Interactive Graph Algorithm Learning with JSXGraph and Moodle STACK

Frauke Sprengel

Department of Computer Science, Faculty IV - Business and Computer Science, Hannover University of Applied Sciences and Arts, Hannover, Germany

frauke.sprengel@hs-hannover.de

Abstract

Teaching fundamental graph algorithms such as Kruskal’s minimum spanning tree, Dijkstra’s shortest path, and depth-first/breadth-first search often relies on static materials that do not adequately convey the interactive nature of algorithmic decision-making. This presentation describes a framework for creating interactive graph algorithm exercises using JSXGraph integrated with Moodle’s STACK question type system.

The implementation generates randomized graph instances with configurable parameters: vertex count, edge density, and weights. JSXGraph is used to visualize the graph, for mouse interactions, hover effects, and undo functionality. Students interact with the graph visualization by clicking edges in the correct algorithmic sequence and receive visual feedback through color-coded selections and progression numbering.

The assessment system validates both the resulting spanning tree structure and the order of edge selections. Both of them are not unique, allowing for multiple correct solutions. The randomized questions allow repeated practice while preventing solution sharing.

This is joint work with Shahab Abtahi, B.Sc.