Designing an AI Elective to Encourage Undergraduate Research

This paper describes the design and execution of a roboticsthemed AI elective at a small liberal arts institution. An important goal of the course is to spark and nurture students’ interest in pursuing related research while still undergraduates. To this end the curriculum turns the usual structure of a survey course on its head, pushing many fundamental topics later in the term so that students receive an early, thorough exposure to an important, recent algorithm known as Monte Carlo Localization (MCL). By starting with MCL, the de facto standard on cutting-edge mobile platforms, students have a touchstone from which to base novel projects and the time to do so. This work relates both the positive and negative experiences we have had with this approach.