LAUSR

Objective To deeply understand the role expectation of clinical teachers for nursing master's degree graduates and use the crowd portrait intelligent data analysis system to assist in enrollment. Methods Retrospective analysis was used to group nursing postgraduates and observe and statistically analyze the passing rate of basic course examination, subject achievement, graduation thesis, and graduation passing rate within three years. Results The passing rates of the observation indexes of the double compliance group, the compliance system group, the compliance teacher group, and the double noncompliance group decreased in turn. It can be said that the system design can provide effective suggestions for the enrollment of nursing postgraduates. If the enrollment is carried out according to the system suggestions, the overall level of postgraduates can be improved, and their role expectations can be met. Conclusion This paper was aimed at studying the advantages of using intelligent data systems to assist in enrollment, which can not only improve the overall level of nursing graduate students but also meet the role expectations of clinical teachers, systematically arrange practical teaching, and promote the development of relevant software systems.