Systematically Thinking about the Complexity of Code Structuring Exercises at Introductory Level

TL;DR

This paper introduces a framework for assessing and teaching the complexity of code structuring exercises in introductory programming, emphasizing decomposition and abstraction to enhance computational thinking skills.

Contribution

It presents a systematic framework with three complexity dimensions for designing and analyzing code structuring tasks, supported by example tasks and an interactive tool.

Findings

Framework effectively categorizes task complexity levels

Supports development of educational tasks for code abstraction skills

Provides tools for generating and exploring code structuring problems

Abstract

Decomposition and abstraction is an essential component of computational thinking, yet it is not always emphasized in introductory programming courses. In addition, as generative AI further reduces the focus on syntax and increases the importance of higher-level code reasoning, there is renewed opportunity to teach DA explicitly. In this paper, we introduce a framework for systematically assessing the complexity of code structuring tasks, where students must identify and separate meaningful abstractions within existing, unstructured code. The framework defines three dimensions of task complexity, each with multiple levels: repetition, code pattern, and data dependency. To support practical use, we provide example tasks mapped to these levels and offer an interactive tool for generating and exploring DA problems. The framework is designed to support the development of educational tasks that build students' skills with DA in the procedural paradigm.