Performance Appraisal and Automatic Scoring System for College Counselors Based on Kmeans Clustering

• Published in: Mathematical problems in engineering Vol. 2022; pp. 1 - 12
• Main Authors: Wang, Zhichao, Tian, Qing
• Format: Journal Article
• Language: English
• Published: New York Hindawi 20.09.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Analytic hierarchy process; Clustering; College students; Engineering; Higher education; Ideology; Learning; Level indicators; Methods; Optimization; Optimization algorithms; Performance appraisal; Population; Velocity
• ISSN: 1024-123X; 1026-7077; 1563-5147; 1563-5147
• DOI: 10.1155/2022/4167842

The optimal solution is output as the result to the Kmeans algorithm as the initial clustering center, and the proposed linear distance model is used to complete the clustering. Combined with the theory of target management, focusing on the job requirements and responsibilities of the counselors, the counselors’ performance appraisal objectives were determined, the counselor performance appraisal system was established, and the first-level indicators and the second-level indicators and their weights were determined by using Del Illegal and Analytic Hierarchy Process (AHP). This paper constructs a performance appraisal system for local undergraduate college counselors based on management by objectives, and has carried out a pilot implementation in a college. The behavior anchoring method is used to determine the scoring standards of each index, which solves the problem of inconsistent scoring standards for different assessment subjects in the past. In the assessment results, the assessment results of the three dimensions are independently evaluated by category. This paper has a certain practical significance and reference value for the optimization research of the counselor’s performance appraisal scheme under the background of institutional reform in a university.