ABSTRACT. Intelligent robotics bridges the gap between the digital and physical worlds, which requires a solid understanding of many different aspects. In this paper, we describe our approach to a gentle introduction into robotics control in general and control theory in particular using a small electric airplane with an Arduino micro-controller. The micro controller has a built in pressure sensor which allows surprisingly efficient and accurate control of the altitude of the plane. In addition to concepts and techniques in aerodynamics, the plane domain is a extremely moti vating domain to introduce students to necessity for and approaches to open-loop and feedback control. We tested the approach with a group of about 30 students.

ABSTRACT. Laboratory experiments are a crucial and most practical part in university courses to apply and observe inner dependencies of theoretical concepts introduced in lectures, especially in engineering. The capacities for these are usually limited due to the high personnel support effort, which increases with the number of students. Therefore, remote laboratories (ReLabs) can provide a scalable, continuously available substitute or additional offer to the usual on-site laboratories. Upon a ReLab, developed in 2017, we propose a further development as well as the implementation in two additional courses. The ReLab is completely open-source on the software side and only requires off-the-shelf personal computers and webcams next to the custom test bench on the hardware side. To evaluate the benefits to students, we surveyed participants from three courses.

ABSTRACT. This paper presents UAIbot, a free and open-source web-based robotics simulator designed to address the educational and research challenges conventional simulation platforms generally face. The Python and JavaScript interfaces of UAIbot enable accessible hands-on learning experiences without cumbersome installations. By allowing users to explore fundamental mathematical and physical principles interactively, ranging from manipulator kinematics to pedestrian flow dynamics, UAIbot provides an effective tool for deepening student understanding, facilitating rapid experimentation, and enhancing research dissemination.

ABSTRACT. This pilot study evaluates the Robot Study Companion at the University of Guyana through a pre-and post-test experimental design involving 10 participants. Our work investigates students’ readiness for technology integration. It gauges user acceptance of the RSC based on key constructs of the Technology Acceptance Model. Pre-test results established baseline technology habits and learning preferences, while post-test feedback strongly supported the RSC’s potential to enhance self-directed learning, academic performance, and retention. Despite challenges such as limited interaction time and small sample size, participants provided valuable insights for ongoing developments.

ABSTRACT. This paper presents a framework designed for robot-assisted education of individuals with Autism Spectrum Disorder (ASD). The framework analyzes a specific type of educational task, known as "shoebox tasks", and applies this analysis to guide robot-assisted task solving. It uses the visual structure of shoebox tasks to generate correct task representations and to plan actions. To verify the feasibility of automated task analysis, we conducted preliminary experiments using vision-based machine learning and large language models (LLMs).

ABSTRACT. The Rescue Online Simulation (ROnSim) expands the Open Roberta platform by simulating the RoboCupJunior Rescue Line Entry challenge, allowing beginner students and educators to participate in a robotics competition without the financial and logistical entry barriers of physical hardware. Unlike existing robotics simulation platforms it does not aim to replace hardware. It rather serves as an easy bridge to hardware-based learning by fostering engagement with the RoboCupJu- nior community. Launching as an official discipline at RoboCupJunior Austrian Open 2025, will provide insights into its educational impact, further advancing the goal of democratizing robotics education and in- spiring future innovators. In this context, the related results of the IEEE RAS International Summer School on Educational Robotics 2024 (EduRob24) will be presented. These include the development of educational material for Open Roberta and key insights on improving simulation tools for Ed- ucational Robotics to better support school and teaching environments.

