Dynamic Evaluation and Incentive Mechanism Framework for Postgraduates' Academic Performance Stability

Abstract

Against the backdrop of the Party and the state's emphasis on promoting educational evaluation reform and implementing process-based evaluation, this paper combines the process optimization concept of Industrial Engineering (IE) and data-driven thinking to construct a dynamic evaluation system covering the entire student learning process. In response to the shortcomings of the traditional "30/70" rigid scoring system, such as insufficient discrimination, inability to dynamically assess students' learning stability, and difficulty in guiding learning enthusiasm through scientific rewards and punishments, this paper designs a stability quantification method based on indicators such as average scores and trend slopes, and formulates segmented incentive and punishment strategies. This model can effectively enhance the discrimination of high-score segments while protecting the learning enthusiasm of underperforming students, providing a feasible approach for the digital and scientific reform of educational evaluation.