our corpus (including verbatim  transcriptions, descriptions of the objects being touched and seen, and coding of the referents of each speech  act) that will allow other researchers to immediately begin answering questions of our data.  

Preschool numeracy is a crucial foundation for STEM learning and long-term academic success. Previous research suggests that the development of strong numeracy skills depends on a combination of perceptual, cognitive, and language skills. However, most past studies have focused on a relatively small and homogeneous groups of children in US urban areas. As a result, current understanding of early numeracy may not<br/>generalize to diverse groups of learners. It is likely that home language background, socio-economic status, and geographic and cross-cultural differences could also influence numeracy development. To address this, and to probe what factors drive early numeracy in a representative sample, this first-of-its-kind project investigates how toddlers and preschool-aged children perceive, reason, and talk about numbers in a massive multi-lab collaboration involving over 130 research sites worldwide.<br/><br/>To investigate early numeracy, this collaborative project includes two foundational studies. The first study focuses on how 2- to 5-year-old children perceive quantity, learn number words, and how to accurately count groups of objects. The study examines variability in how children learn about number and quantity while exploring the underlying perceptual, cognitive and linguistic mechanisms that drive their learning. The second foundational study focuses on toddler’s abilities to keep track of small groups of objects, which researchers have argued may play an especially important role in early numerical learning. This study examines variability across larger and more diverse groups of participants than previously studied. The study also asks whether limits to children’s object tracking abilities change when they begin to learn number words. In addition to these foundational studies, the project supports the creation of multiple exploratory studies, allowing for novel, ground-breaking collaborations between researchers worldwide. These exploratory studies examine how numerical abilities are related to diverse phenomena including but not limited to social cognition, linguistic diversity, cognitive abilities like executive function, and cross-cultural differences in mathematics education and attitudes. Collectively, these studies will test over 3000 children in 28 US states and 27 countries, using a combination of cross-sectional and longitudinal behavioral assessments. Final data will be shared with the broader scientific community, and will be presented on a website in simplified form to make findings accessible to the broader public.<br/><br/>This project is funded by the EHR Core Research (ECR) program, which supports work that advances fundamental research on STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.