The AL Goldberg machine: a virtual environment for engaging learners in algorithmic practices

Abstract

Familiarity with the construction, test, and refinement of computational algorithms is of critical importance to many disciplines in the 21st century. We introduce a novel learning environment that lowers the threshold to participation in algorithmic practices including using functions to transform input, using conditionals to selectively transform or manipulate input, creating simple and complex algorithms, and testing and debugging algorithms to iteratively improve them. Our learning environment leverages VR technology and principles of embodied cognition that prioritize "hands in" learning. Instead of creating algorithms through traditional computational programming (which often renders the structure and components of an algorithm opaque), students using our technology build "concrete algorithms" in the form of a virtual Rube Goldberg-type machine that makes the algorithm's structure, components, and functioning visible.