Teaching Algorithms in 2026
The author reflects on teaching algorithms in 2026, noting how students rely on AI tools for code generation but struggle with algorithmic reasoning and analysis. The post emphasizes the need to focus education on conceptual understanding and problem-solving rather than implementation details.
Background
This is a blog post by Eugene Wallingford, a computer science professor at the University of Northern Iowa, reflecting on how he teaches algorithms in 2026 — a near-future setting that implies changes in the field. The post likely addresses how AI coding assistants (like ChatGPT or GitHub Copilot) and the increasing automation of software development affect what students need to learn about algorithms. Key context: traditional algorithms courses focus on designing, analyzing (e.g., Big-O complexity), and implementing standard algorithms from scratch. By 2026, the question becomes: if AI can write and optimize code, what is the enduring value of teaching algorithms? The post probably argues that conceptual understanding, problem-solving mindset, and ability to evaluate AI-generated solutions remain critical, even if manual coding skills become less central.