Curious Coders or Shortcut Seekers? Patterns of AI Use in High School Computer Science Problem-Solving

• In Event: Bridging the AI Literacy Gap: Systems-Level Approaches to K-12 CS Education

Abstract

This study explores how 72 high-school students in computer science programs use AI tools for problem-solving in their computer science studies. Using both quantitative and qualitative data, the research reveals that students mainly engage with AI during coding and execution stages (e.g., fixing syntax errors, testing code), while relying on their own thinking during earlier planning phases like algorithm design. Common motivations for AI use include curiosity and saving time. However, students also reported challenges, such as mistakes and content misalignment with their curriculum. These findings emphasize the need to develop AI literacy that supports critical and phase-appropriate use of AI, helping students understand not only how to use AI tools, but when and why to use them in computer science.

Authors

• Mor Friebroon-Yesharim, Holon Institute of Technology

• Rinat B. Rosenberg-Kima, Technion Israel Institute of Technology