Expanding the toolbox: 25 years of methodological change in infant research

The landscape of infant behavior research has undergone a remarkable transformation over the past quarter-century. In this special issue opinion article, we synthesize these methodological changes and their implications for developmental science. Drawing on a systematic comparative assessment of empirical articles published in Infant Behavior and Development in 2000 and 2024, we critically evaluate five key methodological dimensions: research contexts, sample and cell sizes, coding practices, data analysis techniques and statistical software, and open science practices. Our synthesis reveals how the field has expanded beyond traditional laboratory settings toward more diverse research environments, including remote and archival approaches that enhance ecological validity and sample diversity. We trace how sample sizes have nearly doubled and experimental cell sizes have increased 2.5-fold, strengthening statistical power and replicability. We examine the selective adoption of automated methodologies in domains like eye tracking and speech analysis, alongside the persistent value of manual coding for complex behaviors. We observe a transition from classical statistical methods to more nuanced analytical approaches, increasingly implemented in open source software, reflecting both technological capabilities and theoretical shifts toward capturing developmental complexity. Finally, we document the emergence of open science practices, which now appear in over a third of published studies. Throughout, we highlight how these methodological transformations reflect broader drivers: the replication crisis, technological innovations, and evolving theoretical perspectives. Looking forward, we offer a roadmap for methodological development that builds on these advances while addressing persistent challenges in the field.