Mixed Reality (MR) is gaining prominence in manual task skill learning due to its in-situ, embodied, and immersive experience. To teach manual tasks, current methodologies break the task into hierarchies (tasks into subtasks) and visualize the current subtask and future in terms of causality. Existing psychology literature also shows that humans learn tasks by breaking them into hierarchies. In order to understand the design space of information visualized to the learner for better task understanding, we conducted a user study with 48 users. The study was conducted using a complex assembly task, which involves learning of both actions and tool usage. We aim to explore the effect of visualization of causality in the hierarchy for manual task learning in MR by four options: no causality, event level causality, interaction level causality, and gesture level causality. The results show that the user understands and performs best when all the level of causality is shown to the user. Based on the results, we further provide design recommendations and in-depth discussions for future manual task learning systems.

翻译：混合现实（MR）因其原位性、具身性和沉浸式体验，在手工技能学习中日益受到重视。为教授手工任务，现有方法论将任务分解为层级结构（任务分解为子任务），并以因果关系形式可视化当前子任务及后续步骤。现有心理学文献也表明，人类通过层级分解来学习任务。为探究如何设计信息可视化以帮助学习者更好理解任务，我们开展了一项包含48名用户的用户研究。研究采用涉及动作学习与工具使用的复杂装配任务，旨在通过四种方案探索层级因果关系可视化对MR手工任务学习的影响：无因果关系、事件级因果关系、交互级因果关系和手势级因果关系。结果表明，当向用户展示所有层级的因果关系时，其理解与操作表现最佳。基于研究结果，我们进一步为未来手工任务学习系统提供了设计建议与深入讨论。