Engaging learners with complex unfamiliar datasets is a known challenge in Data Science education. One promising phenomenon investigated in related work is perspective-taking. A first-person “actor” perspective can help facilitate group and individual sensemaking by mediating observations and actions taken by learners. Here we investigate how museum visitors made use of an actor perspective when exploring an open-ended, interactive data map museum exhibit. We use a mix of qualitative and quantitative empirical methods to explore how actor perspective-taking (APT) may mediate joint sensemaking around data visualizations. By applying interpretive coding to 54 conversations wherein APT naturalistically emerged, we identify 3 distinct self-to-data relationships constructed via APT: role-play, projection, and orientation. A further analysis explores how APT was embedded in joint sensemaking of the visualized data. Twelve APT-mediated sensemaking processes are identified; two (extrapolating and noticing absence) were used in conjunction with multiple APT self-to-data relationships, while the remaining ten (e.g., enacting, spatially characterizing, generalizing) were exclusively used with specific self-to-data APT relationships. We use these empirical findings to generate hypotheses about how APT and associated sensemaking processes may support Data Science learning goals.

在复杂的陌生数据集中吸引学习者是数据科学教育中的一项已知挑战。在相关工作中研究的一种有前途的现象是透视。第一人称“演员”视角可以通过调解学习者的观察和采取的行动，帮助促进团体和个人的感官交流。在这里，我们研究了博物馆参观者在探索开放式交互式数据地图博物馆展览时如何利用演员的视角。我们使用定性和定量的经验方法相结合的方式来探索演员的视角（APT）如何调解围绕数据可视化的联合意义。通过对APT自然出现的54个会话应用解释性编码，我们确定了通过APT构建的3种不同的自我数据关系：角色扮演，投射和方向。进一步的分析探讨了APT如何嵌入到可视化数据的联合感知中。确定了十二个由APT介导的感知过程；其中两个（外推和注意缺失）与多个APT自我数据关系结合使用，而其余十个（例如，制定，空间表征，概括）则专门用于特定的自我数据APT关系。我们使用这些经验性发现得出关于APT和相关的推理过程如何支持数据科学学习目标的假设。