This study aims to explore the construction of an evaluation index system for undergraduate engineering majors based on the Context, Input, Process, Product (CIPP) model under the Outcome-based Education (OBE) approach employing the Delphi method and Analytic Hierarchy Process. The trial of the evaluation index system involved 986 entrepreneurs, engineering technicians and teachers majoring in the field of electronic-information, who were recruited and selected for participation on the Internet. Data were collected from the consultation questionnaire developed in accordance with the indicators at all levels. Subsequently, Principal Component Analysis was used to verify the rationality of the indicator design, and the corresponding weights were adjusted. The results found that the index system includes 4 first-level, 11 second-level, and 42 third-level indicators, and different weights are assigned according to the extent of influence each of these indicators has on the quality of undergraduate training. Furthermore, the evaluation system can reflect the actual relationship among the indicators to some extent, which provides reference for the quality evaluation of engineering education.

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