人工智能驱动下的高校混合教学评价体系变革研究

Research on the Reform of the Evaluation System for Blended Teaching in Universities Driven by Artificial Intelligence

摘要: 在人工智能上升为国家新质生产力的背景下，高校混合教学评价体系面临“唯分数”惯性、数据利用不足、教师负荷过重和维度单一等现实困境。本文以技术可供性与政策支持为分析框架，梳理了2018~2026年国家层面从“数据驱动”到“AI赋能评价改革试点”的三阶段政策演进，并指出当前仍存在的四大短板：AI评价主体地位未确立、伦理规范缺失、复合脑能力指标空白、教师AI素养不足。针对上述问题，论文提出“政策优化 + AI-ESS系统架构”双轮驱动的改进路径：政策层面通过立法确权、伦理沙盒、财政常模与标准协同为改革护航；技术层面构建“全域感知–智能决策–人机共生”五层AI-ESS系统，实现评价的过程–结果耦合、差异个性化、三元协同、动态生成及复合脑能力多维评价。研究认为，人工智能不会取代评价，而将重塑“师–生–AI”评价共同体，未来需在认知数字孪生、量子隐私计算与生成式评价伦理等方向持续探索，以技术增强理性、以人文守护价值。

Abstract: Against the backdrop of artificial intelligence rising to become a national new quality productivity, the mixed teaching evaluation system in universities is facing practical challenges such as the inertia of “score only”, insufficient data utilization, heavy teacher load, and single dimension. This article takes technology availability and policy support as the analytical framework, and summarizes the three-stage policy evolution from “data-driven” to “AI-enabled evaluation reform pilot” at the national level from 2018 to 2026. It also points out four major shortcomings that still exist: the unclear status of AI evaluation subject, the lack of ethical norms, the blank of composite brain ability indicators, and the insufficient AI literacy of teachers. In response to the above issues, the paper proposes a dual wheel driven improvement path of “policy optimization + AI-ESS system architecture”: at the policy level, reform is escorted through legislative confirmation, ethical sandbox, fiscal norm and standard coordination; at the technical level, a five layer AI-ESS system consisting of “global perception, intelligent decision-making, human-machine symbiosis” will be constructed to achieve process result coupling, personalized differentiation, tripartite collaboration, dynamic generation, and multi-dimensional evaluation of composite brain capabilities. Research suggests that artificial intelligence will not replace evaluation, but will reshape the “teacher-student-AI” evaluation community. In the future, continuous exploration is needed in areas such as cognitive digital twins, quantum privacy computing, and generative evaluation ethics, to enhance rationality with technology and protect values with humanities.