Comprehensive quality assessment of “Five-Educations” talents based on AHP and BP neural network

Abstract

This study aims to provide a comprehensive evaluation model for higher education’s “Five-Educations” using the Analytic Hierarchy Process (AHP) method and Back Propagation (BP) neural network. First, a five-dimension evaluation index system (morality, intelligence, sports, aesthetics, and labor) is established through expert consultation and literature analysis. Then, the AHP method determines the weight of each index, ensuring objective and scientific evaluation. Next, we introduce the BP neural network model for efficient evaluation of students’ comprehensive quality through self-learning and adaptive mechanisms. Empirical analysis shows the model’s computational error is within 2.25%, demonstrating excellent accuracy and wide applicability. This research introduces an innovative comprehensive evaluation model for “Five-Education” talent development based on the Analytic Hierarchy Process (AHP). The model quantitatively assesses the comprehensive quality capabilities of talent. Additionally, the introduction of this model serves as a valuable reference for future research in the field of educational assessment.