Computational Thinking Curriculum for Unmanned Aerial Systems

Abstract

Unmanned aerial systems (UAS) can explore common, vast and unsafe places at low cost. They could transform multiple sectors from photography to farming to city planning. However, the software underlying UAS is complex and requires multiple distinct programming skills, e.g., AI, machine learning and flight control. Few programmers encompass these skills, hampering software development and dampening the impact of UAS. We contend that early exposure to UAS software could help align workforce skills. However, early exposure requires curriculum that (1) captures the breadth of UAS software, (2) supports multiple levels of depth for diverse programming backgrounds and (3) fits within resource and institutional challenges. We propose a computational thinking framework. In our approach, lessons fit within 20-30 minute instructional blocks, making them usable in short workshop and extended classroom settings. UAV topics and computational thinking depth link lessons. Teachers can trade breadth for in-depth coding and vice versa. In early work, we presented an autonomous UAS to middle school students. Our 1 hour workshop focused on breadth and was received well.