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

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.

Figures (4)

• Figure 1: Scaffold example taxonomy.
• Figure 2: Example from the pilot study: target task (left) and its scaffold example (right), designed to discourage direct copy-and-paste and support analogical reasoning.
• Figure 3: Student ratings of scaffold examples.
• Figure 4: CodeExemplar interface.