Abstract:

Abstract concepts in computer science — spanning polynomial algorithms, computational complexity, and emerging areas such as quantum computing — are notoriously difficult for students to grasp through static textbook representations alone. This paper presents Redux, an open, web-based interactive visualization platform developed at Idaho State University to address this challenge through dynamic, hands-on exploration of a broad range of computational problems and algorithms.

Redux enables users to select from a growing library of over 34 problems and algorithm visualizations — spanning polynomial, NP-complete, quantum, and other complexity classes — and interact with them through several key pedagogical features. Step-by-step algorithm visualization allows students to walk through the execution of an algorithm at their own pace, building intuition through direct observation. Additional features include gadget highlighting and solution visualization, giving students multiple lenses through which to explore and understand computational problems.

A core design priority of Redux is extensibility. The platform provides a downloadable backend API template and reusable frontend templates for common structures such as graphs, sets, and Boolean satisfiability formulas, enabling both instructors and students to contribute new visualizations with minimal friction. All visualizations are fully dynamic, supporting arbitrary problem inputs rather than fixed examples. Redux is open source and freely accessible through our website, making it a practical open educational resource for institutions worldwide.

Formal user studies were conducted to evaluate Redux's effectiveness, with results suggesting meaningful improvements in student comprehension of abstract algorithmic concepts. Redux is designed to serve dual audiences: instructors seeking classroom-ready tools for teaching computational theory, and students who wish to deepen their understanding or actively contribute to an open educational resource. We discuss the platform's architecture, pedagogical design decisions, and directions for future development.

Keywords:

Algorithm visualization, computer science education, computational complexity, open educational resources, technology-enhanced learning, interactive learning, STEM education.