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Thursday, January 13 • 20:30 - 22:00
Glick et al.: Using engagement to predict word learning by toddlers in an online task

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Slack: ​https://bcccd.slack.com/archives/C02P9HXP99D​​​

Aaron R. Glick 1,3, Ella Vezina 1,2, Kristine H. Onishi 2,3, Aparna Nadig 1,3
1 School of Communication Sciences and Disorders, McGill University, Montreal, Canada
2 Department of Psychology, McGill University, Montreal, Canada
3 Centre for Research on Brain, Language and Music, Montreal, Canada


Young children engage with screens multiple times a day, so it is important to study the factors impacting children’s learning. Engagement is considered a necessary condition for learning (Aguiar & McWilliam, 2013), yet it has typically been reported only as a secondary result in studies assessing word learning in digital contexts (see Myers et al. 2017; Roseberry et al. 2014; Strouse et al., 2018; Troseth et al., 2006) although we know that social contingency and co-viewing moderate learning outcomes in children, particularly in digital environments (Myers, et al., 2017; Roseberry et al., 2014; Strouse et al., 2018). We ask whether children’s level of engagement moderates learning in online contexts, predicting learning outcomes.

We conducted a word learning study remotely with children at home and collected data via webcam. Twenty-one children (24- to 48-months, M = 38) saw four novel objects, two of which were labeled, via prerecorded video or live video-chat. In test, children heard the novel labels and were asked to select the novel object from a set of three. We measured child engagement through (a) observational coding from webcam videos (b) parent ratings and (c) experimenter ratings. Engagement measures moderated referent selection outcomes, yet no single measure reliably moderated outcomes, instead, there were significant interactions between age, observation, and rating measures (β = 2.82) and between observation and rating measures (β = -1.14). Our findings suggest that depending on age, different engagement measures may better capture learning outcomes.

  • Session 10, Thursday, 13 Jan, 20:30 - 22:00 (UTC +0)
  • Session 6, Wednesday, 12 Jan, 13:00 - 14:30 (UTC +0)

Thursday January 13, 2022 20:30 - 22:00 UTC
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