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Teachable robots can be used to support student learning, and tailoring the robot's behaviours - such as their speech, gestures, or expressions - to individual users can further improve the experience and user outcomes. This study investigates whether an algorithm which personalises a teachable robot's dialog responses can improve task engagement, and is conducted in both Australia and Japan to compare the effect across two diverse cultures.

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This page is a summary of: Adapting a Teachable Robot’s Dialog Responses using Reinforcement Learning: Cross-Cultural User Study Exploring Effect on Engagement, ACM Transactions on Human-Robot Interaction, June 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3743692.
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