Volume 3 · Issue 3 (2026)
Analysis of Teachers' Scientific Research Behavior Types Based on K-means Clustering: A Case Study of the School of Information Engineering Hainan Vocational University of Science and Technology
Darun Yang, Fan Yang
Hainan Vocational University of Science and Technology, Haikou, Hainan, China
Abstract: The pattern of teachers' scientific research behavior is of fundamental significance for university research management. Based on the data of scientific research projects at or above the municipal level undertaken by teachers from the School of Information Engineering, Hainan Vocational University of Science and Technology, between 2019 and 2025, this study employs the K-means clustering algorithm to classify the research behaviors of 40 teachers. By extracting seven dimensional features, including professional title rank, education background rank, total number of projects, and the quantities of four project categories, the data were standardized and clustered. The optimal number of clusters was determined to be K=5 using the Elbow Method and Silhouette Coefficient. Consequently, five types of teacher groups were identified: Teaching-Research Balanced Type, Novice Explorer Type, Local Service Type, Industry-Education Integration Type, and Research Leader Type. Significant differences were observed among these groups in terms of project quantity, project type preference, professional title, and education background structure, reflecting the diverse characteristics of teachers' research behaviors in vocational undergraduate universities. Based on the clustering results, differentiated support strategies are proposed, providing an empirical reference for research management in similar institutions.
Keywords: K-means clustering; Teachers' scientific research behavior; Vocational undergraduate; Research management
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