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Research

Do Large Language Models Change How Developers Seek Help? A Trace-Based Study of Stack Overflow Behavior

Paper · Published · ISD 2026

Led and initiated a research project in collaboration with Anna Baj-Rogowska investigating the impact of Large Language Models (LLMs) on observable problem-solving behaviors in technical online communities. Defined the scientific research question, designed the methodological framework, formulated the research hypotheses, and structured the large-scale statistical analysis using Stack Overflow data (2019–2025) to study changes in self-regulated learning behaviors before and after the rise of LLMs. The paper was accepted at ISD 2026, where I presented our work in Prague in September.

Authors

  1. Donatien YETO
  2. Anna Baj-Rogowska

Topics

  • LLM-Assisted Data Annotation
  • Self-Regulated Learning
  • Mistral AI - Batch API
  • SQL
  • Statistical Analysis
  • Learning Analytics
  • Stratified Sampling