User Misconceptions of LLM-Based Conversational Programming Assistants
cs.HC, cs.AI
Submitted: 2025-10-29
Updated: 2026-10-05
Code: https://github.com/elleobrien/wildchat-misconceptionsreplication
Terminology
Sources
- Guidelines for Empirical Studies in Software Engineering involving Large Language Models
- Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
- Evaluating Large Language Models Trained on Code
- GenAI Is No Silver Bullet for Qualitative Research in Software Engineering
- Vibe Coding in Practice: Motivations, Challenges, and a Future Outlook -- a Grey Literature Review
- Adopt not equal to Adapt: Longitudinal Analyses of LLM Conversations in the Wild
- GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
- Good Vibrations? A Qualitative Study of Co-Creation, Communication, Flow, and Trust in Vibe Coding
- What is it like to program with artificial intelligence?
- Towards Understanding Sycophancy in Language Models
- Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Study
- Programming by Chat: A Large-Scale Behavioral Analysis of 11,579 Real-World AI-Assisted IDE Sessions
- How Developers Interact with AI: A Taxonomy of Human-AI Collaboration in Software Engineering
- Language Models Learn to Mislead Humans via RLHF
- WildChat: 1M ChatGPT Interaction Logs in the Wild
- LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset
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