AI 中文总结
该研究针对天文学教育中扩大学生望远镜操作体验难的问题，设计了MIRA平台，构建观测全生命周期，自动处理数据并提供教程，通过特定方式分离前端与控制，连接课堂与天文台操作，提供真实科研工作流程。
AI 中文摘要
实践望远镜体验常用于促进学生参与天文学教育，但扩大对更多学生的访问在操作上具有挑战性。因此，学生仅接触到专业工作流程的一小部分，很少参与严格的同行评审、时间分配过程或管理现代研究设施的自动数据处理管道。我们展示了MIRA（使用机器人天文学的指导研究）的设计，这是一个数据管理和教育平台，将瑞士中学生和本科生与运行中的机器人天文台连接起来。MIRA构建了整个观测生命周期：提案、评审、接受/拒绝、调度和观测。执行后，该平台会自动处理原始FITS帧（包括天体测量校准和测光），并通过基于网络的存档以及基于Python的分析教程提供这些数据。通过Astra和ASCOM Alpaca将教育前端与低级望远镜控制分离，MIRA提供了一个真实的科学研究工作流程，将课堂学习与专业天文台操作联系起来。
英文摘要
Hands-on telescope experience is often used to drive student engagement in astronomy education, but scaling access to larger groups of students is operationally challenging. Consequently, students encounter only a fraction of the professional workflow, rarely engaging with the rigorous peer-review, time-allocation processes, or automated data reduction pipelines that govern modern research facilities. We present the design of MIRA (Mentored Investigations using Robotic Astronomy), a data management and educational platform that connects Swiss secondary school and undergraduate students with operational robotic observatories. MIRA structures the entire observation lifecycle: proposal, review, acceptance/rejection, scheduling, and observation. Following execution, the platform automatically reduces raw FITS frames (including astrometric calibration and photometry) and serves them via a web-accessible archive accompanied by Python-based analysis tutorials. By separating educational front-ends from low-level telescope controls through Astra and ASCOM Alpaca, MIRA delivers an authentic scientific research workflow that bridges classroom learning with professional observatory operations.
Comments9 pages, 6 figures, 1 table, proceedings of SPIE Astronomical Telescopes + Instrumentation 2026, 14151-125
