4 papers · 1 filter
To Tab or Not to Tab: Measuring Critical Engagement in AI Code Completion Tools Using Behavioral Signals and Attention Checks
Jessica Hutchison, Ian Tyler Applebaum, Kenneth Angelikas +6
AI code completion tools, such as Github Copilot, provide students with code suggestions to help them write programs. However, recent qualitative studies suggest that students fail…
Exploring the Value of Diverse LLM Explanations in Introductory Programming
Seth Bernstein, Paul Denny, Juho Leinonen +4
Large Language Models (LLMs) have shown the potential to generate code explanations that surpass those of peers in quality, offering promising opportunities for computer science ed…
Probing the Unknown: Exploring Student Interactions with Probeable Problems at Scale in Introductory Programming
Paul Denny, Viraj Kumar, Stephen MacNeil +2
Introductory programming courses often rely on small code-writing exercises that have clearly specified problem statements. This limits opportunities for students to practice how t…
Exploring Student Behaviors and Motivations using AI TAs with Optional Guardrails
Amanpreet Kapoor, Marc Diaz, Stephen MacNeil +2
AI-powered chatbots and digital teaching assistants (AI TAs) are gaining popularity in programming education, offering students timely and personalized feedback. Despite their pote…