Multi-Index and Hierarchical Comprehensive Evaluation System for Training Quality of Science and Engineering Postgraduates

Abstract

It is essential to establish a multi-dimensional postgraduate quality evaluation system for student assessment and training. This study aimed to explore the construction of the multi-index and hierarchical comprehensive evaluation system for postgraduate training in science and engineering based on the Context, Input, Process, Product (CIPP) model using Analytic Hierarchy Process. It involved 756 postgraduates in physics and engineering who were randomly selected via the Internet. Data were collected from the questionnaire about postgraduates' basic information. After collection, Factor Analysis was used to verify the rationality of the design of second-level and third-level indicators, and adjust the corresponding weights. On this basis, Cluster Analysis was used to classify the training quality of the postgraduates based on their scores on academic ability, basic quality, and social ability indicators. The results revealed that the index system includes 4 first-level indicators,12 second-level indicators and 36 third-level indicators, and different weights being assigned to the indicators according to their influence on the training quality of postgraduates in science and engineering. This study also provides some reference for the quality of science and engineering postgraduate training in Chinese universities by proposing relevant measures, which could be interesting also for international audience. Keywords: Analytic Hierarchy Process, CIPP model, multivariate statistical analysis, postgraduate quality training