Expanding access to webcam-based online data collection for developmental research

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This project will expand, Lookit, an online platform designed to conduct and promote developmental research. The platform will enable families to participate in research studies while in their own homes, using their own computers. The researchers will recruit study participants and make it possible for other researchers to post studies on the Lookit system; thereby, creating a tool for researchers, teachers, and doctors to learn how children think and grow. The project will expand knowledge about child development by making it more practical for researchers to measure small effects, include appropriate controls, work with special populations, and/or observe individual differences across repeated sessions. It will also provide a way to conduct more reproducible work, so that studies from different laboratories can more reliably build on each other. Lookit will broaden family participation in developmental studies, so that research better represents the variety of family structures, educational backgrounds, and communities of American families. In addition, Lookit will reduce barriers faced by researchers who study children but do not have access to laboratories.In-person developmental research is subject to practical constraints that limit which questions can be addressed. In particular, it is often impractical to work with large numbers of children in order to measure small or graded effects, recruit special populations, conduct longitudinal studies, or observe behaviors in homes. The proposed project aims to reduce these barriers by developing a common resource for online testing, allowing researchers to post their studies on the Lookit platform so families can participate at home. The site will be centrally hosted, with a shared participant userbase, but researchers will control access to their own data. The researchers will develop the functionality needed to bring the current system to scale; recruit a large, diverse participant userbase to enable rapid collection of large datasets online; and refine the researcher interface and produce training materials for researchers using the platform.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.