Learning Agent-based Modeling with LLM Companions: Experiences of Novices and Experts Using ChatGPT NetLogo Chat
CoRR(2024)
摘要
Large Language Models (LLMs) have the potential to fundamentally change the
way people engage in computer programming. Agent-based modeling (ABM) has
become ubiquitous in natural and social sciences and education, yet no prior
studies have explored the potential of LLMs to assist it. We designed NetLogo
Chat to support the learning and practice of NetLogo, a programming language
for ABM. To understand how users perceive, use, and need LLM-based interfaces,
we interviewed 30 participants from global academia, industry, and graduate
schools. Experts reported more perceived benefits than novices and were more
inclined to adopt LLMs in their workflow. We found significant differences
between experts and novices in their perceptions, behaviors, and needs for
human-AI collaboration. We surfaced a knowledge gap between experts and novices
as a possible reason for the benefit gap. We identified guidance,
personalization, and integration as major needs for LLM-based interfaces to
support the programming of ABM.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要