人工智能赋能野外地质实习的实践与思考——以周口店野外教学实践为例

Practice and Reflection on Artificial Intelligence-Enhanced Field Geology Training—A Case Study of Field Teaching in Zhoukoudian

摘要: 人工智能为野外地质实习中的知识解释、观察提示、记录检查和即时反馈提供了新的技术支持。基于周口店野外教学实践发现，学生虽普遍具备人工智能使用条件，但主动使用意愿较弱，且不同模型、提问方式和背景信息会显著影响回答质量。人工智能要真正服务于野外教学，不能停留在学生自由使用通用工具的层面，而应由教师主导建设课程知识库，设计标准化任务与提问模板，完善审核、留痕和过程评价机制。其核心作用是辅助学生规范观察、完善证据链和开展反思，而非替代现场实践与专业判断。

Abstract: Artificial intelligence provides new technological support for knowledge explanation, observation guidance, field-record checking, and immediate feedback in field geology training. Teaching practice in Zhoukoudian shows that although students generally have access to artificial intelligence tools, their willingness to use them proactively remains limited. Moreover, the quality of AI-generated responses is significantly affected by the model selected, the way questions are formulated, and the amount of background information provided. To effectively integrate artificial intelligence into field teaching, its application should not be limited to students’ unstructured use of general-purpose tools. Instead, teachers should take the lead in developing course-specific knowledge bases, designing standardized learning tasks and prompting templates, and establishing mechanisms for content review, process documentation, and formative assessment. The primary role of artificial intelligence is to help students standardize geological observations, strengthen evidence-based reasoning, and promote reflection, rather than replace field practice or professional judgment.