Ziyi Yuan, Aoxue Zhao, Xia Li
With the advancement of digital education in colleges and universities, libraries are transforming into "comprehensive academic services", but "unified" services are difficult to adapt to the differentiated needs of students. Existing user profiling research mostly focuses on external behavioral data and ignores intrinsic motivation and its relationship with learning outcomes, resulting in a lack of pertinence in service optimization. This study targeted college students and collected 310 valid questionnaires. Through reliability and validity analysis, it verified the motivation evaluation system including four major dimensions: academic, environment, social interaction, and atmosphere/anxiety. Then, K-means clustering (K=3) was used to divide three types of users: "full motivation-driven academic masters", "academic and social strong participants" and "low motivation wanderers". Through variance and chi-square tests, it was found that the learning efficiency and academic performance of the first two categories were significantly better than those of the third category. There was no significant correlation between the regional preferences of the three categories, but they all favored electronic/general reading rooms. Finally, the study proposes a hierarchical service optimization strategy to provide empirical support for the "user-centered" transformation of libraries.
University Library; User Portrait; Motivation Dimension; K-Means Clustering; Service Optimization