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Given the demonstrated efficacy of robots in educational contexts, a wide range of robotic platforms have been specifically designed for educational purposes. While numerous individual studies have explored the effect of robot-based education, few systematic reviews or meta-analyses have synthesized robots’ effect on educational outcomes such as academic achievement, computational knowledge, learning motivation, and performance. This study aims to bridge this research gap by studying the effect of robots on educational outcomes through a rigorous meta-analysis and systematic review following established guidelines (PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Literature was retrieved from numerous online databases such as Web of Science, ScienceDirect, and EI Compendex. Based on inclusion and exclusion criteria, 36 studies were finally included for this study. Hedge’s g was adopted to calculate the effect sizes, I2 statistics was used to measure heterogeneity, and sensitivity analysis and publication bias tests such as Begg’s test, Egger’s test, and funnel plots were used to verify the robustness. The study concludes that robot-based education is associated with moderate-to-large improvements in academic achievement (g = 0.72; 95%CI = 0.30~1.13, medium-to-large effect), computational knowledge (g = 0.85; 95%CI = 0.55~1.15, large effect), motivation (g = 0.47; 95%CI = 0.19~0.75, medium effect), performance (g = 0.81; 95%CI = 0.22~1.40, large effect), and overall educational outcomes (g = 0.71; 95%CI = 0.50~0.92, medium-to-large effect) compared to traditional methods. No significant publication bias was detected, and the results were demonstrated to be robust. The study has confirmed that robot-based education is an effective pedagogical approach. Thus, there is a pressing need for future research to focus on designing robot-based education programs with a specific focus on optimizing educational outcomes.
Tang et al. (Mon,) studied this question.