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）因其现场、具身和沉浸式体验，在手动作业技能学习中日益受到重视。为教授手动作业，现有方法将任务分解为层级结构（将任务细分为子任务），并以因果关系形式可视化当前子任务与后续任务。已有心理学文献也表明，人类通过层级分解来学习任务。为深入理解面向学习者的信息可视化设计空间以提升任务理解，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和工具使用的复杂装配任务，旨在探索混合现实手动作业学习中层级因果关系的四种可视化方案（无因果关系、事件级因果关系、交互级因果关系、手势级因果关系）的影响。结果表明，当向用户展示所有层级的因果关系时，用户的理解与操作表现最佳。基于研究结果，我们进一步提出了面向未来手动作业学习系统的设计建议与深度讨论。