Abstract

This article analyses how robot–learner interaction in robot-assisted language learning (RALL) is influenced by the interaction behaviour of the robot. Since the robot behaviour is to a large extent determined by the combination of teaching strategy, robot role and robot type, previous studies in RALL are first summarised with respect to which combinations that have been chosen, the rationale behind the choice and the effects on interaction and learning. The goal of the summary is to determine a suitable pedagogical set-up for RALL with adult learners, since previous RALL studies have almost exclusively been performed with children and youths. A user study in which 33 adult second language learners practice Swedish in three-party conversations with an anthropomorphic robot head is then presented. It is demonstrated how different robot interaction behaviours influence interaction between the robot and the learners and between the two learners. Through an analysis of learner interaction, collaboration and learner ratings for the different robot behaviours, it is observed that the learners were most positive towards the robot behaviour that focused on interviewing one learner at the time (highest average ratings), but that they were the most active in sessions when the robot encouraged learner–learner interaction. Moreover, the preferences and activity differed between learner pairs, depending on, e.g., their proficiency level and how well they knew the peer. It is therefore concluded that the robot behaviour needs to adapt to such factors. In addition, collaboration with the peer played an important part in conversation practice sessions to deal with linguistic difficulties or communication problems with the robot.

摘要

本文分析了机器人辅助语言学习（RALL）中机器人与学习者的交互如何受到机器人交互行为的影响。由于机器人行为在很大程度上取决于教学策略、机器人角色和机器人类型的组合，因此首先总结了 RALL 先前的研究，包括选择了哪些组合、选择背后的基本原理以及对交互的影响和学习。总结的目的是为成人学习者确定适合 RALL 的教学设置，因为以前的 RALL 研究几乎只针对儿童和青少年进行。然后介绍了一项用户研究，其中 33 名成年第二语言学习者在与拟人机器人头部的三方对话中练习瑞典语。展示了不同的机器人交互行为如何影响机器人与学习器之间以及两个学习器之间的交互。通过对不同机器人行为的学习者互动、协作和学习者评分的分析，可以观察到，学习者对当时专注于采访一名学习者的机器人行为最为积极（最高平均评分），但他们是当机器人鼓励学习者与学习者互动时，他们在会话中最为活跃。此外，学习者对之间的偏好和活动也不同，这取决于他们的熟练程度和他们对同伴的了解程度。因此得出结论，机器人行为需要适应这些因素。此外，