From Prompts to Propositions: A Logic-Based Lens on Student-LLM Interactions
Ali Alfageeh, Sadegh AlMahdi Kazemi Zarkouei, Daye Nam, Daniel Prol, Matin Amoozadeh, Souti Chattopadhyay, James E. Prather, Paul C. Denny, Juho Leinonen, Michael L. Hilton, Sruti Srinivasa Ragavan, Mohammad Amin Alipour · 2025
Background and Context. The increasing integration of large language models (LLMs) in computing education presents an emerging challenge in understanding how students use LLMs and craft prompts to solve computational tasks. Prior research has used both qualitative and quantitative methods to analyze prompting behavior, but these approaches lack scalability or fail to effectively capture the semantic evolution of prompts.