Abstract

Online data collection methods are expanding the ease and access of developmental research for researchers and participants alike. While its popularity among developmental scientists has soared during the COVID-19 pandemic, its potential goes beyond just a means for safe, socially distanced data collection. In particular, advances in video conferencing software has enabled researchers to engage in face-to-face interactions with participants from nearly any location at any time. Due to the novelty of these methods, however, many researchers still remain uncertain about the differences in available approaches as well as the validity of online methods more broadly. In this article, we aim to address both issues with a focus on moderated (synchronous) data collected using video-conferencing software (e.g., Zoom). First, we review existing approaches for designing and executing moderated online studies with young children. We also present concrete examples of studies that implemented choice and verbal measures (Studies 1 and 2) and looking time (Studies 3 and 4) across both in-person and online moderated data collection methods. Direct comparison of the two methods within each study as well as a meta-analysis of all studies suggest that the results from the two methods are comparable, providing empirical support for the validity of moderated online data collection. Finally, we discuss current limitations of online data collection and possible solutions, as well as its potential to increase the accessibility, diversity, and replicability of developmental science.

Highlights

  • Over the past decade, online data collection has transformed the field of psychological science

  • The current paper aims to serve as a guide for developmental researchers seeking information about online data collection, with a focus on using video-chat software for moderated data collection

  • The older group was accurate for both success and fail trials (Success: 98.2%, Z = 3.64, p < 0.001; Fail: 76.8%, Z = 2.16, p = 0.039)

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Summary

Introduction

Online data collection has transformed the field of psychological science. Commercial crowdsourcing platforms such as Amazon Mechanical Turk have allowed participants to perform experimental tasks remotely from their own computers, making it easier, faster, and cheaper for researchers to collect large samples. Online methods have been mostly constrained to studies with adults, some recent efforts have pioneered ways to conduct developmental research online (e.g., Lookit, Scott and Schulz, 2017; TheChildLab.com, Sheskin and Keil, 2018; Panda, Rhodes et al, 2020). As the COVID-19 pandemic spurred many developmental researchers to consider safer alternatives to inperson interactions, these methods have quickly gained traction as an innovative way to enable large-scale data collection from children and maximize access and impact in developmental science (Sheskin et al, 2020). Researchers may feel hesitant to replicate or build on prior work using online methods because of uncertainties about how developmental data collected online would compare to data collected in person

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