Speed Thrills: Visceral Demonstrations That Get Students Excited About Efficient Algorithms

2026-04-10

AI Summary

This work aims to enhance students’ interest in and understanding of efficient algorithms in data structures and algorithms courses. By designing progressive optimization sequences for two canonical problems, the approach reduces execution time from days or even years to mere seconds—enabling real-time demonstrations on standard laptops and vividly illustrating the dramatic impact of algorithmic efficiency. The project introduces the concept of “algorithmic thrill,” leveraging stark runtime contrasts to create a powerful cognitive impression that reinforces key pedagogical takeaways. Coupled with clear pseudocode and rigorous complexity analysis, this method effectively bridges theoretical concepts and practical implementation, significantly strengthening students’ appreciation of algorithmic efficiency and boosting their motivation to learn.

Technology Category

• Search and Optimization: Algorithm Configuration
• Machine Learning: Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content

Abstract

We address the problem of motivating students in Data Structures and Algorithms courses by presenting two simple problems that each have a series of improvements to a basic algorithm, leading to spectacular decreases in runtimes. Coining a new term, we refer to such sequences as being"thrills of algorithms". Seeing runtimes drop from an estimate of days (or even years) to just a few seconds has a visceral impact which conveys the importance of efficient algorithms in a way unlikely to be forgotten. The demonstrations are particularly compelling because they can be performed live in class on the lecturer's laptop. To assist staff teaching such courses we provide detailed pseudocode descriptions and complexity analyses for the various methods, and can supply implementations on request.

Problem

• student motivation
• efficient algorithms
• algorithm education
• visceral demonstrations
• Data Structures and Algorithms courses

Innovation

• thrills of algorithms
• algorithm efficiency
• visceral demonstration
• runtime reduction
• educational innovation