  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 novice
analysts in UML modeling tasks, but LLMs also have shortcomings and limitations
that should be considered when using them.