ABSTRACT. An effective approach to enhance the educational experience is gamification, a methodology that incorporates game-like elements and mechanics into the learning process to boost motivation and engagement. This paper describes the integration of gamification into the Unibotics open web platform, which is dedicated to teaching robotics to university engineering students. First, the infrastructure necessary to support robotics tournaments based on a collection of robotics exercises was designed and programmed. It includes an automated asynchronous execution of the code from each participant and an automated evaluation system capable of ranking participants based on their performance in these exercises. It also automatically generates video summaries of the execution of the student’s code. This innovation not only enhances the visibility of participants’ achievements but also fosters a dynamic and interactive learning environment. It uses the latest web technologies such as Django, React and mainly Selenium, which leverages the task automation due to its versatility. Second, a pilot experience was implemented with 26 engineering real students at a Spanish university showing good results. This work highlights the potential of combining gamification, robotics and web-based platforms to improve the learning experience, particularly in higher education, by fostering engagement, competition, and practical skill development.

ABSTRACT. This study examines the development of students' motivation in a hybrid robotics course, where some students worked with physical robots on campus while others used simulations online. The goal was to investigate how students' intrinsic motivation evolves in different learning environments while they were working with the course project work. The re-search utilized the Intrinsic Motivation Inventory (IMI) survey to measure students' motivation across five dimensions: interest/enjoyment, perceived competence, effort/importance, pressure/tension, and value/usefulness. The results indicate that hands-on project work enhanced students' overall motivation, whether they worked with physical robots or simulations. Notably, students reported an increase in their perceived competence and under-standing of robotics fundamentals. On-campus students found the project slightly more engaging and valuable. The study supports previous findings that project-based learning increases student motivation. The results suggest that both physical robots and simulations can serve as effective learn-ing tools in robotics education.

ABSTRACT. Since their launch in 2020, LEGO SPIKE Prime robots have become regular and popular participants in robotics activities and robot competitions. Accuracy and consistency are very important factors in the control of mobile robots, but the precise execution of a single movement is often a challenge for participants in robotics activities. This is particularly true in curved movements. The blocks used to program LEGO robots do not provide enough information to accurately plan turning motion in advance, so the trial and error method is often used. This paper proposes a more advanced method to explore the relationship between steering parameters and turning radii. As a result of a series of experiments, an approximate function relationship is presented that gives the steering parameter required to achieve the desired turning radius. Recognising the limitations of the steering parameter, we also developed a formula and method that can give the turning radius using the ratio of wheel speeds.

ABSTRACT. This ongoing study investigates the role of emerging digital technologies in engineering education, focusing on tools such as cloud-based CAD, Internet of Things (IoT) systems, and additive manufacturing. These technologies are examined for their ability to enhance collaborative learning, problem-solving, and technical skill development in engineering students. Through participatory case studies, the research evaluates how iterative design processes and hands-on projects foster teamwork and critical thinking in academic settings. The study also explores the integration of digital tools to bridge the gap between traditional academic training and the evolving demands of Industry 4.0, emphasizing the importance of aligning curricula with modern industrial needs. Preliminary findings demonstrate significant potential for these technologies to facilitate more effective and engaging learning experiences. By equipping students with essential Industry 4.0 skills and fostering adaptability, this research aims to contribute to the development of innovative pedagogical strategies that better prepare students for the challenges of a rapidly evolving technological landscape.

ABSTRACT. Mobile mini–robots are being increasingly used for research and education. Various platforms are available, each focusing on certain key features like CPU or GPU processing, high modularity, or low cost. In this area, the new mini–robot EMAROs (Educational Modular Autonomous Robot Osnabruck) positions itself with a unique combination of modularity, computing capabilities, sensor technologies, and software support. The robot provides two cameras for stereo vision, IMU, distance sensors, and a wide variety of additional sensors and communication interfaces. An important design goal was not only to focus on robotics but also on computer engineering education. Therefore, despite its small size with a diameter of about 10 cm, various computing nodes can be integrated, ranging from embedded CPUs and GPUs to reconfigurable hardware (FPGAs) and dedicated accelerators for machine learning. Using the ROS2 environment, students can focus on algorithm development as well as on resource-efficient implementations, comparing the different computing platforms.

