2023 ASEE Annual Conference & Exposition

The goal is to develop a new elective course for graduate and undergraduate computer science students in the ever-evolving area of robotics. The intention is to structure the course from inception to be:
· motivating including incentives
· inclusive with minimum prerequisites
· accessible to students of various socioeconomic backgrounds
· enabling diverse learners such as students with ADHD or anxiety

These intentions are important for robotics programming as many technical subjects merge to successfully implement software on robotic systems or simulators. This multitude of factors including understanding of robotics hardware, parallel processing, XML, Linux, ROS file structures, and programming makes for a learning experience with many frustrations along the path.

Traditional forms of motivation include fostering expectancies for future self, integrating with industry and academic professionals, and collaborative teamwork to help individuals. Novel forms of motivation include clawback incentives paired with fallback options to illustrate achieving course objectives. These forms of motivation and assessment were previously found to be enjoyable and fostering to students with different levels of course preparation and socioeconomic backgrounds.

Developing software that reads robotic sensors, processes gathered information, and writes to robotic actuators requires prerequisite knowledge of the basics of operating systems, programming, and robotic hardware. To include as many student populations as possible with robotics interests, this knowledge was not made a prerequisite. The only prerequisite knowledge required was a basic working knowledge of C++ (or potentially Python) programming and the ability to use Linux command line statements. The Robotic Operating System (ROS) enables this minimal prerequisite approach. ROS hardware abstraction along with the use of robotic simulators enables project progress while resolving hardware problems. ROS also has tools to playback and log information enabling more debugging approaches. Similarly, prior knowledge of parallel processing, XML, and ROS packages was not required. These topics were simplified, worked on gradually, and then developed, debugged, and demonstrated. The introduction of these topics was aided again by ROS especially the large open-source libraries for assembling software using existing software components. This also fostered an understanding of software reuse and fostered the development of more sophisticated or higher level robotic applications.

Diverse learners are accommodated through class structure. Clawback incentives rely on the assessment of student learning via a project demonstration, report, and project presentation. Clawback incentive is a contractual performance incentive researched by economist John A. List. The individual project is student selected. The topic is instructor approved for meeting the objectives of some novel software development and integration with existing libraries or packages. This alternative form of assessment enables diverse learners by removing the requirement of the traditional exam model and reduces anxiety by providing a fallback option to an exam if technical difficulties prevent project demonstration and presentation. The ability to customize the project choice supports a student's social, emotional, and intellectual interests. It welcomes their social identity and different perspectives, approaches, and interests.