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
- Donatien YETO
- Anna Baj-Rogowska
Topics
- LLM-Assisted Data Annotation
- Self-Regulated Learning
- Mistral AI - Batch API
- SQL
- Statistical Analysis
- Learning Analytics
- Stratified Sampling