ABSTRACT. Formulating research questions can pose a challenge for students in higher edu-cation, particularly in interdisciplinary settings where students and supervisors need to engage in dialogues across different scientific backgrounds. This study investigates the potential of integrating Large Language Models (LLMs) with social robotics to facilitate this process. Using a humanoid robot Furhat pow-ered by an LLM, students received interactive guidance in formulating research topics and questions. The system combines verbal interaction through the robot with a visual feedback interface, ensuring an engaging and dynamic learning experience. A mixed-methods evaluation with 47 university students examined feasibility, effectiveness, and user experience. Data from pre- and post-interaction questionnaires, video recordings, and semi-structured interviews suggest that the system enhances engagement, fosters curiosity, and supports structured academic exploration. Statistical analysis revealed strong correlations between information gain, topic engagement, and system-induced curiosity, highlighting the system’s effectiveness in stimulating deeper thinking about re-search topics. Furthermore, qualitative feedback indicated that students appreci-ated the interactive and adaptive nature of the robot’s responses, which helped them refine their research ideas in a structured manner. The findings demon-strate the potential of AI-driven tutoring in higher education, showing that com-bining humanoid robots with LLMs can create an effective and engaging re-search support tool. This study provides valuable insights for the further devel-opment of AI-assisted academic guidance and highlights future research direc-tions to optimize human-robot interaction in educational contexts.

ABSTRACT. The field of robotics education has seen significant growth, prompting researchers to explore its pedagogical implications through various theoretical frameworks. Traditionally, constructivism and constructionism have dominated discussions, emphasizing cognitive development through experiences with robotics. However, these frameworks primarily focus on human-centered learning, overlooking the agency of nonhuman, material entities. This paper examines the limitations of cognitive approaches and introduces New Materialism as an alternative framework for understanding robotics education. Drawing on Karen Barad’s concept of agential realism, it is suggested that knowledge in robotics settings emerges through material-discursive experiences between students, robots, and their environments. Drawing on observations of students engaged in robotics work, this paper highlights the pedagogical significance of material agency in robotics learning spaces. By shifting from representationalism to performativity, new materialism offers a more holistic approach that recognizes the entanglement of human and nonhuman actors in the co-creation of knowledge.

ABSTRACT. This short paper discusses the challenges and solutions related to teaching ROS 2 in an educational setting. We present "RoboEdu," a remotely accessible, containerized ROS 2 learning platform that runs on a virtualized Linux server with GPU acceleration. RoboEdu allows students to access a fully configured ROS 2 environment via a web browser, eliminating the need for complex local installations. It uses Docker containers, noVNC for remote access, and supports simulations in Gazebo and rviz, demonstrating the potential of cloud-based solutions in robotics education.

ABSTRACT. Using a small set of ordinary mobile computer devices together with modern legged robots, we build a wireless local area network for robot-assisted teaching in classrooms. All data is kept within the network, so that no sensitive communication is shared with any third party.

We employ a webcam application to be processed in OpenCV, a capable large language model supported with context knowledge, assisted with current information sources like date and time, and a real-time object detection and segmentation framework put together to build a common Python application that enables students to interrogate the robot about its general and problem-specific knowledge including the current spatial and temporal information of learning objects for teaching. Through the Web Real-Time communication interface, it is possible to instruct the robot to navigate through the classroom and perform certain tasks.

This lightweight brownfield automation setup proves versatile for robot-assisted interactive teaching.

ABSTRACT. This paper presents findings from a European survey of 849 teachers in Portugal, Poland, Croatia, and Germany, conducted within the "MyRobot MyLearnMate" project. The survey explored teachers' experiences with robots in education, identifying obstacles, motivations, and training needs. Insights from the survey were used to design a teacher training program, following the Design Thinking methodology. We describe the blueprint of the training program with its key modules. The program focuses on the use of the NAO robot as a teaching assistant in schools and will provide teachers with knowledge and good practice examples on how robots such as NAO can be used to innovate teaching and foster inclusive, engaging learning including a wide range of subjects such as mathematics, languages, and computer science.