AI-Enhanced Socratic Method in Computer Science Education: An Implementation Study of Traditional and AI-Guided Learning Approaches

This study examines the implementation of an AI-Enhanced Socratic teaching method in AP Computer Science Principles education. Through a controlled comparison with 162 high school students across six class periods, this research documents the application of artificial intelligence as a guided inquiry tool combined with mock test benchmarks. Analysis of midterm and final assessment data reveals that the AI-Enhanced method effectively maintained student performance levels compared to traditional instruction when controlling for baseline differences. The method's key innovation lies in its structured implementation framework that enables guided exploration while preventing concept drift through built-in conceptual anchoring mechanisms.Beyond measurable outcomes, this approach also frees teachers from redundant questioning. This extra time allows educators to build stronger rapport with their students—a benefit that often transcends content mastery. After all, students may not remember every detail of what was taught, but they will never forget that they were made to feel that they mattered. This research contributes evidence for effective AI integration in computer science education and provides a replicable framework for educators seeking to incorporate AI tools within existing curricula.