Visual algorithm simulation exercises with authentic data sets

Abstract

Learning data structures and algorithms requires dealing with abstractions such as stack, queue, trees, and graphs. Interactive algorithm visualizations have been used to aid learning abstract concepts and to make it more interesting. In addition to making these visualizations interactive, utilization of real life data is a good way to motivate students. In this paper, we introduce a web mashup for a student-centered approach to learn graph algorithms. The mashup is built on top of Google Maps and visualizes realistic semantic data fetched from DBPedia. The outcome is a visualization of a graph on a map where the nodes are authentic locations such as Buildings in Tokyo, and the weighted edges denote the distances between locations. The students simulate graph algorithms such as Dijkstra's shortest-path algorithm by clicking nodes or edges on the graphs, thus better engaging with the visualization than in case of abstract data often provided in textbooks. In this paper, we report on our first experiences with students using these exercises. Comments from students show that they value exercises utilizing authentic data as they concretize the visualizations. We conclude that mashups are a feasible way to develop new educational tools rapidly.