Social robots: a meta-analysis of learning outcomes
J.C.F. de Winter (TU Delft - Mechanical Engineering)
D. Dodou (TU Delft - Mechanical Engineering)
Fleur Moorlag (Student TU Delft)
Joost Broekens (Universiteit Leiden)
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Abstract
Previous meta-analyses show that social robots aid learning but were often limited in scope or grouped diverse control conditions together. This meta-analysis examined learning outcomes, focusing on control condition type. We retrieved 146 studies (Google Scholar and reference searches) where a physical social robot was used for training cognitive skills, comprising 183 post-test effect sizes between the robot and the control group, and 372 pre-post effect sizes. Analysis of the 78 studies with control groups indicated that robots generally improved learning, most notably when compared to a no-training control group (d = 0.75). Comparing robots to human teachers yielded an overall positive effect (d = 0.31), although effect sizes varied widely. This variability was explained by the robot’s role: robots in a co-teaching capacity showed a strong positive effect (d = 0.88), while robots replacing the teacher showed no benefit (d = −0.06). LLM-based sentiment analysis indicated that papers from outside Europe received higher positivity scores when describing the robots. We conclude that the effect size is influenced by the robot implementation and the control condition chosen.
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