Reducing Instructor Workload in an Introductory Robotics Course via Computational Design

Abstract

Physical computing and building robots has important benefits for novice engineers and computer scientists. However, lab time and hardware debugging comes with a high cost of instructor time and effort. To reduce this workload, we implemented a computational design tool that simplifies printed circuit board (PCB) design and manufacture, assembly, and programming. We pilot tested our computational design tool in a one-unit introductory physical computing course for 196 CS1 students. The students designed, assembled, and programmed a custom robot with minimal instructor assistance. The robots are Arduino-based and each included a student designed PCB. The students assembled the robots from off-the-shelf electronic components according to automatically generated assembly instructions. Students programmed their robots using simple APIs that were automatically generated and customized for each unique robot. A minimum of two quarters after the completion of the course, grade point average (GPA) for the students who completed the course, was found to be 0.15 higher than a comparison group of similar student (n = 498, p<0.05). We present a detailed description of our computational design tool and course curriculum, identify challenges encountered by the students and instructional staff, make recommendations to increase student achievement, and address the scalability of the course.