Teaching Well-Structured Code: A Literature Review of Instructional Approaches

TL;DR

This literature review examines various instructional approaches for teaching code structure to software engineering students, highlighting existing methods, their effectiveness, and gaps in evaluation to improve future educational strategies.

Contribution

It categorizes 53 studies on code structure instruction, analyzing their strategies, tools, and curriculum integration, and calls for more effectiveness research.

Findings

Over 40% of studies lacked evaluation.

Interventions improved student performance in some cases.

Tools like code analyzers are commonly used but hard to integrate.

Abstract

Teaching the software engineers of the future to write high-quality code with good style and structure is important. This systematic literature review identifies existing instructional approaches, their objectives, and the strategies used for measuring their effectiveness. Building on an existing mapping study of code quality in education, we identified 53 papers on code structure instruction. We classified these studies into three categories: (1) studies focused on developing or evaluating automated tools and their usage (e.g., code analyzers, tutors, and refactoring tools), (2) studies discussing other instructional materials, such as learning resources (e.g., refactoring lessons and activities), rubrics, and catalogs of violations, and (3) studies discussing how to integrate code structure into the curriculum through a holistic approach to course design to support code quality. While most approaches use analyzers that point students to problems in their code, incorporating these tools into classrooms is not straightforward. Combined with further research on code structure instruction in the classroom, we call for more studies on effectiveness. Over 40% of instructional studies had no evaluation. Many studies show promise for their interventions by demonstrating improvement in student performance (e.g., reduced violations in student code when using the intervention compared with code that was written without access to the intervention). These interventions warrant further investigation on learning, to see how students apply their knowledge after the instructional supports are removed.