Lookit (Part 1): A New Online Platform for Developmental Research

Abstract

Many important questions about children’s early abilities and learning mechanisms remain unanswered not because of their inherent scientific difficulty but because of practical challenges: recruiting an adequate number of children, reaching special populations, or scheduling repeated sessions. Additionally, small participant pools create barriers to replication while differing laboratory environments make it difficult to share protocols with precision, limiting the reproducibility of developmental research. Here we introduce a new platform, “Lookit,” that addresses these constraints by allowing families to participate in behavioral studies online via webcam. We show that this platform can be used to test infants (11–18 months), toddlers (24–36 months), and preschoolers (36–60 months) and reliably code looking time, preferential looking, and verbal responses, respectively; empirical results of these studies are presented in Scott, Chu, and Schulz ( 2017 ). In contrast to most laboratory-based studies, participants were roughly representative of the American population with regards to income, race, and parental education. We discuss broad technical and methodological aspects of the platform, its strengths and limitations, recommendations for researchers interested in conducting developmental studies online, and issues that remain before online testing can fulfill its promise.

Using automation to combat the replication crisis: A case study from controlled-rearing studies of newborn chicks

“…Many researchers in developmental psychology are already moving in this direction. For example, while it is not possible to experimentally test human infants 24/7, new automated internet-based platforms, such as "Lookit", allow families to participate in behavioral studies via webcam (51,52). Thus, researchers can begin recruiting larger numbers of infants and collecting repeated measurements.…”

A thousand studies for the price of one: Accelerating psychological science with Pushkin

“…To be clear: some questions cannot (yet) be addressed through massive online experiments for methodological reasons, such as those that currently require magnetic resonance imaging. Likewise, some populations, such as babies, remain difficult to recruit and test online (though see Scott & Schulz, 2017). However, the wide-spread use of online studies gives an indication of just how many research questions can be addressed online (see Stewart et al, 2017).…”

“…For a creative solution for testing children via Amazon Mechanical Turk, seeScott and Schulz (2017). 2 Here we focus on datasets originating from experiments, rather than on secondary uses of preexisting systems, such as observational studies of online gamers and social networkers or experiments conducted by websites on their users(Bainbridge, 2007;Hardy & Scanlon, 2009;Settles & Meeder, 2016;Streeter, 2015;Wilson, Gosling, & Graham, 2012).…”

Preregistration in infant research—A primer

“…Infant studies will probably continue to be costly to conduct, and the possibility of getting clean measures will remain limited. Therefore, the problem of measurement noise, data scarcity, and formulating precise predictions will prevail (though see some new developments, e.g., https://lookit.mit.edu/, an online platform for testing infants; Scott & Schulz, 2017). While we cannot offer a one‐size‐fits‐all solution to dealing with protocol deviations or uncertainties in protocol planning, one way to reduce these is to include, where possible, decision tree type preregistrations, where potential points of deviation are anticipated and steps to decide on the form of deviations are described (though see Williams & Albers, 2019, for counterarguments).…”