Sho Tsuji BITSS CatalystCognitive Science

Sho Tsuji is an Assistant Professor at the University of Tokyo. She studies the role of social cues, specifically interactivity, on infant word learning. Using techniques like gaze-contingent eye-tracking, she tries to disentangle the influence of social cues from the presence of a human interaction partner during learning.

During her PhD, Sho conducted her first meta-analysis on infant vowel discrimination and since then, she has been convinced that a meta-analysis is a great starting point for many scientific projects. Based on the infrastructure she built around her and other meta-analyses, her team proposed the concept of community-augmented meta-analyses (Tsuji, Bergmann, & Cristia, 2014), a concept that later lead to MetaLab, a project funded by a SSMART grant. MetaLab is an open-access, dynamic, and growing database of meta-analyses on infant language development, and aims to lower the hurdles of using meta-analytic tools by providing educational material as well as ready-to-use visualization and calculation tools. She was also a postdoctoral researcher at University of Pennsylvania and Laboratoire de Sciences Cognitives et Psycholinguistique.

Dr. Tsuiji promotes the use and creation of meta-analysis by teaching the technique during workshops, classes, and conferences, as well as continuing to develop the educational material for MetaLab (like this video tutorial series).