The Performance Evaluation of Employees Engaging in Teaching Positions in Private Higher Learning Institution Based on BPNN Model

摘要

The performance evaluation of employees is of great significance for the development of private higher learning institution (PHLI) and the judgment of the work effectiveness, so establishing a scientific, reasonable and fair evaluation system is essential. The performance evaluation of PHLI is influenced by various factors. Relationships among these factors are complex, some are nonlinear, even some are random and fuzzy. It is difficult to explain their internal relationships with traditional method. This research combines Back-Propagation neural network to establish a three-layer BP neural network model, which took 30 employees engaging in teaching positions as samples and made predictions in accordance with five factors, including educate teaching, scientific research, educational administration, social work, and attendance & ethics. The results show that BP neural network model has strong nonlinear approximation ability, could truly reflects the nonlinear relationships between performance levels and main controlling factors, with small error between predicted values and the measured values, relative error lower than 5%.