Domain models in software engineering--often represented as class diagrams--depict relevant classes in a given problem domain along with necessary relationships among those classes. These models are important because they establish links between the requirements of a given system under development and the subsequent phases of the systems development life cycle. Although the teaching of basic concepts related to domain modeling takes only about 1 or 2 hours, proper application of these concepts to a given problem situation is difficult for students studying software engineering. Due to their insufficient domain knowledge of the problem situation and modeling experience, they often produce domain models that may not adequately represent necessary elements as part of the domain models. Analysis patterns can help them by encoding expert knowledge and offering guidance in the modeling process. This article reports the findings from a controlled experiment conducted to study the effects of collaboration patterns on the domain modeling process by students. Specifically, the study investigated the differences in students' perceptions of the ease of the domain modeling process and quality of models produced, perceived difficulties, and how collaboration patterns help address domain modeling difficulties and the quality of domain models produced. Findings from this experimental study involving students from a software engineering course indicate that although there is no significant difference in subjects' perceptions between the control and treatment groups, the subjects from the treatment group produced better-quality domain models. Additionally, the qualitative analysis of the feedback collected from the subjects from the control and treatment groups reveals that that having knowledge of patterns is beneficial, as it addresses the difficulties in domain modeling.