Abstract Pedagogical agents are typically designed to take on a single role: either as a tutor who guides and instructs the student, or as a tutee that learns from the student to reinforce what he/she knows. While both agent-role paradigms have been shown to promote student learning, we hypothesize that there will be heightened benefit with respect to students’ learning and emotional engagement if the agent engages children in a more peer-like way — adaptively switching between tutor/tutee roles. In this work, we present a novel active role-switching (ARS) policy trained using reinforcement learning, in which the agent is rewarded for adapting its tutor or tutee behavior to the child’s knowledge mastery level. To investigate how the three different child–agent interaction paradigms (tutee, tutor, and peer agents) impact children’s learning and affective engagement, we designed a randomized controlled between-subject experiment. Fifty-nine children aged 5–7 years old from a local public school participated in a collaborative word-learning activity with one of the three agent-role paradigms. Our analysis revealed that children’s vocabulary acquisition benefited from the robot tutor’s instruction and knowledge demonstration, whereas children exhibited slightly greater affect on their faces when the robot behaves as a tutee of the child. This synergistic effect between tutor and tutee roles suggests why our adaptive peer-like agent brought the most benefit to children’s vocabulary learning and affective engagement, as compared to an agent that interacts only as a tutor or tutee for the child. This work sheds light on how fixed role (tutor/tutee) and adaptive role (peer) agents support children’s cognitive and emotional needs as they play and learn. It also contributes to an important new dimension of designing educational agents — actively adapting roles based on the student’s engagement and learning needs.

中文翻译：

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与儿童一起教与学：社交机器人的互惠同伴学习对儿童学习和情感参与的影响

摘要 教学代理通常被设计为承担单一角色：作为指导和指导学生的导师，或作为向学生学习以加强他/她所知道的知识的学生。虽然两种代理角色范式都已被证明可以促进学生的学习，但我们假设，如果代理以更像同龄人的方式与孩子互动——在导师/学生之间自适应地切换，那么在学生的学习和情感参与方面将会有更大的好处角色。在这项工作中，我们提出了一种使用强化学习训练的新型主动角色转换 (ARS) 策略，其中代理因将其导师或学生行为适应孩子的知识掌握水平而获得奖励。研究三种不同的儿童-代理交互范式（学生、导师、和同伴代理）影响儿童的学习和情感参与，我们设计了一个随机控制的受试者间实验。来自当地公立学校的 59 名 5-7 岁的儿童参加了具有三个代理角色范式之一的协作单词学习活动。我们的分析表明，孩子的词汇习得受益于机器人导师的指导和知识展示，而当机器人表现得像孩子的学生时，孩子对他们的脸的影响略大。导师和学生角色之间的这种协同效应表明，与仅作为孩子的导师或学生互动的代理相比，为什么我们的自适应同伴代理为儿童的词汇学习和情感参与带来了最大的好处。这项工作阐明了固定角色（导师/学生）和适应性角色（同伴）代理如何支持儿童在玩耍和学习时的认知和情感需求。它还有助于设计教育代理的一个重要新维度——根据学生的参与和学习需求积极调整角色。