Date
Publisher
arXiv
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.
Study at a glance
- Question: How do beginners and experts perceive and use AI tools to learn and practice agent-based modeling?
- Setting and data: 30 participants from global academia, industry, and graduate schools
- Method: Interviews with 30 participants
Why it matters
Large Language Models have the potential to fundamentally change computer programming. While agent-based modeling has become ubiquitous in natural and social sciences and education, no prior studies have explored the potential of LLMs to assist it.
Key findings
- Among 30 participants from academia, industry, and graduate schools, programming experts reported more benefits from AI assistants than novices and adopted them more readily.
- Experts and novices differed significantly in their AI behaviors and perceptions, with a knowledge gap identified as a possible reason experts benefited more.
- Participants identified guidance, personalization, and system integration as major needs for AI interfaces supporting agent-based modeling programming.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who age?
Why use AI?
Study design
