A Language and System for Constructing and Presenting Low Fidelity Algorithm Visualizations

Abstract

Computer science educators have traditionally used algorithm visualization (AV) software to create graphical representations of algorithms that are later used as visual aids in lectures, or as the basis for interactive labs. Typically, such visualizations are high fidelity in the sense that (a) they depict the target algorithm for arbitrary input, and (b) they tend to have the polished look of textbook figures. In contrast, low fidelity visualizations illustrate the target algorithm for a few, carefully chosen input data sets, and tend to have a sketched, unpolished appearance. Drawing on the findings of ethnographic studies we conducted in a junior-level algorithms course, we motivate the use of low fidelity AV technology as the basis for an alternative learning paradigm in which students construct and present their own visualizations. To explore the design space of low fidelity AV technology, we present a prototype language and system derived from empirical studies in which students constructed and presented visualizations made out of simple art supplies. Our prototype language and system pioneer a novel technique for programming visualizations based on spatial relations, and a novel presentation interface that supports reverse execution and dynamic mark-up and modification