基于气质联用技术的高等仪器分析课程教改实践与探索

Teaching Reform Practice and Exploration of Advanced Instrumental Analysis Courses Based on GC-MS Technology

摘要: 针对高等仪器分析课程中气质联用(GC-MS)教学中长期存在的“重操作轻应用、理论与产业脱节、能力培养单一”等问题，文章构建了以“AI赋能–虚拟仿真–多维评价”为核心的立体化教学改革体系。通过引入真实检测场景、重构模块化教学内容、创新过程性考核方式，并结合GC-MS的技术特点，系统设计了融合人工智能与虚拟仿真的教学环节。教改重点在于推动AI与教学的深度融合，依托线上虚拟仿真平台，实现GC-MS全流程的模拟操作与原理可视化。该模式使学生在无实体设备依赖的情况下，能够充分理解仪器原理、熟练掌握操作流程，有效突破了传统教学中资源受限、实操机会不足的瓶颈。实践表明，改革后学生GC-MS全流程操作熟练度提升了72%，数据解析正确率从38%提升至81%，学生熟练操作所需时间节省60%，为“新工科”背景下分析检测人才的培养提供了可复制、可推广的有效路径。

Abstract: In response to long-standing issues in Gas Chromatography-Mass Spectrometry (GC-MS) teaching in the Advanced Instrumental Analysis curriculum—such as “emphasizing operation over application, disconnection between theory and industry, and singular skill cultivation”—this paper constructs a three-dimensional teaching reform framework centered on “AI Empowerment, Virtual Simulation, and Multi-dimensional Evaluation.” By introducing real-world detection scenarios, restructuring modular teaching content, innovating process-oriented assessment methods, and aligning with the technical characteristics of GC-MS, teaching segments that integrate artificial intelligence and virtual simulation were systematically designed. The reform focuses on deeply integrating AI with teaching, leveraging an online virtual simulation platform to simulate the entire GC-MS workflow and visualize its principles. This model enables students to thoroughly understand the instrument principles and master operational procedures without relying on physical equipment, effectively overcoming the bottlenecks of limited resources and insufficient hands-on opportunities in traditional teaching. Practice has shown that after the reform, students’ proficiency in the full GC-MS operational process increased by 72%, the accuracy of data interpretation rose from 38% to 81%, and the time required for students to achieve proficiency was reduced by 60%. This provides a replicable and scalable effective pathway for cultivating analytical testing talents under the “Emerging Engineering Education” framework.