Socially assistive robots (SARs) are increasingly deployed in educational and information-sharing contexts, supported by advances in large language models that enable fluent real-time interaction. Despite the growing diversity of robot embodiments, it remains unclear whether a single robot appearance is appropriate across different interaction tasks or whether trust depends primarily on contextual factors. In this study, we examine how robot appearance and task type jointly influence trust in robots. Using a within-subjects video-based experiment (N = 81), participants evaluated three robots with distinct appearances while performing three educationally relevant tasks: teaching, procedural instruction, and personal-information discussion. Results from repeated-measures analyses show a strong main effect of task on trust, with participants reporting the highest trust during instructional guidance, moderate trust during teaching activities, and significantly lower trust when robots requested personal information. In contrast, robot appearance showed no significant main effect, and the interaction between appearance and task was marginal. These findings suggest that trust in human-robot interaction is shaped more strongly by task context than by physical embodiment alone. By focusing on future educators as end users, this work contributes empirical evidence toward task-aware robot deployment in educational environments and highlights the importance of aligning robot roles and behaviors with interaction goals rather than relying solely on anthropomorphic design.

翻译：社交辅助机器人（SARs）依托大型语言模型的进步，实现了流畅的实时交互，正越来越多地被部署于教育和信息共享场景中。尽管机器人具身形态日益多样化，但尚不明确：单一机器人外观是否适用于不同的交互任务，抑或信任主要取决于情境因素。本研究探讨了机器人外观与任务类型如何共同影响人们对机器人的信任。通过一项受试者内设计的视频实验（N=81），参与者评估了三种外观迥异的机器人执行三项教育相关任务（教学、程序指导和个人信息讨论）时的表现。重复测量分析结果显示：任务对信任存在显著主效应——参与者在指导性引导任务中报告信任度最高，教学活动中的信任度中等，而当机器人索要个人信息时信任度显著降低。相比之下，机器人外观未呈现显著主效应，且外观与任务交互作用不显著。这些发现表明，人机交互中的信任更多取决于任务情境，而非仅凭物理具身形态。本研究以未来教育工作者为终端用户，为教育环境中任务感知型机器人部署提供了实证依据，并强调：相较于单纯依赖拟人化设计，应将机器人角色与行为同交互目标对齐。