CodeExemplar: Example-Based Scaffolding for Introductory Programming in the GenAI Era

TL;DR

CodeExemplar introduces an example-based scaffolding approach using GenAI to support introductory programming students by providing analogical, reasoning-pattern matching examples that reduce copying and promote understanding.

Contribution

It presents a novel taxonomy, design guidelines, and a prototype system for scaffolded code examples leveraging GenAI in educational settings.

Findings

Initial classroom pilot shows positive student engagement

Instructor interviews indicate usefulness for teaching

Prototype effectively matches reasoning patterns in code examples

Abstract

Generative AI (GenAI) can generate working code with minimal effort, creating a tension in introductory programming: students need timely help, yet direct solutions invite copying and can short-circuit reasoning. To address this, we propose example-based scaffolding, where GenAI provides scaffold examples that match a target task's underlying reasoning pattern but differ in contexts to support analogical transfer while reducing copying. We contribute a two-dimensional taxonomy, design guidelines, and CodeExemplar, a prototype integrated with auto-graded tasks, with initial formative feedback from a classroom pilot and instructor interviews.