ABSTRACT. Simulation tools are often used in robotics education to transfer theoretical knowledge into practical experience. The correlation between practical and real-world experience depends on the quality of the simulation environment and its ability to serve as a replacement for the real world. In this study an environment for UAV education is proposed, where the transfer of theoretical knowledge into practical experience is achieved through the implementation of both simulation and real UAV deployment. Initially, this environment allows students to develop their applications in the simulation. Subsequently, in the later stages, they are able to easily deploy them into the educational UAV and test the solution in the drone laboratory. Compatibility between simulation and physical UAV is achieved by combining the appropriate components in both the simulation and physical UAV. The software technologies used include ROS, ArduPilot, and MavLink, while the hardware platform for the educational UAV was chosen as DroneCore.Suite by Airvolute s.r.o.. These technologies are not only suitable for the proposed environment but are also commonly used across the robotics field, which enhances relevant students competencies. Later in the article, an example assignment is presented and described how to use the environment for UAV education in a classroom setting.

ABSTRACT. This paper presents some feedback on a curriculum on robotics developed for Master’s level students at ESIEA, a graduate school of engineering in France. The main particularity of this curriculum is that it is composed of only three short modules (control and estimation, computer vision, ROS), with a small number of hours (18hrs each), but proposes hands-on experiments with drones to students. Experiments are done in the classrooms with low-cost drones as exercises integrated into the practical work sessions. The detail of the curriculum, the pedagogic approach, and examples of experiments proposed to the students are presented in this paper.

ABSTRACT. With an increased demand for roboticists in the labor market, there is a growing interest in acquiring skills in ROS (Robot Operating System), one of the more popular robotics software development platforms. Most freely available resources for learning ROS rely on simulation or assume that people have a robotics platform at their disposal. In this study we extended professional robotics to self-guided learning using physical hardware by creating a massive open online course (MOOC) for learning ROS. Course participants could log into a web lab and remotely control robots located in a university classroom without the need to install anything locally on their computers. During the 7-week course participants of varying ages and backgrounds learned about the necessary skills to use ROS on a Linux machine through receiving an authentic ROS developing experience. The participants’ weekly performance results and answers to a feedback questionnaire were subsequently analysed. The first iteration of this course was completed by 49 participants, with the biggest reason for dropping the course being lack of time. The course demonstrated the possibility of using a remote web lab to teach ROS. This paper summarizes our lessons learned.

ABSTRACT. This article presents an exercise framework for teaching robotics with Robot Operating System ROS. It is designed to teach the fundamental robotics principles in an interactive way, while using modern software tools that are commonly used in realworld practice. The exercises and assignments encourage students to implement the robotics theory into their own algorithms and test and compare them to ROS provided functionality, to better understand the development of robotic systems. This paper describes the framework in detail and explains the choice of ROS as the software tool for the framework. In the end, the results of an evaluation questionnaire are presented to assess the overall satisfaction and usefulness of the course.

ABSTRACT. The pandemic period enforced lecturers and students to face new challenges and search for alternatives to the standard presence educational process. This paper presents a simulator-based approach to teaching mobile robotics topics, such as localization, mapping, and navigation. The effectiveness of this approach is measured by various evaluations.

ABSTRACT. There are currently different robotic simulation programs for educational robotics activities. All of them aim to offer an entrance into the world of robots in an easy way and with fewer resources. How can it enhance these student learning? This paper will compare two free versions of robotic simulation programs, IDE HedgeHog and Thymio Suite. One system is a web-based simulation in a web browser and does not need an installation. The other is a program on the computer; therefore, a program is to download and install on the computer. Both have different program languages for different difficulty levels, like text-based or visual-based programming languages. 124 Students solved the different tasks with a simulation and responded to an online survey about their learned knowledge and usability. The result shows that both simulations are user-friendly and helpful for beginners. They are useful tools to engage students in educational robotics activities or test programme codes in a virtual environment before they were transferred to physical settings.

ABSTRACT. In this research paper we describe the activities designed for a 5 day engineering design workshop using an educational robotics tool called SmartMotors. SmartMotors are low cost solutions to teach elemen- tary and middle school students about robotics and Artificial Intelligence in under-resourced classrooms. In a few simple steps these motors can be trained by the users to run to various states corresponding to dif- ferent sensor inputs. We believe that the low cost and trainable aspects of SmartMotors will reduce barriers of entry for both teachers and stu- dents in introducing robotics in classrooms and increase student access to robotics and engineering. In the summer of 2022, we used one of our prototypes to run a usability study in a workshop with ten middle school students aged 12-15. The students participated in an hour-long engineer- ing design workshop for five days, and each day they received different prompts along with necessary scaffolding. The participating students had limited prior exposure to robotics and AI. By the end of the workshop, the students were able to train robots in group projects that reflected their individual interests. In this paper, we talk about the students’ jour- ney, starting with building simple projects and subsequently gaining the skills and confidence to showcase diverse and complex designs. We will then discuss the affordances of the tool and explore the opportunities and limitations of SmartMotors in an engineering design workshop.

ABSTRACT. As Artificial Intelligence (AI) is increasingly having an im- pact on education, a context for AI learning activities based on problem- solving STEAM challenges is created in this project. Having been focused on philosophy maker, students are initiated into coding and computer sciences, exploring its potential and combining robots, microcontrollers and artificial vision cameras. In that sense, students use of a variety of strategies that allow the camera to recognize a ball, a face, a color or a card and also they use Machine Learning by teaching the camera what to detect. The project not only engage students to build creative solutions but also it empowers them to start prototyping their own ideas keeping through exploration.

ABSTRACT. As artificial intelligence (AI) plays a more prominent role in our everyday lives, it becomes increasingly important to introduce basic AI concepts to K-12 students. To help do this, we combined physical robots and an augmented reality (AR) software to help students learn some of the fundamental concepts of reinforcement learning (RL). We chose RL because it is conceptually easy to understand but has received the least attention in previous research on teaching AI to K-12 students. We designed a series of activities in which students can design their own robots and train them with RL to finish a variety of tasks. We tested our platform with a pilot study conducted with 14 high school students in a rural city. Students' engagement and learning were assessed through a qualitative analysis of students' behavior and discussions. The result showed that students were able to understand both high-level AI concepts and specific RL terms through our activities. Also, our approach of combining virtual platforms and physical robots engaged students and inspired their curiosity to self-explore more about RL.

ABSTRACT. Based on new methods and algorithms to improve the detection of emotions from facial expressions by means of sophisticated software during certain situations, we explore if a virtual robotic animal appearance design with the role of a virtual instructor can affect such emotions in users. A total of 131 students from two secondary public schools in Bogota, Colombia, participated in this study. We used an established facial emotion recognition software called “FaceReader” to analyze data recorded during their class. The results showed that the virtual robot animal’s appearance could affect participants’ emotional facial expressions when it was a virtual instructor in this study. The study contributes to our understanding of the visual appearance of virtual animals related to emotional facial expressions and their future enforcement in relation to advances in artificial intelligence and educational robotics for accurate recognition of the emotions of users.