Enhancing AI Learning through Algorithm Visualization with Pseudocode Tracing: An Experience Report

Abstract

Algorithm visualization tools have traditionally been employed in CS2 courses to support student learning of data structures and sorting algorithms. Building on this approach, we developed a custom visualization tool AI-SearchViz specifically designed for AI education, targeting uninformed, informed, and pathfinding search algorithms, topics that students often find abstract and difficult to grasp. Our tool combines dynamic visualizations with step-by-step pseudocode tracing to enhance clarity and interactivity. It was used by 406 computing students at our institution, and its effectiveness was evaluated through pre- and post-activity surveys. Findings show that the tool significantly enhanced students’ conceptual understanding, engagement, and confidence in applying AI search algorithms. This experience report contributes (a) an open-access visualization tool for AI algorithms that can be adopted by computing educators, and (b) a summary of the tool’s design and evaluation outcomes, offering practical insights for integrating visual and active learning strategies into AI instruction.