针对人工智能平台(如DeepSeek、豆包等)的普及对线上学情评价体系的冲击，基于对传统在线学情评价体系及编程类课程的综合分析，提出一种完全过程化评价体系，旨在通过细致的过程管理和阶段性评价，激发和培养学生的学习主动性和内驱力。文章通过与传统学情评价体系的对比，给出该体系的结构与组成，从多门编程类课程的知识结构出发，对该体系适用编程类课程的可行性进行分析，给出该体系在Web程序设计课程中的实践案例，并从课程的适用性、效用和实践重难点等角度详细介绍该体系的具体实施过程，以期为当前学情评价体系和编程类课程考核体系的改革提供具有实践性的参考。

Against the impact of the popularization of artificial intelligence platforms such as DeepSeek and Doubao on the online course evaluation system,based on a comprehensive analysis of the traditional online course evaluation system and programming courses,a fully process-oriented evaluation system is proposed.This system aims to stimulate and cultivate students' learning initiative and internal motivation through meticulous process management and phased evaluations.By comparing with the traditional course evaluation system,the structure and composition of this system are presented.Starting from the knowledge structures of multiple programming courses,the feasibility of applying this system to programming courses is analyzed.A practical case of this system in the web programming courses provided,and the specific implementation process of this system is introduced in detail from the perspectives of course applicability,effectiveness,and key and difficult points in practice,with the expectation of providing practical references for the reform of the current course evaluation system,especially the assessment system of programming courses.