In children's collaborative learning, effective peer conversations can significantly enhance the quality of children's collaborative interactions. The integration of Large Language Model (LLM) agents into this setting explores their novel role as peers, assessing impacts as team moderators and participants. We invited two groups of participants to engage in a collaborative learning workshop, where they discussed and proposed conceptual solutions to a design problem. The peer conversation transcripts were analyzed using thematic analysis. We discovered that peer agents, while managing discussions effectively as team moderators, sometimes have their instructions disregarded. As participants, they foster children's creative thinking but may not consistently provide timely feedback. These findings highlight potential design improvements and considerations for peer agents in both roles.

翻译：在儿童协作学习中，有效的同伴对话能显著提升协作互动的质量。将大语言模型智能体融入该情境，旨在探索其作为同伴的新颖角色，评估其作为团队主持者与参与者的影响。我们邀请两组参与者参与协作学习工作坊，共同讨论并提出设计问题的概念性解决方案。通过主题分析法对同伴对话记录进行分析，发现：作为团队主持者，同伴智能体虽能有效管理讨论，但其指令有时会被忽视；作为参与者，智能体能激发儿童的创造性思维，但可能无法持续提供及时反馈。这些发现揭示了同伴智能体在两种角色中的潜在设计改进方向与注意事项。