AI浪潮下《自然语言处理》课程教学改革探索

Exploring Teaching Reform of “Natural Language Processing” Course under the AI Wave

摘要: 文章针对当前《自然语言处理》课程教学中存在的“数理知识储备要求高与浅应用矛盾突出、实践资源匮乏、评价方式单一”等核心问题，提出并实践了一套系统性的教学改革方案。通过构建前置知识、基础理论、核心技术、前沿应用和工程实践五级递进内容体系，创新实施“项目驱动 + 串联对比 + 双导师协同”的教学方法，并建立融合项目实现、答辩与过程化考核的多维动态评价机制。改革有效降低了学习门槛，强化了真实场景实践，全面提升了学生的工程能力、创新思维与技术迁移能力，为新工科背景下人工智能类课程建设提供了可借鉴的范式。

Abstract: This paper addresses the core problems in current “Natural Language Processing” courses, such as the prominent contradiction between high learning barriers and superficial applications, a lack of practical resources, and a single evaluation method. It proposes and implements a systematic teaching reform plan. By constructing a five-level progressive content system encompassing prerequisite knowledge, basic theory, core technologies, cutting-edge applications, and engineering practice, the reform innovatively implements a teaching method of “project-driven + sequential comparison + dual-mentor collaboration”, and establishes a multi-dimensional dynamic evaluation mechanism integrating project implementation, defense, and process-oriented assessment. The reform effectively lowers the learning threshold, strengthens real-world practice, and comprehensively improves students’ engineering capabilities, innovative thinking, and technology transfer abilities, providing a model for the construction of AI courses under the new engineering disciplines.