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Using a Robot Peer to Encourage the Production of Spatial Concepts in a Second Language

Published: 04 December 2018 Publication History

Abstract

We conducted a study with 25 children to investigate the effectiveness of a robot measuring and encouraging production of spatial concepts in a second language compared to a human experimenter. Productive vocabulary is often not measured in second language learning, due to the difficulty of both learning and assessing productive learning gains. We hypothesized that a robot peer may help assessing productive vocabulary. Previous studies on foreign language learning have found that robots can help to reduce language anxiety, leading to improved results. In our study we found that a robot is able to reach a similar performance to the experimenter in getting children to produce, despite the person's advantages in social ability, and discuss the extent to which a robot may be suitable for this task.

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cover image ACM Conferences
HAI '18: Proceedings of the 6th International Conference on Human-Agent Interaction
December 2018
402 pages
ISBN:9781450359535
DOI:10.1145/3284432
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 04 December 2018

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Author Tags

  1. assessment
  2. robot assisted language learning
  3. second language learning

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HAI '18
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HAI '18: 6th International Conference on Human-Agent Interaction
December 15 - 18, 2018
Southampton, United Kingdom

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HAI '18 Paper Acceptance Rate 40 of 92 submissions, 43%;
Overall Acceptance Rate 121 of 404 submissions, 30%

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