# Mixed Reality-Based Robotics Education--Supervisor Perspective on Thesis Works
## 1 Introduction
[23] concluded in their meta-analysis on the impact of AR in education that AR has a larger mean effect size on students' performance as well as higher learner responses, but also identified that the 3D visualization used in AR learning experiences needs to be carefully designed. In his master's thesis, [PERSON] describes the development of a teach-and-learn scenario in industrial robotics using an UR5 and a Hololens2. In his application, the movement of the joints and speed can be observed and studied to prevent collision when it is implemented in a real-world scenario. The capability to change the robot arm in the simulation is a very crucial point for the education sector, where the real size and real movement speed of each joint can be compared between several different robot arms, although it still has several imperfections, such as software malfunctions, shifts in operating environments, or the misinterpretation of human intentions [24]. [PERSON] et al. [25] explore the integration of XR, robotics, and vision-language models. Their work presented valuable insights into how these technologies can be combined to simplify robot programming and enhance user interaction. This research introduces an innovative framework that leverages large language models (LLMs) and AR [26], creating a seamless interface for human-robot collaboration. The recent MASTER-XR initiative [27] is an EU-funded project aimed at integrating Extended Reality (XR) technologies into industrial robotics education. It focuses on developing an open-source XR platform to enhance vocational training and upskilling in manufacturing, emphasizing advanced interaction mechanisms and high-quality educational content. The first results of the awarded projects are expected to be published throughout 2025/2026. It can be summarized that MR/AR applications for education and/or training in engineering domains are increasingly being found in many different areas. In the field of robotics, especially industrial robotics, to the best of our knowledge, in all evaluated research papers and especially surveys, only one contribution could be identified to deal with MR-based robotics education [28]. Furthermore, obstacles and challenges during the development and the measurement of the learning outcome, are typically not specifically investigated in the present literature. [PERSON] et al. [29] identified that the threshold to design and develop respective educational artefacts is still high. Also, they state that the development and design process of such applications often remains fuzzy, as insights on the use of current MR authoring tools are missing. Therefore, in this work, we resolve these shortcomings. In particular, we make the following contributions:  
1. Introduction of seven thesis works showcasing MR developments in the educational field of robotics, all supervised by the main author. 2. Comparative analysis of the presented works, highlighting the different approaches, insights, and contributions of each work. 3. Identification of key indicators for a comparative study of AR learning experiences in robotics. 4. Summary of advantages and obstacles during the development and use of MR applications from the supervisor's point of view.