Strategies for basing the CS theory course on non-decision problems

TL;DR

This paper advocates for teaching computational and complexity theory to undergraduates using non-decision problems, such as optimization and search problems, instead of the traditional decision problem paradigm.

Contribution

It introduces technical definitions and pedagogical strategies for effectively teaching the theory course centered on non-decision problems.

Findings

Non-decision problems are more accessible for undergraduates.

Pedagogical strategies improve understanding of complexity concepts.

Evidence supports using non-decision problems in introductory courses.

Abstract

Computational and complexity theory are core components of the computer science curriculum, and in the vast majority of cases are taught using decision problems as the main paradigm. For experienced practitioners, decision problems are the best tool. But for undergraduates encountering the material for the first time, we present evidence that non-decision problems (such as optimization problems and search problems) are preferable. In addition, we describe technical definitions and pedagogical strategies that have been used successfully for teaching the theory course using non-decision problems as the central concept.