Since the emergence of GPT-3, Large Language Models (LLMs) have caught the eyes of researchers, practitioners, and educators in the field of software engineering. However, there has been relatively little investigation regarding the performance of LLMs in assisting with requirements analysis and UML modeling. This paper explores how LLMs can assist novice analysts in creating three types of typical UML models: use case models, class diagrams, and sequence diagrams. For this purpose, we designed the modeling tasks of these three UML models for 45 undergraduate students who participated in a requirements modeling course, with the help of LLMs. By analyzing their project reports, we found that LLMs can assist undergraduate students as notice analysts in UML modeling tasks, but LLMs also have shortcomings and limitations.

翻译：自GPT-3问世以来，大型语言模型（LLMs）已引起软件工程领域研究人员、从业者和教育者的广泛关注。然而，关于LLMs在辅助需求分析与UML建模方面表现的研究仍相对匮乏。本文探索了LLMs如何辅助新手分析师创建三类典型UML模型：用例模型、类图和序列图。为此，我们为45名参与需求建模课程的本科生设计了这三类UML模型的建模任务，并借助LLMs开展实践。通过分析其项目报告，我们发现LLMs能够辅助作为新手分析师的本科生完成UML建模任务，但LLMs仍存在不足与局限性。